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Collect awesome best papers from top AI conferences.
https://github.com/familyld/Awesome-Best-Papers
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Collect awesome best papers from top AI conferences.
Host: GitHub
URL: https://github.com/familyld/Awesome-Best-Papers
Owner: familyld
Created: 2019-11-18T02:09:39.000Z (almost 5 years ago)
Default Branch: master
Last Pushed: 2022-06-14T04:16:05.000Z (over 2 years ago)
Last Synced: 2024-07-29T17:45:41.186Z (about 2 months ago)
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Forks: 43
Open Issues: 2
Metadata Files:
- Readme: README.md
Awesome Lists containing this project

awesome-artificial-intelligence - Awesome Best Papers - Collect awesome best papers from top AI conferences. (Awesome lists for learning AI)
ultimate-awesome - Awesome-Best-Papers - Collect awesome best papers from top AI conferences. (Other Lists / PowerShell Lists)
README

        # Awesome Best Papers

本项目收集了各大顶会的最佳论文（*自 2013 年起*），包括*论文名、论文链接、作者名以及机构名*（多个机构并列时记录第一个）。所有的数据都是手工输入的，所以 *如果你发现有任何错误，欢迎开个 issue 提醒我*。你也可以通过 *创建 pull requests* 的方式参与到这个项目中来，加入机器人、优化、图形学等本项目未包含领域的顶会最佳论文信息（**非常欢迎**）。项目中的部分数据参考了 Jeff Huang 的网站，他收集了自 1996 年起计算机科学领域部分顶会的最佳论文，如果你感兴趣，也可以访问[他的网站](https://jeffhuang.com/best_paper_awards.html)。

This repo collects best papers from various top conferences (*since 2013*), including *paper names and links, author names and organization names* (use the first one when the author works for multiple organizations). All the data are collected and entered by hand, so *feel free to open an issue if you find anything wrong*. You can also contribute to this repo by *creating pull requests* and add best papers from top conferences in research areas that are not covered in this repo, e.g., robotics, optimization, computer graphics and etc (**very welcome**). Part of the data is collected by Jeff Huang. If you are interested in more best papers in computer science (since 1996), you can visit [his website](https://jeffhuang.com/best_paper_awards.html).

# Table of Content

| Domain | Conferences |

| :-  |  :-   |

| Cross-domain | [AAAI](#aaai), [IJCAI](#ijcai), [NeurIPS](#neurips), [ICML](#icml), [ICLR](#iclr), [WWW](#www) |

| Data Mining and Information Retrieval | [KDD](#kdd), [SIGIR](#sigir), [CIKM](#cikm), [ICDM](#icdm), [WSDM](#wsdm), [RecSys](#recsys) |

| Computer Vision | [CVPR](#cvpr), [ICCV](#iccv), [ECCV](#eccv) |

| Natural Language Processing | [ACL](#acl), [EMNLP](#emnlp), [NAACL](#naacl), [EACL](#eacl) |

# Format

This repo is writen in Markdown. Each entry follows the following format. 

```markdown

| Year | Paper |

| :-:  |  :-   |

| 2020 | **[Paper title](Link to pdf)**
AuthorName (Organization); AuthorName (Organization) |

```

When multiple best papers are available:

```markdown

| Year | Paper |

| :-:  |  :-   |

| 2020 | 1. **[Paper title](Link to pdf)**
AuthorName (Organization); AuthorName (Organization)
2. **[Paper title](Link to pdf)**
AuthorName (Organization); AuthorName (Organization) |

```

# Deadlines

Thanks to [Abhishek Das](https://github.com/abhshkdz) and [Jackie Tseng](https://github.com/JackieTseng/), the exact dates of AI conferences are available on:

1. [AI Conference Deadlines](https://aideadlin.es/)

2. [jackietseng.github.io/conference_call_for_paper](https://jackietseng.github.io/conference_call_for_paper/conferences.html)

To make it easier to find the most recent conferences, the following table sorts each conference by therir deadlines.

| Conference | Date | Deadline |

|:-:|:-:|:-:|

| CVPR | Late Jun | Mid Jan |

| IJCAI | Late Aug | Late Jan |

| SIGIR | Mid Jul | Early Feb |

| ICML | Late Jul | Early Feb |

| KDD | Mid Aug | Early Feb |

| ECCV | Late Aug | Early Mar |

| ICCV | Mid Oct | Mid Mar |

| RecSys | Late Sep | Early May |

| EMNLP | Mid Nov | Mid May |

| NeurIPS | Early Dec | Late May |

| CIKM | Early Nov | Late May |

| ICDM | Early Dec | Mid Jun |

| ACL | Early Feb | Early Aug |

| WSDM | Late Feb | Early Aug |

| AAAI | Late Feb | Early Sep |

| EACL | Late Apr | Early Oct |

| ICLR | Late Apr | Early Oct |

| WWW | Late Apr | Late Oct |

| NAACL | Early Jun | Late Nov |

# List of Best Papers



## AAAI

The full list of AAAI outstanding papers (including best student papers and their Honorable Mentions) is presented on [this website](https://aaai.org/Awards/paper.php).

| Year | Paper |

|:-:|:-|

| 2021 | 1. **[Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting](https://arxiv.org/pdf/2012.07436.pdf)**
Haoyi Zhou (Beihang University); Shanghang Zhang (UC Berkeley); Jieqi Peng (Beihang University); Shuai Zhang (Beihang University); Jianxin Li (Beihang University); Hui Xiong (Rutgers University); Wancai Zhang (Beijing Guowang Fuda Science & Technology Development Company) 
2. **[Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory](https://arxiv.org/abs/2012.03083)**
Stefanos Leonardos (Singapore University of Technology and Design); Georgios Piliouras (Singapore University of Technology and Design) 
3. **[Mitigating Political Bias in Language Models Through Reinforced Calibration](https://www.cs.dartmouth.edu/~rbliu/aaai_copy.pdf)**
Ruibo Liu (Dartmouth College); Chenyan Jia (University of Texas at Austin); Jason Wei (Google AI); Guangxuan Xu (Dartmouth College); Lili Wang (Dartmouth College); Soroush Vosoughi (Dartmouth College) |

| 2020 | **[WinoGrande: An Adversarial Winograd Schema Challenge at Scale](https://arxiv.org/pdf/1907.10641.pdf)**
Keisuke Sakaguchi (Allen Institute for Artificial Intelligence); Ronan Le Bras (Allen Institute for Artificial Intelligence); Chandra Bhagavatula (Allen Institute for Artificial Intelligence); Yejin Choi (University of Washington) |

| 2019 | **[How to Combine Tree-Search Methods in Reinforcement Learning](https://arxiv.org/pdf/1809.01843.pdf)**
Yonathan Efroni (Technion); Gal Dala (Technion); Bruno Scherrer (INRIA); Shie Mannor (Technion) |

| 2018 | **[Memory-Augmented Monte Carlo Tree Search](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/download/17139/15841)**
Chenjun Xiao (University of Alberta); Jincheng Mei (University of Alberta); Martin Müller (University of Alberta) |

| 2017 | **[Label-Free Supervision of Neural Networks with Physics and Domain Knowledge](https://arxiv.org/pdf/1609.05566.pdf)**
Russell Stewart (Stanford University);  Stefano Ermon (Stanford University) |

| 2016 | **[Bidirectional Search That Is Guaranteed to Meet in the Middle](https://people.engr.tamu.edu/guni/Papers/AAAI16-MM.pdf)**
Robert C. Holte (University of Alberta); Ariel Felner (Ben-Gurion University); Guni Sharon (Ben-Gurion University); Nathan R. Sturtevant (University of Denver) |

| 2015 | **[From Non-Negative to General Operator Cost Partitioning](https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/download/9983/9762)**
Florian Pommerening (University of Basel); Malte Helmert (University of Basel); Gabriele Röger (University of Basel); Jendrik Seipp (University of Basel) |

| 2014 | **[Recovering from Selection Bias in Causal and Statistical Inference](http://ftp.cs.ucla.edu/pub/stat_ser/r425.pdf)**
Elias Bareinboim (UCLA); Jin Tian (Iowa State University); Judea Pearl (UCLA) |

| 2013 | 1. **[HC-Search: Learning Heuristics and Cost Functions for Structured Prediction](http://web.engr.oregonstate.edu/~afern/papers/aaai13-hcsearch.pdf)**
Janardhan Rao Doppa (Oregon State University); Alan Fern (Oregon State University); Prasad Tadepalli (Oregon State University)
2. **[SMILe: Shufﬂed Multiple-Instance Learning](https://www.aaai.org/ocs/index.php/AAAI/AAAI13/paper/view/6405/7131)**
Gary Doran (Case Western Reserve University); Soumya Ray (Case Western Reserve University) |



## IJCAI

IJCAI Distinguished papers.

| Year | Paper |

|:-:|:-|

| 2019 | **[Boosting for Comparison-Based Learning](https://arxiv.org/pdf/1810.13333.pdf)**
Michaël Perrot (Max-Planck-Institute for Intelligent Systems); Ulrike von Luxburg (University of Tubingen) |

| 2018 | 1. **[Reasoning about Consensus when Opinions Diffuse through Majority Dynamics](https://www.ijcai.org/Proceedings/2018/0007.pdf)**
Vincenzo Auletta (University of Salerno); Diodato Ferraioli (University of Salerno); Gianluigi Greco (University of Calabria)
2. **[SentiGAN: Generating Sentimental Texts via Mixture Adversarial Networks](https://www.ijcai.org/Proceedings/2018/0618.pdf)**
Ke Wang (Peking University); Xiaojun Wan (Peking University)
3. **[From Conjunctive Queries to Instance Queries in Ontology-Mediated Querying](https://www.ijcai.org/Proceedings/2018/0250.pdf)**
Cristina Feier (University of Bremen); Carsten Lutz (University of Bremen); Frank Wolte (University of Liverpool)
4. **[What game are we playing? End-to-end learning in normal and extensive form games](https://arxiv.org/pdf/1805.02777.pdf)**
Chun Kai Ling (Carnegie Mellon University); Fei Fang (Carnegie Mellon University); J. Zico Kolter (Carnegie Mellon University)
5. **[Commonsense Knowledge Aware Conversation Generation with Graph Attention](https://www.ijcai.org/Proceedings/2018/0643.pdf)**
Hao Zhou (Tsinghua University); Tom Young (Beijing Institute of Technology); Minlie Huang (Tsinghua University); Haizhou Zhao, Sogou Inc.; Jingfang Xu, Sogou Inc.; Xiaoyan Zhu (Tsinghua University)
6. **[R-SVM+: Robust Learning with Privileged Information](https://www.ijcai.org/Proceedings/2018/0334.pdf)**
Xue Li (Wuhan University); Bo Du (Wuhan University); Chang Xu (University of Sydney); Yipeng Zhang (Wuhan University); Lefei Zhang (Wuhan University); Dacheng Tao (University of Sydney)
7. **[A Degeneracy Framework for Graph Similarity](https://www.ijcai.org/Proceedings/2018/0360.pdf)**
Giannis Nikolentzos, École Polytechnique; Polykarpos Meladianos (Athens University of Economics and Business); Stratis Limnios, École Polytechnique; Michalis Vazirgiannis (École Polytechnique) |

| 2017 | **[Foundations of Declarative Data Analysis Using Limit Datalog Programs](https://www.cs.ox.ac.uk/people/boris.motik/pubs/kcgkmh17limit-datalog.pdf)**
Mark Kaminski (University of Oxford); Bernardo Cuenca Grau (University of Oxford); Egor V. Kostylev (University of Oxford); Boris Motik (University of Oxford); Ian Horrocks (University of Oxford) |

| 2016 | **[Hierarchical Finite State Controllers for Generalized Planning](https://arxiv.org/pdf/1911.02887.pdf)**
Javier Segovia (Universitat Pompeu Fabra); Sergio Jiménez (Universitat Pompeu Fabra); Anders Jonsson (Universitat Pompeu Fabra) |

| 2015 | 1. **[Bayesian Active Learning for Posterior Estimation](https://www.cs.cmu.edu/~schneide/kandasamyIJCAI15activePostEst.pdf)**
Kirthevasan Kandasamy (Carnegie Mellon University); Jeff Schneider (Carnegie Mellon University); Barnabas Poczos (Carnegie Mellon University)
2. **[Recursive Decomposition for Nonconvex Optimization](https://arxiv.org/pdf/1611.02755.pdf)**
Abram L. Friesen (University of Washington); Pedro Domingos (University of Washington) |

| 2013 | 1. **[Bayesian Optimization in High Dimensions via Random Embeddings](https://www.cs.ubc.ca/~hutter/papers/13-IJCAI-BO-highdim.pdf)**
Ziyu Wang (University of British Columbia); Masrour Zoghi (University of Amsterdam); Frank Hutter (Freiberg University); David Matheson (University of British Columbia); Nando de Freitas (University of British Columbia)
2. **[Flexibility and Decoupling in the Simple Temporal Problem](https://www.ijcai.org/Proceedings/13/Papers/356.pdf)**
Michel Wilson (Delft University of Technology); Tomas Klos (Delft University of Technology); Cees Witteveen (Delft University of Technology); Bob Huisman (Delft University of Technology) |



## NeurIPS

| Year | Paper |

|:-:|:-|

| 2020 | 1. **[No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium](https://arxiv.org/pdf/2004.00603.pdf)**
Andrea Celli (Politecnico di Milano); Alberto Marchesi (Politecnico di Milano); Gabriele Farina (Carnegie Mellon University); Nicola Gatti (Politecnico di Milano)
2. **[Improved Guarantees and a Multiple-Descent Curve for Column Subset Selection and the Nyström Method](https://arxiv.org/pdf/2002.09073.pdf)**
Michal Derezinski (UC Berkeley); Rajiv Khanna (UC Berkeley); Michael W. Mahoney (UC Berkeley)
3. **[Language Models are Few-Shot Learners](https://arxiv.org/pdf/2005.14165.pdf)**
Tom B. Brown (OpenAI); Benjamin Mann (OpenAI); Nick Ryder (OpenAI); Melanie Subbiah (OpenAI); Jared D. Kaplan (Johns Hopkins University); Prafulla Dhariwal (OpenAI); Arvind Neelakantan (OpenAI); Pranav Shyam (OpenAI); Girish Sastry (OpenAI); Amanda Askell (OpenAI); Sandhini Agarwal (OpenAI); Ariel Herbert-Voss (OpenAI); Gretchen M. Krueger (OpenAI); Tom Henighan (OpenAI); Rewon Child (OpenAI); Aditya Ramesh (OpenAI); Daniel Ziegler (OpenAI); Jeffrey Wu (OpenAI); Clemens Winter (OpenAI); Chris Hesse (OpenAI); Mark Chen (OpenAI); Eric Sigler (OpenAI); Mateusz Litwin (OpenAI); Scott Gray (OpenAI); Benjamin Chess (OpenAI); Jack Clark (OpenAI); Christopher Berner (OpenAI); Sam McCandlish (OpenAI); Alec Radford (OpenAI); Ilya Sutskever (OpenAI); Dario Amodei (OpenAI) |

| 2019 | **[Distribution-Independent PAC Learning of Halfspaces with Massart Noise](https://arxiv.org/pdf/1906.10075.pdf)**
Ilias Diakonikolas (University of Wisconsin-Madison); Themis Gouleakis (Max Planck Institute for Informatics) |

| 2018 | 1. **[Non-delusional Q-learning and Value-iteration](https://papers.nips.cc/paper/8200-non-delusional-q-learning-and-value-iteration.pdf)**
Tyler Lu; Dale Schuurmans; Craig Boutilier
2. **[Optimal Algorithms for Non-Smooth Distributed Optimization in Networks](https://papers.nips.cc/paper/7539-optimal-algorithms-for-non-smooth-distributed-optimization-in-networks.pdf)**
Kevin Scaman ; Francis Bach ; Sebastien Bubeck ; Laurent Massoulié ; Yin Tat Lee
3. **[Nearly Tight Sample Complexity Bounds for Learning Mixtures of Gaussians via Sample Compression Schemes](https://papers.nips.cc/paper/7601-nearly-tight-sample-complexity-bounds-for-learning-mixtures-of-gaussians-via-sample-compression-schemes.pdf)**
Hassan Ashtiani ; Shai Ben-David ; Nick Harvey ; Christopher Liaw ; Abbas Mehrabian ; Yaniv Plan
4. **[Neural Ordinary Differential Equations](https://papers.nips.cc/paper/7892-neural-ordinary-differential-equations.pdf)**
Tian Qi Chen ; Yulia Rubanova ; Jesse Bettencourt ; David Duvenaud |

| 2017 | 1. **[Safe and Nested Subgame Solving for Imperfect-Information Games](http://papers.nips.cc/paper/6671-safe-and-nested-subgame-solving-for-imperfect-information-games.pdf)**
Noam Brown (Carnegie Mellon University); Tuomas Sandholm(Carnegie Mellon University)
2. **[Variance-based Regularization with Convex Objectives](https://papers.nips.cc/paper/6890-variance-based-regularization-with-convex-objectives.pdf)**
Hongseok Namkoong (Stanford University); John Duchi (Stanford University)
3. **[A Linear-Time Kernel Goodness-of-Fit Test](https://arxiv.org/pdf/1705.07673.pdf)**
Wittawat Jitkrittum (University College London), Wenkai Xu (University College London), Zoltan Szabo (École Polytechnique), Kenji Fukumizu (The Institute of Statistical Mathematics), Arthur Gretton (University College London) |

| 2016 | **[Value Iteration Networks](http://papers.nips.cc/paper/6046-value-iteration-networks.pdf)**
Aviv Tamar (UC Berkeley); Yi Wu (UC Berkeley); Garrett Thomas (UC Berkeley); Sergey Levine (UC Berkeley); Pieter Abbeel (UC Berkeley)|

| 2015 | 1. **[Competitive Distribution Estimation: Why is Good-Turing Good](http://papers.nips.cc/paper/5762-competitive-distribution-estimation-why-is-good-turing-good.pdf)**
Alon Orlitsky (UC San Diego); Ananda Suresh (UC San Diego)
2. **[Fast Convergence of Regularized Learning in Games](http://papers.nips.cc/paper/5763-fast-convergence-of-regularized-learning-in-games.pdf)**
Vasilis Syrgkanis (Microsoft Research); Alekh Agarwal (Microsoft Research); Haipeng Luo (Princeton University); Robert Schapire (Microsoft Research) |

| 2014 | 1. **[Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)](http://papers.nips.cc/paper/5329-asymmetric-lsh-alsh-for-sublinear-time-maximum-inner-product-search-mips.pdf)**
Anshumali Shrivastava (Cornell University); Ping Li (Rutgers University)
 2. **[A\* Sampling](http://papers.nips.cc/paper/5449-a-sampling.pdf)**
Christopher Maddison (University of Toronto); Daniel Tarlow (Microsoft Research); Tom Minka (Microsoft Research) |

| 2013 | 1. **[A memory frontier for complex synapses](http://papers.nips.cc/paper/4872-a-memory-frontier-for-complex-synapses.pdf)**
Subhaneil Lahiri (Stanford University); Surya Ganguli (Stanford University)
2. **[Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints](http://papers.nips.cc/paper/4911-submodular-optimization-with-submodular-cover-and-submodular-knapsack-constraints.pdf)**
Rishabh Iyer (University of Washington, Seattle); Jeff Bilmes (University of Washington, Seattle)
3. **[Scalable Influence Estimation in Continuous-Time Diffusion Networks](http://papers.nips.cc/paper/4857-scalable-influence-estimation-in-continuous-time-diffusion-networks.pdf)**
Nan Du (Georgia Tech); Le Song (Georgia Tech); Manuel Gomez-Rodriguez (MPI for Intelligent Systems); Hongyuan Zha (Georgia Tech) |



## ICML

ICML Outstanding Papers.

| Year | Paper |

|:-:|:-|

| 2021 | **[Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies](http://proceedings.mlr.press/v139/vicol21a/vicol21a.pdf)**
Paul Vicol (University of Toronto); Luke Metz (Google Brain); Jascha Sohl-Dickstein (Google Brain) |

| 2020 | 1. **[On Learning Sets of Symmetric Elements](https://proceedings.icml.cc/static/paper_files/icml/2020/1625-Paper.pdf)**
Haggai Maron (NVIDIA Research); Or Litany (Stanford University); Gal Chechik (Stanford University); Ethan Fetaya (Bar Ilan University)
2. **[Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems](https://proceedings.icml.cc/static/paper_files/icml/2020/4134-Paper.pdf)**
Kaixuan Wei (Beijing Institute of Technology); Angelica I Aviles-Rivero (University of Cambridge); Jingwei Liang (University of Cambridge); Ying Fu (Beijing Institute of Technology); Carola-Bibiane Schönlieb (University of Cambridge); Hua Huang (Beijing Institute of Technology) |

| 2019 | 1. **[Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations](http://proceedings.mlr.press/v97/locatello19a/locatello19a.pdf)**
Francesco Locatello (ETH Zurich); Stefan Bauer (MaxPlanck Institute for Intelligent Systems); Mario Lucic (Google Brain); Gunnar Rätsch (Google Brain); Sylvain Gelly  (ETH Zurich); Bernhard Schölkopf (MaxPlanck Institute for Intelligent Systems); Olivier Bachem (Google Brain)
2. **[Rates of Convergence for Sparse Variational Gaussian Process Regression](https://arxiv.org/pdf/1903.03571.pdf)**
David R. Burt (University of Cambridge); Carl Edward Rasmussen (University of Cambridge); Mark van der Wilk (PROWLER.io) |

| 2018 | 1. **[Delayed Impact of Fair Machine Learning](https://arxiv.org/pdf/1803.04383.pdf)**
Lydia T. Liu (University of California Berkeley); Sarah Dean (University of California Berkeley); Esther Rolf (University of California Berkeley); Max Simchowitz (University of California Berkeley); Moritz Hardt (University of California Berkeley)
2. **[Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples](https://arxiv.org/pdf/1802.00420.pdf)**
Anish Athalye (Massachusetts Institute of Technology); Nicholas Carlini (University of California Berkeley); David Wagner (University of California Berkeley) |

| 2017 | **[Understanding Black-box Predictions via Influence Functions](https://arxiv.org/pdf/1703.04730.pdf)**
Pang Wei Koh (Stanford University); Percy Liang (Stanford University) |

| 2016 | 1. **[Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling](http://proceedings.mlr.press/v48/sa16.pdf)**
Christopher De Sa (Stanford University); Chris Re (Stanford University); Kunle Olukotun (Stanford University)
2. **[Pixel Recurrent Neural Networks](https://arxiv.org/pdf/1601.06759.pdf)**
Aaron Van den Oord (Google); Nal Kalchbrenner (Google); Koray Kavukcuoglu (Google)
3. **[Dueling Network Architectures for Deep Reinforcement Learning](https://arxiv.org/pdf/1511.06581.pdf)**
Ziyu Wang (Google); Tom Schaul (Google); Matteo Hessel (Google); Hado van Hasselt (Google); Marc Lanctot (Google); Nando de Freitas (University of Oxford) |

| 2015 | 1. **[A Nearly-Linear Time Framework for Graph-Structured Sparsity](http://proceedings.mlr.press/v37/hegde15.pdf)**
Chinmay Hegde (Massachusetts Institute of Technology); Piotr Indyk (Massachusetts Institute of Technology); Ludwig Schmid (Massachusetts Institute of Technology)
2. **[Optimal and Adaptive Algorithms for Online Boosting](https://arxiv.org/pdf/1502.02651.pdf)**
Alina Beygelzimer (Yahoo! Research); Satyen Kale (Yahoo! Research); Haipeng Luo (Princeton University) |

| 2014 | **[Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis](http://proceedings.mlr.press/v32/tang14.pdf)**
Jian Tang (Peking University); Zhaoshi Meng (University of Michigan); XuanLong Nguyen (University of Michigan); Qiaozhu Mei (University of Michigan); Ming Zhang (Peking University) |

| 2013 | 1. **[Vanishing Component Analysis](https://mlai.cs.huji.ac.il/publications/Amir_Globerson/files/Vanishing%20Component%20Analysis.pdf)**
Roi Livni (The Hebrew University of Jerusalum); David Lehavi (Hewlett-Packard Labs); Sagi Schein (Hewlett-Packard Labs); Hila Nachlieli (Hewlett-Packard Labs); Shai Shalev Shwartz (The Hebrew University of Jerusalum); Amir Globerson (The Hebrew University of Jerusalum)
2. **[Fast Semidifferential-based Submodular Function Optimization](https://arxiv.org/pdf/1308.1006.pdf)**
Rishabh Iyer (University of Washington); Stefanie Jegelka (University of California Berkeley); Jeff Bilmes (University of Washington) |



## ICLR

ICLR Outstanding Papers.

| Year | Paper |

|:-:|:-|

| 2021 | 1. **[Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with 1/n Parameters](https://openreview.net/pdf?id=rcQdycl0zyk)**
Aston Zhang (Amazon); Yi Tay (Google Research); Shuai Zhang (ETH ZURICH); Alvin Chan (Nanyang Technological University);, Anh Tuan Luu (Nanyang Technological University);, Siu Hui (Nanyang Technological University);, Jie Fu (Mila, Universite de Montreal)
2. **[Complex Query Answering with Neural Link Predictors](https://openreview.net/pdf?id=Mos9F9kDwkz)**
Erik Arakelyan (University College London); Daniel Daza (Vrije Universiteit Amsterdam); Pasquale Minervini (University College London); Michael Cochez (Vrije Universiteit Amsterdam)
3. **[EigenGame: PCA as a Nash Equilibrium](https://openreview.net/pdf?id=NzTU59SYbNq)**
Ian Gemp (DeepMind); Brian McWilliams (DeepMind); Claire Vernade (DeepMind); Thore Graepel (DeepMind)
4. **[Learning Mesh-Based Simulation with Graph Networks](https://openreview.net/pdf?id=roNqYL0_XP)**
Tobias Pfaff (DeepMind); Meire Fortunato (DeepMind); Alvaro Sanchez-Gonzalez (DeepMind); Peter Battaglia (DeepMind)
 5. **[Neural Synthesis of Binaural Speech from Mono Audio](https://openreview.net/pdf?id=uAX8q61EVRu)**
Alexander Richard (Facebook); Dejan Markovic (Facebook); Israel D. Gebru (Facebook); Steven Krenn (Facebook); Gladstone Alexander Butler (Facebook); Fernando Torre (Facebook); Yaser Sheikh (Facebook)
6. **[Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime](https://openreview.net/pdf?id=PULSD5qI2N1)**
Atsushi Nitanda (The University of Tokyo); Taiji Suzuki (The University of Tokyo)
7. **[Rethinking Architecture Selection in Differentiable NAS](https://openreview.net/pdf?id=PKubaeJkw3)**
Ruochen Wang (UCLA); Minhao Cheng (UCLA); Xiangning Chen (UCLA); Xiaocheng Tang (DiDi); Cho-Jui Hsieh (UCLA)
8. **[Score-Based Generative Modeling through Stochastic Differential Equations](https://openreview.net/pdf?id=PxTIG12RRHS)**
Yang Song (Stanford University); Jascha Sohl-Dickstein (Google Brain); Diederik P Kingma (Google Brain); Abhishek Kumar (Google Brain); Stefano Ermon (Stanford University); Ben Poole (Google Brain)|



## WWW

The Web Conference.

| Year | Paper |

|:-:|:-|

| 2021 | **[Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach](https://arxiv.org/pdf/2101.07714.pdf)**
Ashish Sharma (University of Washington); Inna Lin (University of Washington); Adam Miner (Stanford University); David Atkins (University of Washington); Tim Althoff (University of Washington) |

| 2020 | **[Open Intent Extraction from Natural Language Interactions](https://dl.acm.org/doi/abs/10.1145/3366423.3380268)**
Nikhita Vedula (The Ohio State University); Nedim Lipka (Adobe); Pranav Maneriker (The Ohio State University); Srinivasan Parthasarathy (The Ohio State University) |

| 2019 | 1. **[Ermes: Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification](https://arxiv.org/pdf/1806.02557.pdf)**
Zhenpeng Chen (Peking University); Sheng Shen (University of California, Berkeley); Ziniu Hu (University of California, Berkeley); Xuan Lu (Peking University); Qiaozhu Mei (University of Michigan); Xuanzhe Liu (Peking University)
2. **[OUTGUARD: Detecting In-Browser Covert Cryptocurrency Mining in the Wild](https://nikita.ca/papers/outguard-www19.pdf)**
Amin Kharraz (University of Illinois at Urbana-Champaign); Zane Ma (University of Illinois at Urbana-Champaign); Paul Murley (University of Illinois at Urbana-Champaign); Charles Lever (Georgia Institute of Technology); Joshua Mason (University of Illinois at Urbana-Champaign); Andrew Miller (University of Illinois at Urbana-Champaign); Nikita Borisov (University of Illinois at Urbana-Champaign); Manos Antonakakis (Georgia Institute of Technology); Michael Bailey (University of Illinois at Urbana-Champaign) |

| 2018 | **[HighLife: Higher-arity Fact Harvesting](https://dl.acm.org/doi/10.1145/3178876.3186000)**
Patrick Ernst (Saarland Informatics Campus in Saarbrücken); Amy Siu (Saarland Informatics Campus in Saarbrücken); Gerhard Weikum (Saarland Informatics Campus in Saarbrücken) |

| 2017 | [Currently missing.](http://www.www2017.com.au/) |

| 2016 | **[Social Networks Under Stress](https://arxiv.org/pdf/1602.00572.pdf)**
Daniel Romero (University of Michigan); Brian Uzzi (Northwestern University); Jon Kleinberg (Cornell University) |

| 2015 | **[HypTrails: A Bayesian Approach for Comparing Hypotheses About Human Trails on the Web](https://arxiv.org/pdf/1411.2844.pdf)**
Philipp Singer (GESIS - Leibniz Institute for the Social Sciences); Denis Helic (Graz University of Technology); Andreas Hotho, University of Würzburg; Markus Strohmaier (GESIS - Leibniz Institute for the Social Sciences） |

| 2014 | **[Efficient Estimation for High Similarities using Odd Sketches](https://www.itu.dk/people/pagh/papers/oddsketch.pdf)**
Michael Mitzenmacher (Harvard University); Rasmus Pagh (IT University of Copenhagen); Ninh Pham (IT University of Copenhagen) |

| 2013 | **[No Country for Old Members: User Lifecycle and Linguistic Change in Online Communities](https://nlp.stanford.edu/pubs/linguistic_change_lifecycle.pdf)**
Cristian Danescu-Niculescu-Mizil (Stanford University); Robert West (Stanford University); Dan Jurafsky (Stanford University); Jure Leskovec (Stanford University); Christopher Potts (Stanford University) |

---



## KDD

KDD has two paper tracks, i.e., the Research Track and the Applied Data Science Track. I only report the best papers for the research track in this repo but the ADS track is remarkable as well.

| Year | Paper |

|:-:|:-|

| 2020 | **[On Sampled Metrics for Item Recommendation](https://dl.acm.org/doi/pdf/10.1145/3394486.3403226)**
Walid Krichene (Google Research); Steffen Rendle (Google Research) |

| 2019 | **[Network Density of States](https://www.cs.cornell.edu/~bindel/papers/2019-kdd.pdf)**
Kun Dong (Cornell University); Austin Benson (Cornell University); David Bindel (Cornell University) |

| 2018 | **[Adversarial Attacks on Neural Networks for Graph Data](https://arxiv.org/pdf/1805.07984.pdf)**
Daniel Zügner (Technical University of Munich); Amir Akbarnejad (Technical University of Munich); Stephan Günnemann (Technical University of Munich) |

| 2017 | **[Accelerating Innovation Through Analogy Mining](https://arxiv.org/pdf/1706.05585.pdf)**
Tom Hope (Hebrew University of Jerusalem); Joel Chan (Carnegie Mellon University); Aniket Kittur (Carnegie Mellon University); Dafna Shahaf (Hebrew University of Jerusalem) |

| 2016 | **[FRAUDAR: Bounding Graph Fraud in the Face of Camouflage](https://bhooi.github.io/papers/fraudar_kdd16.pdf)**
Bryan Hooi (Carnegie Mellon University); Hyun Ah Song (Carnegie Mellon University); Alex Beutel (Carnegie Mellon University); Neil Shah (Carnegie Mellon University); Kijung Shin (Carnegie Mellon University); Christos Faloutsos (Carnegie Mellon University) |

| 2015 | **[Efficient Algorithms for Public-Private Social Networks](https://www.epasto.org/papers/kdd2015.pdf)**
Flavio Chierichetti (Sapienza University of Rome); Alessandro Epasto (Brown University); Ravi Kumar (Google); Silvio Lattanzi (Google); Vahab Mirrokni (Google) |

| 2014 | **[Reducing the Sampling Complexity of Topic Models](http://www.sravi.org/pubs/fastlda-kdd2014.pdf)**
Aaron Li (Carnegie Mellon University); Amr Ahmed (Google); Sujith Ravi (Google); Alexander Smola (Carnegie Mellon University) |

| 2013 | **[Simple and Deterministic Matrix Sketching](https://arxiv.org/pdf/1206.0594.pdf)**
Edo Liberty (Yahoo! Research) |



## SIGIR

The full list of SIGIR best papers is presented on [this website](https://sigir.org/awards/best-paper-awards/).

| Year | Paper |

|:-:|:-|

| 2021 | **[Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness](https://arxiv.org/pdf/2105.00855.pdf)**
Harrie Oosterhuis (Radboud University) |

| 2020 | **[Controlling Fairness and Bias in Dynamic Learning-to-Rank](https://arxiv.org/pdf/2005.14713.pdf)**
Marco Morik (Technische Univerität Berlin); Ashudeep Singh (Cornell University); Jessica Hong (Cornell University); Thorsten Joachims (Cornell University) |

| 2019 | **[Variance Reduction in Gradient Exploration for Online Learning to Rank](https://arxiv.org/pdf/1906.03766.pdf)**
 Huazheng Wang (University of Virginia); Sonwoo Kim (University of Virginia); Eric McCord-Snook (University of Virginia); Qingyun Wu (University of Virginia); Hongning Wang (University of Virginia) |

| 2018 | **[Should I Follow the Crowd? A Probabilistic Analysis of the Effectiveness of Popularity in Recommender Systems](http://ir.ii.uam.es/pubs/sigir2018.pdf)**
Rocío Cañamares (Universidad Autónoma de Madrid); Pablo Castells (Universidad Autónoma de Madrid) |

| 2017 | **[BitFunnel: Revisiting Signatures for Search](https://danluu.com/bitfunnel-sigir.pdf)**
Bob Goodwin (Microsoft); Michael Hopcroft (Microsoft); Dan Luu (Microsoft); Alex Clemmer (Heptio); Mihaela Curmei (Microsoft); Sameh Elnikety (Microsoft); Yuxiong He (Microsoft) |

| 2016 | **[Understanding Information Need: An fMRI Study](https://core.ac.uk/download/pdf/42370897.pdf)**
Yashar Moshfeghi (University of Glasgow); Peter Triantafillou (University of Glasgow); Frank E. Pollick (University of Glasgow) |

| 2015 | **[QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees](https://www.cse.cuhk.edu.hk/irwin.king/_media/presentations/sigir15bestpaperslides.pdf)**
Claudio Lucchese (Istituto di Scienza e Tecnologie dell'Informazione); Franco Maria Nardini (Istituto di Scienza e Tecnologie dell'Informazione); Salvatore Orlando, Università di Venezia; Raffaele Perego (Istituto di Scienza e Tecnologie dell'Informazione); Nicola Tonellotto (Istituto di Scienza e Tecnologie dell'Informazione); Rossano Venturini (Istituto di Scienza e Tecnologie dell'Informazione) |

| 2014 | **[Partitioned Elias-Fano Indexes](http://groups.di.unipi.it/~ottavian/files/elias_fano_sigir14.pdf)**
Giuseppe Ottaviano (Istituto di Scienza e Tecnologie dell'Informazione); Rossano Venturini (Università di Pisa) |

| 2013 | **[Beliefs and Biases in Web Search](https://www.microsoft.com/en-us/research/wp-content/uploads/2017/01/WhiteSIGIR2013.pdf)**
Ryen W. White (Microsoft Research) |



## CIKM

| Year | Paper |

|:-:|:-|

| 2020 | 1. **[Do People and Neural Networks Pay Attention to the Same Words? Studying Eye-tracking Data for Non-factoid QA Evaluation](http://marksanderson.org/publications/my_papers/CIKM__Do_People_and_Neural_Networks_Pay_Attention_to_the_Same_Words_.pdf)**
Valeriya Bolotova-Baranova (RMIT University); Vladislav Blinov (Ural Federal University); Yukun Zheng (Tsinghua University); Mark Sanderson (University of Massachusetts Amherst); Falk Scholer (RMIT University); Bruce Croft (RMIT University)
2. **[FANG: Leveraging Social Context for Fake News Detection Using Graph Representation](https://arxiv.org/pdf/2008.07939.pdf)**
Van-Hoang Nguyen (National University of Singapore); Kazunari Sugiyama (Kyoto University); Preslav Nakov (Qatar Computing Research Institute; HBKU); Min-Yen Kan (National University of Singapore) |

| 2019 | **[AutoGRD: Model Recommendation Through Graphical Dataset Representation](https://dl.acm.org/doi/10.1145/3357384.3357896)**
Noy Cohen-Shapira (Ben Gurion University of the Negev); Lior Rokach (Ben Gurion University of the Negev); Bracha Shapira (Ben Gurion University of the Negev); Gilad Katz (Ben Gurion University of the Negev); Roman Vainshtein (Ben Gurion University of the Negev) |

| 2018 | **[Relevance estimation with multiple information sources on search engine result pages](http://www.thuir.cn/group/~YQLiu/publications/CIKM18Zhang.pdf)**
Junqi Zhang (Tsinghua University); Yiqun Liu (Tsinghua University); Shaoping Ma (Tsinghua University); Qi Tian (University of Texas at San Antonio) |

| 2017 | **[Hike: A Hybrid Human-Machine Method for Entity Alignment in Large-Scale Knowledge Bases](https://dbgroup.cs.tsinghua.edu.cn/ligl/papers/CIKM2017-Hike.pdf)**
Yan Zhuang (Tsinghua University); Guoliang Li (Tsinghua University); Zhuojian Zhong (Tsinghua University); Jianhua Feng (Tsinghua University) |

| 2016 | **[Vandalism Detection in Wikidata](https://webis.de/downloads/publications/papers/stein_2016m.pdf)**
Stefan Heindorf (Paderborn University); Martin Potthast (Bauhaus-Universität Weimar); Benno Stein (Bauhaus-Universität Weimar); Gregor Engels (Paderborn University) |

| 2015 | **[Assessing the Impact of Syntactic and Semantic Structures for Answer Passages Reranking](http://casa.disi.unitn.it/moschitti/since2013/2015_CIKM_Tymoshenko_Assessing_Impact_Syntactic.pdf)**
Kateryna Tymoshenko (University of Trento); Alessandro Moschitti (Qatar Computing Research Institute) |

| 2014 | **[Cross-Device Search](https://www.microsoft.com/en-us/research/wp-content/uploads/2017/01/MontanezCIKM2014.pdf)**
George Montanez (Carnegie Mellon University); Ryen White (Microsoft Research); Xiao Huang (Microsoft) |

| 2013 | **[Penguins in Sweaters, or Serendipitous Entity Search on User-generated Content](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.418.5058&rep=rep1&type=pdf)**
Ilaria Bordino (Yahoo! Research); Yelena Mejova (Yahoo! Research); Mounia Lalmas (Yahoo! Research) |



## ICDM

The full list of ICDM best papers and best student papers is presented on [this website](http://39.104.72.142:802/Awards/BestPapers.shtml).

| Year | Paper |

|:-:|:-|

| 2020 | **[Co-Embedding Network Nodes and Hierarchical Labels with Taxonomy Based Generative Adversarial Networks](https://jiyang3.web.engr.illinois.edu/files/taxogan.pdf)**
Carl Yang (University of Illinois, Urbana Champaign); Jieyu Zhang (University of Illinois, Urbana Champaign); Jiawei Han (University of Illinois, Urbana Champaign) |

| 2019 | **[Deep Multi-attributed Graph Translation with Node-Edge Co-evolution](https://mason.gmu.edu/~lzhao9/materials/papers/ICDM_2019_NEC_DGT-final.pdf)**
Xiaojie Guo (George Mason University); Liang Zhao (George Mason University), Cameron Nowzari (George Mason University); Setareh Rafatirad (George Mason University); Houman Homayoun (George Mason University); Sai Manoj Pudukotai Dinakarrao (George Mason University) |

| 2018 | **[Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms](https://arxiv.org/pdf/1809.05467.pdf)**
Panagiotis Mandros (Max Planck Institute for Informatics); Mario Boley (Max Planck Institute for Informatics); Jilles Vreeken (Max Planck Institute for Informatics) |

| 2017 | **[TensorCast: Forecasting with Context using Coupled Tensors](http://www.cs.cmu.edu/~christos/PUBLICATIONS/icdm17-tensor-cast-CR.pdf)**
Miguel Ramos de Araujo (Carnegie Mellon University); Pedro Manuel Pinto Ribeiro (University of Porto); Christos Faloutsos (Carnegie Mellon University) |

| 2016 | **[KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift]()**
Viktor Losing (Bielefeld University); Barbara Hammer (Bielefeld University); Heiko Wersing (HONDA Research Institute Europe) |

| 2015 | **[Diamond Sampling for Approximate Maximum All-pairs Dot-product (MAD) Search](https://arxiv.org/pdf/1506.03872.pdf)**
Grey Ballard (Sandia National Laboratories); Seshadhri Comandur (University of California, Santa Cruz); Tamara Kolda (Sandia National Laboratories); Ali Pinar (Sandia National Laboratories) |

| 2014 | **[Ternary Matrix Factorization](https://ieeexplore.ieee.org/document/7023357/)**
Sam Maurus (Technische Universität München); Claudia Plant (Technische Universität München) |

| 2013 | **[Reconstructing Individual Mobility from Smart Card Transactions: A Space Alignment Approach](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/icdm13_embed.pdf)**
Nicholas Jing Yuan (Microsoft Research); Yingzi Wang (University of Science and Technology of China); Fuzheng Zhang (University of Science and Technology of China); Xing Xie (Microsoft Research); Guang-Zhong Sun (University of Science and Technology of China) |



## WSDM

| Year | Paper |

|:-:|:-|

| 2020 | **[The Power of Pivoting for Exact Clique Counting](https://arxiv.org/pdf/2001.06784.pdf)**
Shweta Jain (University of California, Santa Cruz); C. Seshadhri (University of California, Santa Cruz) |

| 2019 | **[Slice: Scalable Linear Extreme Classifiers trained on 100 Million Labels for Related Searches](http://manikvarma.org/pubs/jain19.pdf)**
 Himanshu Jain (Indian Institute of Technology Delhi); Venkatesh Balasubramanian (Microsoft AI & Research); Bhanu Chunduri (Microsoft AI & Research); Manik Varma (Microsoft AI & Research) |

| 2018 | **[Index Compression Using Byte-Aligned ANS Coding and Two-Dimensional Contexts](https://dl.acm.org/doi/10.1145/3159652.3159663)**
 Alistair Moffat (The University of Melbourne); Matthias Petri (The University of Melbourne) |

| 2017 | **[Unbiased Learning-to-Rank with Biased Feedback](https://dl.acm.org/doi/10.1145/3018661.3018699)**
 Thorsten Joachims (Cornell University); Adith Swaminathan (Cornell University); Tobias Schnabel (Cornell University)|

| 2016 | **[Beyond Ranking: Optimizing Whole-Page Presentation](http://www-personal.umich.edu/~qmei/pub/wsdm2016-ranking.pdf)**
 Yue Wang (University of Michigan); Dawei Yin (Yahoo Labs); Luo Jie (Snapchat); Pengyuan Wang (Yahoo Labs); Makoto Yamada (Yahoo Labs); Yi Chang (Yahoo Labs); Qiaozhu Mei (University of Michigan)|

| 2015 | **[Inverting a Steady-State](http://theory.stanford.edu/~sergei/papers/wsdm15-cset.pdf)**
 Ravi Kumar (Google); Andrew Tomkins (Google); Sergei Vassilvitskii (Google); Erik Vee (Google) |

| 2014 | **[Scalable Hierarchical Multitask Learning Algorithms for Conversion Optimization in Display Advertising](https://storage.googleapis.com/pub-tools-public-publication-data/pdf/42498.pdf)**
  Amr Ahmed (Google); Abhimanyu Das (Microsoft Research); Alex J. Smola (Carnegie Mellon University) |

| 2013 | **[Optimized Interleaving for Online Retrieval Evaluation](https://www.microsoft.com/en-us/research/wp-content/uploads/2013/02/Radlinski_Optimized_WSDM2013.pdf.pdf)**
 Filip Radlinski (Microsoft); Nick Craswell (Microsoft) |



## RecSys

| Year | Paper |

|:-:|:-|

| 2020 | **[Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations](https://dl.acm.org/doi/pdf/10.1145/3383313.3412236)**
 Hongyan Tang (Tencent PCG); Junning Liu (Tencent PCG); Ming Zhao (Tencent PCG); Xudong Gong (Tencent PCG) |

| 2019 | **[Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches](https://arxiv.org/pdf/1907.06902.pdf)**
  Maurizio Ferrari Dacrema (Politecnico di Milano); Paolo Cremonesi (Politecnico di Milano); Dietmar Jannach (University of Klagenfurt) |

| 2018 | **[Causal Embeddings for Recommendation](https://arxiv.org/pdf/1706.07639.pdf)**
 Stephen Bonner (Criteo AI Labs); Flavian Vasile (Criteo AI Labs) |

| 2017 | **[Modeling the Assimilation-Contrast Effects in Online Product Rating Systems: Debiasing and Recommendations]()**
 Xiaoying Zhang (The Chinese University of Hong Kong); Junzhou Zhao (The Chinese University of Hong Kong); John C.S. Lui (The Chinese University of Hong Kong) |

| 2016 | **[Local Item-Item Models for Top-N Recommendation](https://www-users.cs.umn.edu/~chri2951/recsy368-christakopoulouA.pdf)**
 Evangelia Christakopoulou (University of Minnesota); George Karypis (University of Minnesota) |

| 2015 | **[Context-Aware Event Recommendation in Event-based Social Networks](https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.714.8211&rep=rep1&type=pdf)**
 Augusto Q. Macedo (Federal University of Campina Grande); Leandro B. Marinho (Federal University of Campina Grande); Rodrygo L.T. Santos (Federal University of Campina Grande) |

| 2014 | **[Beyond Clicks: Dwell Time for Personalization](http://www.hongliangjie.com/publications/recsys2014.pdf)**
 Xing Yi (Yahoo Labs); Liangjie Hong (Yahoo Labs); Erheng Zhong (Yahoo Labs); Nathan Nan Liu (Yahoo Labs); Suju Rajan (Yahoo Labs) |

| 2013 | **[A Fast Parallel SGD for Matrix Factorization in Shared Memory Systems](https://www.csie.ntu.edu.tw/~cjlin/papers/libmf/libmf.pdf)**
 Yong Zhuang (National Taiwan University); Wei-Sheng Chin (National Taiwan University); Yu-Chih Juan (National Taiwan University); Chih-Jen Lin (National Taiwan University) |

---



## CVPR

The full list of CVPR best papers is presented on [this website](https://www.thecvf.com/?page_id=413#CVPRBest).

| Year | Paper |

|:-:|:-|

| 2021 | **[GIRAFFE: Representing Scenes As Compositional Generative Neural Feature Fields](https://openaccess.thecvf.com/content/CVPR2021/papers/Niemeyer_GIRAFFE_Representing_Scenes_As_Compositional_Generative_Neural_Feature_Fields_CVPR_2021_paper.pdf)**
Michael Niemeyer (Max Planck Institute for Intelligent Systems); Andreas Geiger (University of Tubingen) |

| 2020 | **[Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild](https://arxiv.org/pdf/1911.11130.pdf)**
Shangzhe Wu (University of Oxford); Christian Rupprecht (University of Oxford); Andrea Vedaldi (Oxford University) |

| 2019 | **[A theory of Fermat Paths for Non-Line-of-Sight Shape Reconstruction](https://imaging.cs.cmu.edu/fermat_paths/assets/cvpr2019.pdf)**
Shumian Xin (Carnegie Mellon University); Sotiris Nousias (University of Toronto); Kiriakos N. Kutulakos (University of Toronto); Aswin C. Sankaranarayanan (Carnegie Mellon University); Srinivasa G. Narasimhan (Carnegie Mellon University); Ioannis Gkioulekas (Carnegie Mellon University) |

| 2018 | **[Taskonomy: Disentangling Task Transfer Learning](https://arxiv.org/pdf/1804.08328.pdf)**
Amir R. Zamir (Stanford University); Alexander Sax (Stanford University); William Shen (Stanford University); Leonidas Guibas (Stanford University); Jitendra Malik (University of California Berkeley); Silvio Savarese (Stanford University) |

| 2017 | 1. **[Densely Connected Convolutional Networks](https://arxiv.org/pdf/1608.06993.pdf)**
Zhuang Liu (Tsinghua University); Gao Huang (Cornell University); Laurens van der Maaten (Facebook AI Research); Kilian Q. Weinberger (Cornell University)
2. **[Learning from Simulated and Unsupervised Images through Adversarial Training](https://arxiv.org/pdf/1612.07828.pdf)**
Ashish Shrivastava (Apple Inc.); Tomas Pfister (Apple Inc.); Oncel Tuzel (Apple Inc.); Josh Susskind (Apple Inc.); Wenda Wang (Apple Inc.); Russ Webb (Apple Inc.) |

| 2016 | **[Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf)**
Kaiming He (Microsoft Research); Xiangyu Zhang (Microsoft Research); Shaoqing Ren (Microsoft Research); Jian Sun (Microsoft Research) |

| 2015 | **[DynamicFusion: Reconstruction and Tracking of Non-rigid Scenes in Real-Time](https://rse-lab.cs.washington.edu/papers/dynamic-fusion-cvpr-2015.pdf)**
Richard A. Newcombe (University of Washington); Dieter Fox (University of Washington); Steven M. Seitz (University of Washington) |

| 2014 | **[What Camera Motion Reveals About Shape with Unknown BRDF](https://cseweb.ucsd.edu/~mkchandraker/pdf/cvpr14_cameramotion.pdf)**
Manmohan Chandraker (NEC Labs America) |

| 2013 | **[Fast, Accurate Detection of 100,000 Object Classes on a Single Machine](https://www.cv-foundation.org/openaccess/content_cvpr_2013/papers/Dean_Fast_Accurate_Detection_2013_CVPR_paper.pdf)**
Thomas Dean (Google); Mark A. Ruzon (Google); Mark Segal (Google); Jonathon Shlens (Google); Sudheendra Vijayanarasimhan (Google); Jay Yagnik (Google) |



## ICCV

The ICCV Best Paper Award is also called the Marr Prize, named after British neuroscientist [David Marr](https://en.wikipedia.org/wiki/David_Marr_(neuroscientist)). The full list of ICCV best papers is presented on [this website](https://www.thecvf.com/?page_id=413#ICCVBest).

| Year | Paper |

|:-:|:-|

| 2019 | **[SinGAN: Learning a Generative Model from a Single Natural Image](https://arxiv.org/pdf/1905.01164.pdf)**
Tamar Rott Shaham (Israel Institute of Technology); Tomer Michaeli (Israel Institute of Technology); Tali Dekel (Google Research) |

| 2017 | **[Mask R-CNN](https://arxiv.org/pdf/1703.06870.pdf)**
 Kaiming He (Facebook AI Research); Georgia Gkioxari (Facebook AI Research); Piotr Dollar (Facebook AI Research); Ross Girshick (Facebook AI Research) |

| 2015 | **[Deep Neural Decision Forests](https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Kontschieder_Deep_Neural_Decision_ICCV_2015_paper.pdf)**
Peter Kontschieder (Microsoft Research); Madalina Fiterau (Carnegie Mellon University); Antonio Criminisi (Microsoft Research); Samuel Rota Bulò (Microsoft Research) |

| 2013 | **[From Large Scale Image Categorization to Entry-Level Categories](https://homes.cs.washington.edu/~yejin/Papers/iccv13_entrylevel.pdf)**
Vicente Ordonez (University of North Carolina at Chapel Hill); Jia Deng (Stanford University); Yejin Choi (Stony Brook University); Alexander Berg (University of North Carolina at Chapel Hill); Tamara Berg (University of North Carolina at Chapel Hill) |



## ECCV

The full list of ECCV best papers is presented on [this website](https://www.thecvf.com/?page_id=413#ECCVBest).

| Year | Paper |

|:-:|:-|

| 2020 | **[RAFT: Recurrent All-Pairs Field Transforms for Optical Flow](https://arxiv.org/pdf/2003.12039.pdf)**
 Zachary Teed (Princeton University); Jia Deng (Princeton University) |

| 2018 | **[Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection from RGB Images](https://arxiv.org/pdf/1902.01275.pdf)**
 Martin Sundermeyer (German Aerospace Center); Zoltan-Csaba Marton (German Aerospace Center); Maximilian Durner (German Aerospace Center); Rudolph Triebel (German Aerospace Center) |

| 2016 | **[Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera](https://www.doc.ic.ac.uk/~ajd/Publications/kim_etal_eccv2016.pdf)**
 Hanme Kim (Imperial College London); Stefan Leutenegger (Imperial College London); Andrew J. Davison (Imperial College London) |

| 2014 | 1. **[Large-Scale Object Classification using Label Relation Graphs](https://www.cs.princeton.edu/~jiadeng/paper/deng2014large.pdf)**
 Jia Deng (University of Michigan); Nan Ding (Google); Yangqing Jia (Google); Andrea Frome (Google); Kevin Murphy (Google); Samy Bengio (Google); Yuan Li (Google); Hartmut Neven (Google); Hartwig Adam (Google) 
2. **[Scene Chronology](http://www.cs.cornell.edu/~snavely/publications/matzen_eccv2014.pdf)**
 Kevin Matzen (Cornell University); Noah Snavely (Cornell University) |

---



## ACL

The full list of ACL best papers is presented on [this website](https://aclweb.org/aclwiki/Best_paper_awards#ACL).

| Year | Paper |

|:-:|:-|

| 2020 | **[Beyond Accuracy: Behavioral Testing of NLP Models with CheckList](https://arxiv.org/pdf/2005.04118.pdf)**
Marco Tulio Ribeiro (Microsoft Research), Tongshuang Wu (University of Washington), Carlos Guestrin (University of Washington), Sameer Singh (University of Washington) |

| 2019 | **[Bridging the Gap between Training and Inference for Neural Machine Translation](https://arxiv.org/pdf/1906.02448.pdf)**
Wen Zhang (University of Chinese Academy of Sciences); Yang Feng (University of Chinese Academy of Sciences); Fandong Meng (WeChat AI); Di You (Worcester Polytechnic Institute); Qun Liu (Huawei Noah’s Ark Lab) |

| 2018 | **[Finding syntax in human encephalography with beam search](https://arxiv.org/pdf/1806.04127.pdf)**
John Hale (Cornell University); Chris Dyer (DeepMind); Adhiguna Kuncoro (University of Oxford); Jonathan R. Brennan (University of Michigan) |

| 2017 | **[Probabilistic Typology: Deep Generative Models of Vowel Inventories](https://arxiv.org/pdf/1705.01684.pdf)**
Ryan Cotterell (Johns Hopkins University); Jason Eisner (Johns Hopkins University) |

| 2016 | **[Finding Non-Arbitrary Form-Meaning Systematicity Using String-Metric Learning for Kernel Regression](https://www.aclweb.org/anthology/P16-1225.pdf)**
E. Darío Gutiérrez (University of California Berkeley); Roger Levy (Massachusetts Institute of Technology); Benjamin K. Bergen (University of California San Diego) |

| 2015 | 1. **[Improving Evaluation of Machine Translation Quality Estimation](https://www.aclweb.org/anthology/P15-1174.pdf)**
Yvette Graham (Trinity College Dublin)
2. **[Learning Dynamic Feature Selection for Fast Sequential Prediction](https://www.aclweb.org/anthology/P15-1015.pdf)**
Emma Strubell (University of Massachusetts Amherst); Luke Vilnis (University of Massachusetts Amherst); Kate Silverstein (University of Massachusetts Amherst); Andrew McCallum (University of Massachusetts Amherst) |

| 2014 | **[Fast and Robust Neural Network Joint Models for Statistical Machine Translation](https://www.aclweb.org/anthology/P14-1129.pdf)**
Jacob Devlin (Raytheon BBN Technologies); Rabih Zbib (Raytheon BBN Technologies); Zhongqiang Huang (Raytheon BBN Technologies); Thomas Lamar (Raytheon BBN Technologies); Richard Schwartz (Raytheon BBN Technologies); John Makhoul (Raytheon BBN Technologies) |

| 2013 | **[Grounded Language Learning from Video Described with Sentences](https://www.aclweb.org/anthology/P13-1006.pdf)**
Haonan Yu (Purdue University); Jeffrey Mark Siskind (Purdue University) |



## EMNLP

The full list of EMNLP best papers is presented on [this website](https://aclweb.org/aclwiki/Best_paper_awards#EMNLP).

| Year | Paper |

|:-:|:-|

| 2020 | **[Digital voicing of Silent Speech](https://arxiv.org/pdf/2010.02960.pdf)**
David Gaddy (University of California, Berkeley); Dan Klein (University of California, Berkeley) |

| 2019 | **[Specializing Word Embeddings (for Parsing) by Information Bottleneck](https://arxiv.org/pdf/1910.00163.pdf)**
 Xiang Lisa Li (Johns Hopkins University); Jason Eisner (Johns Hopkins University) |

| 2018 | **[Linguistically-Informed Self-Attention for Semantic Role Labeling](https://arxiv.org/pdf/1804.08199.pdf)**
 Emma Strubell (University of Massachusetts Amherst); Patrick Verga (University of Massachusetts Amherst); Daniel Andor (Google AI Language); David Weiss (Google AI Language); Andrew McCallum (University of Massachusetts Amherst) |

| 2017 | 1. **[Depression and Self-Harm Risk Assessment in Online Forums](https://arxiv.org/pdf/1709.01848.pdf)**
 Andrew Yates (Max Planck Institute for Informatics); Arman Cohan (Georgetown University); Nazli Goharian (Georgetown University) 
2. **[Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints](https://arxiv.org/pdf/1707.09457.pdf)**
 Jieyu Zhao (University of Virginia); Tianlu Wang (University of Virginia); Mark Yatskar (University of Washington); Vicente Ordonez (University of Virginia); Kai-Wei Chang (University of Virginia) |

| 2016 | 1. **[Global Neural CCG Parsing with Optimality Guarantees](https://arxiv.org/pdf/1607.01432.pdf)**
 Kenton Lee (University of Washington); Mike Lewis (University of Washington); Luke Zettlemoyer (University of Washington) 
2. **[Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning](https://arxiv.org/pdf/1603.07954.pdf)**
 Karthik Narasimhan (Massachusetts Institute of Technology); Adam Yala (Massachusetts Institute of Technology); Regina Barzilay (Massachusetts Institute of Technology) |

| 2015 | 1. **[Broad-coverage CCG Semantic Parsing with AMR](https://www.aclweb.org/anthology/D15-1198.pdf)**
 Yoav Artzi (Cornell University); Kenton Lee (University of Washington); Luke Zettlemoyer (University of Washington) 
2. **[Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems](https://arxiv.org/pdf/1508.01745.pdf)**
 Tsung-Hsien Wen (Cambridge University); Milica Gasic (Cambridge University); Nikola Mrkši´c (Cambridge University); Pei-Hao Su (Cambridge University); David Vandyke (Cambridge University); Steve Young (Cambridge University) |

| 2014 | **[Modeling Biological Processes for Reading Comprehension](https://www.aclweb.org/anthology/D14-1159v2.pdf)**
 Vivek Srikumar (Stanford University); Pei-Chun Chen (Stanford University); Abby Vander Linden (Stanford University); Brittany Harding (Stanford University); Brad Huang (Stanford University); Peter Clark (Stanford University); Christopher D. Manning (Stanford University) |

| 2013 | **[Breaking Out of Local Optima with Count Transforms and Model Recombination: A Study in Grammar Induction](https://www.aclweb.org/anthology/D13-1204.pdf)**
 Valentin Spitkovsky (Stanford University); Hiyan Alshawi (Stanford University); Daniel Jurafsky (Stanford University) |



## NAACL

The full list of NAACL best papers is presented on [this website](https://aclweb.org/aclwiki/Best_paper_awards#NAACL).

| Year | Paper |

|:-:|:-|

| 2019 | **[BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://www.aclweb.org/anthology/N19-1423.pdf)**
 Jacob Devlin (Google AI Language); Ming-Wei Chang (Google AI Language); Kenton Lee (Google AI Language); Kristina Toutanova (Google AI Language) |

| 2018 | **[Deep contextualized word representations](https://www.aclweb.org/anthology/N18-1202.pdf)**
 Matthew E. Peters (Allen Institute for Artificial Intelligence); Mark Neumann (Allen Institute for Artificial Intelligence); Mohit Iyyer (Allen Institute for Artificial Intelligence); Matt Gardner (Allen Institute for Artificial Intelligence); Christopher Clark (University of Washington); Kenton Lee (University of Washington); Luke Zettlemoyer (Allen Institute for Artificial Intelligence) |

| 2016 | 1. **[Feuding Families and Former Friends; Unsupervised Learning for Dynamic Fictional Relationships](https://www.aclweb.org/anthology/N16-1180.pdf)**
 Mohit Iyyer (University of Maryland); Anupam Guha (University of Maryland); Snigdha Chaturvedi (University of Maryland); Jordan Boyd-Graber (University of Colorado); Hal Daumé III (University of Maryland) 
2. **[Learning to Compose Neural Networks for Question Answering](https://www.aclweb.org/anthology/N16-1181.pdf)** Jacob Andreas (University of California, Berkeley); Marcus Rohrbach (University of California, Berkeley); Trevor Darrell (University of California, Berkeley); Dan Klein (University of California, Berkeley) |

| 2015 | **[Unsupervised Morphology Induction Using Word Embeddings](https://www.aclweb.org/anthology/N15-1186.pdf)**
 Radu Soricut (Google); Franz Och (Human Longevity) |



## EACL

| Year | Paper |

|:-:|:-|

| 2021 | 1. **[Error Analysis and the Role of Morphology](https://www.aclweb.org/anthology/2021.eacl-main.162.pdf)**
 Marcel Bollmann (University of Copenhagen); Anders Søgaard (University of Copenhagen) 
 2. **[Is Supervised Syntactic Parsing Beneficial for Language Understanding Tasks? An Empirical Investigation](https://www.aclweb.org/anthology/2021.eacl-main.270v2.pdf)**
Goran Glavaš (University of Mannheim); Ivan Vulić (University of Cambridge) |