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https://github.com/ccclyu/awesome-deeplogic

A collection of papers of neural-symbolic AI (mainly focus on NLP applications)
https://github.com/ccclyu/awesome-deeplogic

List: awesome-deeplogic

deep-logic-model first-order-logic neuro-symbolic-learning paper-list psl reasoning

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A collection of papers of neural-symbolic AI (mainly focus on NLP applications)

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# [Awesome deep logic](https://github.com/ccclyu/awesome-deeplogic) [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)



Must-Read Papers or Resources on how to integrate symbolic logic into deep neural nets.



### Survey and Open Challenges



1. **From Machine Learning to Machine Reasoning** *Leon Bottou* Arxiv 2011 [[pdf](https://arxiv.org/abs/1102.1808)]



1. **From Statistical Relational to Neuro-Symbolic Artificial Intelligence** *Luc De Raedt , Sebastijan Dumanˇci ́c , Robin Manhaeve and Giuseppe Marra* Arxiv 2020 [[pdf](https://arxiv.org/pdf/2003.08316.pdf)]



1. **Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective** *Luis C. Lamb et,al.* Arxiv 2020 [[pdf](https://arxiv.org/pdf/2003.00330.pdf)]



1. **Relational inductive biases, deep learning and graph networks**  *Peter W. Battaglia et,al.* Arxiv 2018 [[pdf](https://arxiv.org/pdf/1806.01261.pdf)]



### Tutorials



1. **Neuro-Symbolic Methods For Language And Vision** AAAI 2022 [[link](https://sites.google.com/allenai.org/nsmlv-tutorial-aaai-22)]



### Logic as Knowledge Regularization

1. **Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic** *Xufeng Zhao, Mengdi Li, Wenhao Lu, Cornelius Weber, Jae Hee Lee, Kun Chu, Stefan Wermter.* COLING 2024 [[pdf](https://arxiv.org/abs/2309.13339)] [[code](https://github.com/xf-zhao/LoT)]



1. **Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference.** *Yichao Zhou, Yu Yan, Rujun Han, J. Harry Caufield,Kai-Wei Chang, Yizhou Sun, Peipei Ping and Wei Wang.* AAAI 2021 [[pdf](https://arxiv.org/pdf/2012.08790.pdf)] [[code](https://github.com/yuyanislearning/CTRL-PG)]



1. **Integrating Deep Learning with Logic Fusion for Information Extraction.** *Wenya Wang, Sinno Jialin Pan*. AAAI 2020 [[pdf](https://arxiv.org/pdf/1912.03041.pdf)] [[code](https://github.com/happywwy/RuleFusionForIE)] 



1. **Logic-guided Data Augmentation and Reguralization for Consistent Question Answering.** *[Akari Asai](https://akariasai.github.io/), Hannaneh Hajishirzi*. ACL 2020 [[pdf](https://arxiv.org/pdf/2004.10157.pdf)] [[code](https://github.com/AkariAsai/logic_guided_qa)]



1. **Structured Tuning for Semantic Role Labeling.** *[Tao Li](https://www.cs.utah.edu/~tli/), Parth Anand Jawale, Martha Palmer, Vivek Srikumar* ACL 2020 [[pdf](https://arxiv.org/pdf/2005.00496.pdf)] [[code](https://github.com/utahnlp/structured_tuning_srl)]



1. **Leveraging Declarative Knowledge in Text and First-Order Logic for Fine-Grained Propaganda Detection.** *Ruize Wang, Duyu Tang, et,al* EMNLP 2020 [[pdf](https://arxiv.org/pdf/2004.14201.pdf)]



1. **Joint Constrained Learning for Event-Event Relation Extraction** *Haoyu Wang, Muhao Chen, Hongming Zhang, Dan Roth* EMNLP 2020 [[pdf](https://arxiv.org/pdf/2010.06727.pdf)]



1. **A Logic-Driven Framework for Consistency of Neural Models.** *Tao Li, Vivek Gupta, Maitrey Mehta, Vivek Srikumar* EMNLP-IJCNLP 2019 [[pdf](https://www.aclweb.org/anthology/D19-1405/)] [[code](https://github.com/utahnlp/consistency)]



1. **Adversarially regularising neural NLI models to integrate logical background knowledge.** *Pasquale Minervini, Sebastian Riedel*. CoNLL 2018 [[pdf](https://www.aclweb.org/anthology/K18-1007.pdf)] [[code](https://github.com/uclnlp/adversarial-nli)]



1. **Lifted Rule Injection for Relation Embeddings.** *Thomas Demeester, Tim Rocktäschel, Sebastian Riedel* EMNLP 2016 [[pdf](https://www.aclweb.org/anthology/D16-1146.pdf)] 



### Logic as Weak Supervision



1. **Neuro-symbolic Natural Logic with Introspective Revision for Natural Language Inference** *Yufei Feng, Xiaoyu Yang, Xiaodan Zhu, Michael Greenspan* TACL 2022 [[pdf](https://arxiv.org/pdf/2203.04857.pdf)]



1. **LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking** *Hang Jiang et,al* ACL 2021 [[pdf](https://aclanthology.org/2021.acl-long.64.pdf)]  



1. **Weakly Supervised Named Entity Tagging with Learnable Logical Rules.**  *Jiacheng Li, Haibo Ding, Jingbo Shang, Julian McAuley, Zhe Feng* ACL-IJCNLP 2021 [[pdf](https://aclanthology.org/2021.acl-long.352.pdf)] [[code](https://github.com/JiachengLi1995/TALLOR)] 



### Incorporate Logic into NN Module



1. **Learning Language Representations with Logical Inductive Bias.** *Jianshu Chen* ICLR 2023 [pdf](https://openreview.net/pdf?id=rGeZuBRahju)]



1. **Modeling Content and Context with Deep Relational Learning** *Maria Leonor Pacheco and Dan Goldwasser* TACL 2021 [[pdf]](https://www.aclweb.org/anthology/2021.tacl-1.7.pdf) [[code]](https://gitlab.com/purdueNlp/DRaiL/)



1. **Logical Neural Networks** *Ryan Riegel et,al (IBM Research)* Arxiv 2020 [[pdf](https://arxiv.org/pdf/2006.13155.pdf)]



### Explainability and Understanding



1. **LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models**, *Mihir Parmar et,al* ACL 2024  [[pdf](https://aclanthology.org/2024.acl-long.739.pdf)]



1. **Transformers Implement First-Order Logic with Majority Quantifiers** *William Merrill, Ashish Sabharwal* Arxiv 2022 [[pdf](https://arxiv.org/abs/2210.02671)]



1. **What Can Neural Networks Reson About?**  *Keyulu Xu, Jingling Li et,al* ICLR 2020 [[pdf](https://arxiv.org/pdf/1905.13211.pdf)] [[code](https://github.com/NNReasoning/What-Can-Neural-Networks-Reason-About)]



1. **Relational Reasoning and Generalization using Non-symbolic Neural Networks** Arxiv 2020 [[pdf](https://arxiv.org/pdf/2006.07968.pdf)]



### Related Application



1. **Complex Query Answering With Neural Link Predictors** *Erik Arakelyan, Daniel Daza, Pasquale Minervini & Michael Cochez* ICLR 2021 [[pdf](https://openreview.net/pdf?id=Mos9F9kDwkz)] [[code](https://github.com/uclnlp/cqd)]



1. **Faithfully Explainable Recommendation via Neural Logic Reasoning** *Yaxin Zhu, Yikun Xian, Zuohui Fu, Gerard de Melo, Yongfeng Zhang* NAACL [[pdf](https://www.aclweb.org/anthology/2021.naacl-main.245.pdf)] [[code](https://github.com/orcax/LOGER)]



1. **Correlating neural and symbolic representations of language.** *Grzegorz Chrupała, Afra Alishahi.* ACL 2019 [[pdf](https://www.aclweb.org/anthology/P19-1283.pdf)][[code](https://github.com/gchrupala/ursa)]



1. **Representing Meaning with a Combination of Logical and Distributional Models.** *I. Beltagy, Stephen Roller, Pengxiang Cheng, Katrin Erk, Raymond J. Mooney.* Computational Linguistics 2016 [[pdf](https://www.aclweb.org/anthology/J16-4007.pdf)] [[code](https://github.com/ibeltagy/rrr)]