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https://github.com/Kyrie-Zhao/awesome-foundation-model
Foundation Model for X and X for Foundation Model
https://github.com/Kyrie-Zhao/awesome-foundation-model
List: awesome-foundation-model
Last synced: 3 months ago
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Foundation Model for X and X for Foundation Model
- Host: GitHub
- URL: https://github.com/Kyrie-Zhao/awesome-foundation-model
- Owner: Kyrie-Zhao
- Created: 2023-10-14T03:04:57.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2024-01-10T03:34:59.000Z (10 months ago)
- Last Synced: 2024-05-22T23:05:30.561Z (5 months ago)
- Size: 50.8 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - awesome-foundation-model - Foundation Model for X and X for Foundation Model. (Other Lists / PowerShell Lists)
README
# Awesome Foundation Model  []
This is a list of awesome _**Foundation Model for X and X for Foundation Model**_ related projects & papers.
## Contents
- [Benchmark and Dataset](#benchmark-and-dataset)
- [Open Source Projects](#open-source-projects)
- [Papers](#papers)
- [Multi Modal](#multi-modal)
- [Agent](#agent)
- [Efficient Inference](#efficient-inference)
- [Efficient Training](#efficient-training)
- [Optimization](#optimization)
- [Healthcare](#healthcare)
- [Code Optimization and Compiler](#code-optimization-and-compiler)
- [Data Selection](#data-selection)
- [Prompt Optimization](#prompt-optimization)
- [Others](#others)
## Benchmark and Dataset
- [Embedchain](https://github.com/embedchain/embedchain)
## Open Source Projects
- [ImageBind](https://github.com/facebookresearch/ImageBind)
- [MetaTransformer](https://github.com/invictus717/MetaTransformer)
## Papers
### Multi Modal
- [ImageBind: One embedding space to bind them all](https://openaccess.thecvf.com/content/CVPR2023/papers/Girdhar_ImageBind_One_Embedding_Space_To_Bind_Them_All_CVPR_2023_paper.pdf) by Girdhar, Rohit, et al., CVPR 2023
- [LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action](https://arxiv.org/pdf/2207.04429.pdf) by Shah, Dhruv, Błażej Osiński, and Sergey Levine., PMLR 2023
- [IoT in the Era of Generative AI: Vision and Challenges](https://arxiv.org/pdf/2401.01923) by Wang, Xin, et al., arxiv 2024
### Agent
- [TypeFly: Flying Drones with Large Language Model](https://arxiv.org/pdf/2312.14950) by Chen, Guojun, Xiaojing Yu, and Lin Zhong., arxiv 2023
### Efficient Inference
- [FlexGen: High-throughput Generative Inference of Large Language Models with a Single GPU](https://arxiv.org/pdf/2303.06865) by Sheng, Ying, et al., ICML 2023
- [Tabi: An Efficient Multi-Level Inference System for Large Language Models](https://dl.acm.org/doi/pdf/10.1145/3552326.3587438?casa_token=2Ju1tOw9-OQAAAAA:JiW7lFRbuCbNQp8JxLKq0_Fu5O2HnPKnCtXSBuWYiW0HOJa5AhUEhvaAQVBVoyDN0qAgI2abM73h20A) by Wang, Yiding, et al. EuroSys 2023
- [EFFICIENTLY SCALING TRANSFORMER INFERENCE](https://arxiv.org/pdf/2211.05102) by Pope, Reiner, et al., arxiv 2022
- [SpecInfer: Accelerating Generative LLM Serving with Speculative Inference and Token Tree Verification](https://arxiv.org/pdf/2305.09781) by Miao, Xupeng, et al., arxiv 2023
- [EnergonAI: An Inference System for 10-100 Billion Parameter Transformer Models](https://arxiv.org/pdf/2209.02341) by Du, Jiangsu, et al., arxiv 2022
- [AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving](https://arxiv.org/pdf/2302.11665) by Li, Zhuohan, et al., OSDI 2023
- [STI: Turbocharge NLP Inference at the Edge via Elastic Pipelining](https://dl.acm.org/doi/pdf/10.1145/3575693.3575698) by Guo, Liwei, Wonkyo Choe, and Felix Xiaozhu Lin., ASPLOS 2023
- [DeepSpeed-inference: enabling efficient inference of transformer models at unprecedented scale](https://ieeexplore.ieee.org/iel7/10046045/10045783/10046087.pdf?casa_token=-l-VUdoAL9cAAAAA:Zt9pbjDGwTuqtX-RSm6Np74l4mUYuPp6ls_xH-wdaIPQig-A6UduT7xDn8Wcsv05W1imTH08mhU) by Aminabadi, Reza Yazdani, et al., SC 2022
- [PETALS: Collaborative Inference and Fine-tuning of Large Models](https://arxiv.org/pdf/2209.01188) by Borzunov, Alexander, et al., arxiv 2022
- [Fairness in Serving Large Language Models](https://arxiv.org/pdf/2401.00588) by Sheng, Ying, et al., arxiv 2023
- [Fast Distributed Inference Serving for Large Language Models](https://arxiv.org/pdf/2305.05920) by Wu, Bingyang, et al., arxiv 2023
- [DISTRIBUTED INFERENCE AND FINE-TUNING OF LARGE LANGUAGE MODELS OVER THE INTERNET](https://openreview.net/pdf?id=HLQyRgRnoXo) under review
- [Orca: A Distributed Serving System for {Transformer-Based} Generative Models](https://www.usenix.org/system/files/osdi22-yu.pdf) by Yu, Gyeong-In, et al., OSDI 2022
### Efficient Training
- [TopoopT: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training Jobs](https://www.usenix.org/system/files/nsdi23-wang-weiyang.pdf) by Wang, Weiyang, et al., NSDI 2023
- [Breadth-First Pipeline Parallelism](https://arxiv.org/pdf/2211.05953) by Lamy-Poirier, Joel., MLSys 2023
- [On Optimizing the Communication of Model Parallelism](https://arxiv.org/pdf/2211.05322.pdf) by Zhuang, Yonghao, et al., MLSys 2023
- [Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism](https://arxiv.org/pdf/2211.13878) by Miao, Xupeng, et al., arxiv 2022
- [Overlap Communication with Dependent Computation via Decomposition in Large Deep Learning Models](https://dl.acm.org/doi/pdf/10.1145/3567955.3567959) by Wang, Shibo, et al., ASPLOS 2023
### Optimization
- [Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens](https://arxiv.org/pdf/2305.04241) by Zeng, Zhanpeng, et al., arxiv 2023
### Healthcare
- [Multimodal LLMs for health grounded in individual-specific data](https://arxiv.org/pdf/2307.09018) by Belyaeva, Anastasiya, et al., arxiv 2023
- [Path to Medical AGI: Unify Domain-specific Medical LLMs with the Lowest Cost](https://arxiv.org/pdf/2306.10765) by Zhou, Juexiao, Xiuying Chen, and Xin Gao., arxiv 2023
- [Decoding speech perception from non-invasive brain recordings](https://www.nature.com/articles/s42256-023-00714-5) by Défossez, Alexandre, et al., Nature Machine Intelligence 2023
- [Large language models improve Alzheimer’s disease diagnosis using multi-modality data](https://arxiv.org/pdf/2305.19280) by Feng, Yingjie, et al., arxiv 2023
- [Neuro-GPT: Developing A Foundation Model for EEG](https://arxiv.org/pdf/2311.03764) by Cui, Wenhui, et al., arxiv 2023
- [From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models](https://arxiv.org/pdf/2311.13063) by Englhardt, Zachary, et al., arxiv 2023
- [Conversational Health Agents: A Personalized LLM-Powered Agent Framework](https://arxiv.org/pdf/2310.02374.pdf) by Abbasian, Mahyar, et al., arxiv 2023
- [UbiPhysio: Support Daily Functioning, Fitness, and Rehabilitation with Action Understanding and Feedback in Natural Language](https://arxiv.org/pdf/2308.10526) by Wang, Chongyang, et al., arxiv 2023
- [GG-LLM: Geometrically Grounding Large Language Models for Zero-shot Human Activity Forecasting in Human-Aware Task Planning](https://arxiv.org/pdf/2310.20034) by Graule, Moritz A., and Volkan Isler., arxiv 2023
### Code Optimization and Compiler
- [Can Large Language Models Reason about Program Invariants?](https://openreview.net/pdf?id=mXv2aVqUGG) by Pei, Kexin, et al., ICML 2023
- [The Hitchhiker's Guide to Program Analysis: A Journey with Large Language Models](https://arxiv.org/pdf/2308.00245) by Li, Haonan, et al., arxiv 2023
- [Clover: Closed-Loop Verifiable Code Generation](https://arxiv.org/pdf/2310.17807) by Sun, Chuyue, et al., arxiv 2023
- [Formalizing Natural Language Intent into Program Specifications via Large Language Models](https://arxiv.org/pdf/2310.01831) by Endres, Madeline, et al., arxiv 2023
- [Ranking LLM-Generated Loop Invariants for Program Verification](https://arxiv.org/pdf/2310.09342) by Chakraborty, Saikat, et al., arxiv 2023
- [Large language models for compiler optimization](https://arxiv.org/pdf/2309.07062) by Cummins, Chris, et al., arxiv 2023
- [Magicoder: Source Code Is All You Need](https://arxiv.org/pdf/2312.02120.pdf) by Yuxiang Wei1 Zhe Wang2 Jiawei Liu1 Yifeng Ding1 Lingming Zhang, arxiv 2023
### Data Selection
- [Towards Free Data Selection with General-Purpose Models](https://arxiv.org/pdf/2309.17342) by Xie, Yichen, et al., arxiv 2023
### Prompt Optimization
- [Prompt-aligned Gradient for Prompt Tuning](http://openaccess.thecvf.com/content/ICCV2023/papers/Zhu_Prompt-aligned_Gradient_for_Prompt_Tuning_ICCV_2023_paper.pdf) by Zhu, Beier, et al., CVPR 2023
- [MaPLe: Multi-modal Prompt Learning](https://openaccess.thecvf.com/content/CVPR2023/papers/Khattak_MaPLe_Multi-Modal_Prompt_Learning_CVPR_2023_paper.pdf) by Khattak, Muhammad Uzair, et al., CVPR 2023
### Others
- [ClimaX: A foundation model for weather and climate](https://arxiv.org/pdf/2301.10343) by Nguyen, Tung, et al., arxiv 2023