Awesome RAG

Key papers

• Efficient Memory Management For Large Language Model Serving With Pagedattention (2023)
  Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, et al.
  46.56
• Self-rag: Learning To Retrieve, Generate, And Critique Through Self-reflection (2023)
  Akari Asai, Zeqiu Wu, Yizhong Wang, et al.
  33.82
• Prefix-tuning: Optimizing Continuous Prompts For Generation (2021)
  Xiang Lisa Li, Percy Liang
  32.38
• Adaptive-rag: Learning To Adapt Retrieval-augmented Large Language Models Through Question Complexity (2024)
  Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.
  29.58
• Scaling Synthetic Data Creation With 1,000,000,000 Personas (2024)
  Tao Ge, Xin Chan, Xiaoyang Wang, et al.
  29.19
• Multihop-rag: Benchmarking Retrieval-augmented Generation For Multi-hop Queries (2024)
  Yixuan Tang, Yi Yang
  27.60
• Duoattention: Efficient Long-context LLM Inference With Retrieval And Streaming Heads (2024)
  Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.
  27.44
• Flashrag: A Modular Toolkit For Efficient Retrieval-augmented Generation Research (2024)
  Jiajie Jin, Yutao Zhu, Guanting Dong, et al.
  26.95
• Saullm-7b: A Pioneering Large Language Model For Law (2024)
  Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.
  26.00
• Scaling Retrieval-based Language Models With A Trillion-token Datastore (2024)
  Rulin Shao, Jacqueline He, Akari Asai, et al.
  25.71
• Freshllms: Refreshing Large Language Models With Search Engine Augmentation (2023)
  Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.
  25.58
• Mindmap: Knowledge Graph Prompting Sparks Graph Of Thoughts In Large Language Models (2023)
  Yilin Wen, Zifeng Wang, Jimeng Sun
  25.51
• Cacheblend: Fast Large Language Model Serving For RAG With Cached Knowledge Fusion (2024)
  Jiayi Yao, Hanchen Li, Yuhan Liu, et al.
  25.46
• Ragas: Automated Evaluation Of Retrieval Augmented Generation (2023)
  Shahul Es, Jithin James, Luis Espinosa-Anke, et al.
  24.85
• Controlllm: Augment Language Models With Tools By Searching On Graphs (2023)
  Zhaoyang Liu, Zeqiang Lai, Zhangwei Gao, et al.
  24.66
• Layoutllm: Layout Instruction Tuning With Large Language Models For Document Understanding (2024)
  Chuwei Luo, Yufan Shen, Zhaoqing Zhu, et al.
  24.66
• Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! (2023)
  Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.
  24.31
• A Systematic Survey Of Prompt Engineering In Large Language Models: Techniques And Applications (2024)
  Pranab Sahoo, Ayush Kumar Singh, Sriparna Saha, et al.
  24.27
• Federatedscope-llm: A Comprehensive Package For Fine-tuning Large Language Models In Federated Learning (2023)
  Weirui Kuang, Bingchen Qian, Zitao Li, et al.
  24.26
• Tell Your Model Where To Attend: Post-hoc Attention Steering For Llms (2023)
  Qingru Zhang, Chandan Singh, Liyuan Liu, et al.
  24.26
• Patchscopes: A Unifying Framework For Inspecting Hidden Representations Of Language Models (2024)
  Asma Ghandeharioun, Avi Caciularu, Adam Pearce, et al.
  23.87
• Disc-lawllm: Fine-tuning Large Language Models For Intelligent Legal Services (2023)
  Shengbin Yue, Wei Chen, Siyuan Wang, et al.
  23.76
• Optimize Weight Rounding Via Signed Gradient Descent For The Quantization Of Llms (2023)
  Wenhua Cheng, Weiwei Zhang, Haihao Shen, et al.
  23.56
• Tool Learning With Large Language Models: A Survey (2024)
  Changle Qu, Sunhao Dai, Xiaochi Wei, et al.
  23.52
• Graph Chain-of-thought: Augmenting Large Language Models By Reasoning On Graphs (2024)
  Bowen Jin, Chulin Xie, Jiawei Zhang, et al.
  23.21
• Expel: LLM Agents Are Experiential Learners (2023)
  Andrew Zhao, Daniel Huang, Quentin Xu, et al.
  23.10
• Fact, Fetch, And Reason: A Unified Evaluation Of Retrieval-augmented Generation (2024)
  Satyapriya Krishna, Kalpesh Krishna, Anhad Mohananey, et al.
  22.96
• Shepherd: A Critic For Language Model Generation (2023)
  Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al.
  22.89
• Visrag: Vision-based Retrieval-augmented Generation On Multi-modality Documents (2024)
  Shi Yu, Chaoyue Tang, Bokai Xu, et al.
  22.87
• Reasoning On Graphs: Faithful And Interpretable Large Language Model Reasoning (2023)
  Linhao Luo, Yuan-Fang Li, Gholamreza Haffari, et al.
  22.59
• Does Fine-tuning Llms On New Knowledge Encourage Hallucinations? (2024)
  Zorik Gekhman, Gal Yona, Roee Aharoni, et al.
  22.36
• Memorag: Boosting Long Context Processing With Global Memory-enhanced Retrieval Augmentation (2024)
  Hongjin Qian, Zheng Liu, Peitian Zhang, et al.
  22.21
• Ragtruth: A Hallucination Corpus For Developing Trustworthy Retrieval-augmented Language Models (2024)
  Cheng Niu, Yuanhao Wu, Juno Zhu, et al.
  22.10
• Structrag: Boosting Knowledge Intensive Reasoning Of Llms Via Inference-time Hybrid Information Structurization (2024)
  Zhuoqun Li, Xuanang Chen, Haiyang Yu, et al.
  22.07
• AST-T5: Structure-aware Pretraining For Code Generation And Understanding (2024)
  Linyuan Gong, Mostafa Elhoushi, Alvin Cheung
  21.95
• A Survey On RAG Meeting Llms: Towards Retrieval-augmented Large Language Models (2024)
  Wenqi Fan, Yujuan Ding, Liangbo Ning, et al.
  21.90
• Rankrag: Unifying Context Ranking With Retrieval-augmented Generation In Llms (2024)
  Yue Yu, Wei Ping, Zihan Liu, et al.
  21.80
• From RAG To Memory: Non-parametric Continual Learning For Large Language Models (2025)
  Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi, et al.
  21.27
• Fingpt: Large Generative Models For A Small Language (2023)
  Risto Luukkonen, Ville Komulainen, Jouni Luoma, et al.
  21.27
• RLEF: Grounding Code Llms In Execution Feedback With Reinforcement Learning (2024)
  Jonas Gehring, Kunhao Zheng, Jade Copet, et al.
  21.18
• A Simple And Effective \(L_2\) Norm-based Strategy For KV Cache Compression (2024)
  Alessio Devoto, Yu Zhao, Simone Scardapane, et al.
  20.70
• The Good And The Bad: Exploring Privacy Issues In Retrieval-augmented Generation (RAG) (2024)
  Shenglai Zeng, Jiankun Zhang, Pengfei He, et al.
  20.64
• Understand What LLM Needs: Dual Preference Alignment For Retrieval-augmented Generation (2024)
  Guanting Dong, Yutao Zhu, Chenghao Zhang, et al.
  20.23
• Disc-finllm: A Chinese Financial Large Language Model Based On Multiple Experts Fine-tuning (2023)
  Wei Chen, Qiushi Wang, Zefei Long, et al.
  20.11
• Jatmo: Prompt Injection Defense By Task-specific Finetuning (2023)
  Julien Piet, Maha Alrashed, Chawin Sitawarin, et al.
  20.06
• Benchmarking Uncertainty Quantification Methods For Large Language Models With Lm-polygraph (2024)
  Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, et al.
  20.04
• Can Large Language Models Understand Real-world Complex Instructions? (2023)
  Qianyu He, Jie Zeng, Wenhao Huang, et al.
  19.91
• Continual Pre-training For Cross-lingual LLM Adaptation: Enhancing Japanese Language Capabilities (2024)
  Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.
  19.81
• Fact-checking The Output Of Large Language Models Via Token-level Uncertainty Quantification (2024)
  Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.
  19.78
• Chain-of-note: Enhancing Robustness In Retrieval-augmented Language Models (2023)
  Wenhao Yu, Hongming Zhang, Xiaoman Pan, et al.
  19.67
• Clasheval: Quantifying The Tug-of-war Between An Llm's Internal Prior And External Evidence (2024)
  Kevin Wu, Eric Wu, James Zou
  19.62
• Stacking Your Transformers: A Closer Look At Model Growth For Efficient LLM Pre-training (2024)
  Wenyu Du, Tongxu Luo, Zihan Qiu, et al.
  19.56
• Omnieval: An Omnidirectional And Automatic RAG Evaluation Benchmark In Financial Domain (2024)
  Shuting Wang, Jiejun Tan, Zhicheng Dou, et al.
  19.52
• Magicpig: LSH Sampling For Efficient LLM Generation (2024)
  Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.
  19.39
• Faitheval: Can Your Language Model Stay Faithful To Context, Even If "the Moon Is Made Of Marshmallows" (2024)
  Yifei Ming, Senthil Purushwalkam, Shrey Pandit, et al.
  19.34
• Pearl: Personalizing Large Language Model Writing Assistants With Generation-calibrated Retrievers (2023)
  Sheshera Mysore, Zhuoran Lu, Mengting Wan, et al.
  19.23
• Assessing The Brittleness Of Safety Alignment Via Pruning And Low-rank Modifications (2024)
  Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.
  19.00
• From Words To Watts: Benchmarking The Energy Costs Of Large Language Model Inference (2023)
  Siddharth Samsi, Dan Zhao, Joseph McDonald, et al.
  18.71
• DDK: Distilling Domain Knowledge For Efficient Large Language Models (2024)
  Jiaheng Liu, Chenchen Zhang, Jinyang Guo, et al.
  18.67
• Repairagent: An Autonomous, Llm-based Agent For Program Repair (2024)
  Islem Bouzenia, Premkumar Devanbu, Michael Pradel
  18.60