HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications

Roberta: A robustly optimized bert pretraining approach

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Language models are few-shot learners

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Retrieval-augmented generation for knowledge-intensive nlp tasks

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The probabilistic relevance framework: Bm25 and beyond

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Bert: Pre-training of deep bidirectional transformers for language understanding

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Knowledge graphs

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A survey on knowledge graphs: Representation, acquisition, and applications

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A statistical interpretation of term specificity and its application in retrieval

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Training a helpful and harmless assistant with reinforcement learning from human feedback

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Survey of hallucination in natural language generation

Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Yejin Bang, Delong Chen, Wenliang Dai, Andrea Madotto, and Pascale Fung. 2022 · 2022

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Mteb: Massive text embedding benchmark

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Niklas Muennighoff, Nouamane Tazi, Loïc Magne, and Nils Reimers. 2022 · 2022

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Learning to retrieve passages without supervision

Ori Ram, Gal Shachaf, Omer Levy, Jonathan Berant, and Amir Globerson. 2022 · 2022

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Legal prompt engineering for multilingual legal judgement prediction

Original

Dietrich Trautmann, Alina Petrova, and Frank Schilder. 2022 · 2022

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Hybrid hierarchical retrieval for open-domain question answering

Manoj Ghuhan Arivazhagan, Lan Liu, Peng Qi, Xinchi Chen, William Yang Wang, and Zhiheng Huang. 2023 · 2023

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Self-rag: Learning to retrieve, generate, and critique through self-reflection

Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2023 · 2023

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Can gpt-3 perform statutory reasoning?

Andrew Blair-Stanek, Nils Holzenberger, and Benjamin Van Durme. 2023 · 2023

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Chatgpt goes to law school

Jonathan H. Choi, Kristin E. Hickman, Amy B. Monahan, and Daniel Benjamin Schwarcz. 2023 · 2023

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Chatlaw: A multi-agent collaborative legal assistant with knowledge graph enhanced mixture-of-experts large language model

Jiaxi Cui, Zongjia Li, Yang Yan, Bohua Chen, and Li Yuan. 2023 · 2023

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Retrieval-augmented generation for large language models: A survey

Original

Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Qianyu Guo, Meng Wang, and Haofen Wang. 2023 · 2023

Cited alongside, same era.

Legalbench: A collaboratively built benchmark for measuring legal reasoning in large language models

Original

Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin M. K. Peters, Brandon Waldon, Daniel N. Rockmore, Diego A. Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, Gregory M. Dickinson, Haggai Porat, Jason Hegland, Jessica Wu, Joe Nudell, Joel Niklaus, John J. Nay, Jonathan H. Choi, Kevin Patrick Tobia, Margaret Hagan, Megan Ma, Michael A. Livermore, Nikon Rasumov-Rahe, Nils Holzenberger, Noam Kolt, Peter Henderson, Sean Rehaag, Sharad Goel, Shangsheng Gao, Spencer Williams, Sunny G. Gandhi, Tomer Zur, Varun J. Iyer, and Zehua Li. 2023 · 2023

Cited alongside, same era.

‘words are flowing out like endless rain into a paper cup’: Chatgpt & law school assessments

Bloomberggpt: A large language model for finance

Original

Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann. 2023 · 2023

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C-pack: Packaged resources to advance general chinese embedding

Original

Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff. 2023 · 2023

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Harnessing the power of llms in practice: A survey on chatgpt and beyond

Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, and Xia Hu. 2023 · 2023

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Judging llm-as-a-judge with mt-bench and chatbot arena

Original

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Haotong Zhang, Joseph Gonzalez, and Ion Stoica. 2023 · 2023

Later among the works it cites.