Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge

Some Simple Effective Approximations to the 2-Poisson Model for Probabilistic Weighted Retrieval. In Proceedings of the 17th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval . 232–241

Stephen E. Robertson and Steve Walker. 1994 · 1994

Earlier work this paper cites.

The Probabilistic Relevance Framework: BM25 and Beyond

Stephen E. Robertson and Hugo Zaragoza. 2009 · 2009

Earlier work this paper cites.

Bloom’s taxonomy of cognitive learning objectives

Nancy E Adams. 2015 · 2015

Earlier work this paper cites.

Synthetic QA Corpora Generation with Roundtrip Consistency. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019 . 6168–6173

Chris Alberti, Daniel Andor, Emily Pitler, Jacob Devlin, and Michael Collins. 2019 · 2019

Earlier work this paper cites.

Unsupervised Question Answering by Cloze Translation. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL (2019) . 4896–4910

Patrick S. H. Lewis, Ludovic Denoyer, and Sebastian Riedel. 2019 · 2019

Earlier work this paper cites.

Better Highlighting: Creating Sub-Sentence Summary Highlights. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP (2020) . 6282–6300

Sangwoo Cho, Kaiqiang Song, Chen Li, Dong Yu, Hassan Foroosh, and Fei Liu. 2020 · 2020

Earlier work this paper cites.

Dense Passage Retrieval for Open-Domain Question Answering. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP (2020) . 6769–6781

Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick S. H. Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020

Earlier work this paper cites.

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS (2020)

Patrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020

Earlier work this paper cites.

REL: An Entity Linker Standing on the Shoulders of Giants. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’20) . 2197–2200

Johannes M van Hulst, Faegheh Hasibi, Koen Dercksen, Krisztian Balog, and Arjen P de Vries. 2020 · 2020

Earlier work this paper cites.

Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP (2021) . 4472–4485

Anthony Chen, Pallavi Gudipati, Shayne Longpre, Xiao Ling, and Sameer Singh. 2021 · 2021

Earlier work this paper cites.

Autoregressive Entity Retrieval. In 9th International Conference on Learning Representations, ICLR (2021)

Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2021 · 2021

Earlier work this paper cites.

PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them

Patrick S. H. Lewis, Yuxiang Wu, Linqing Liu, Pasquale Minervini, Heinrich Küttler, Aleksandra Piktus, Pontus Stenetorp, and Sebastian Riedel. 2021 · 2021

Earlier work this paper cites.

Pretrained Transformers for Text Ranking: BERT and Beyond

Jimmy Lin, Rodrigo Frassetto Nogueira, and Andrew Yates. 2021 · 2021

Earlier work this paper cites.

Simple Entity-Centric Questions Challenge Dense Retrievers. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021 . 6138–6148

Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, and Danqi Chen. 2021 · 2021

Earlier work this paper cites.

Retrieval Augmentation Reduces Hallucination in Conversation. In Findings of the Association for Computational Linguistics: EMNLP (2021) . 3784–3803

Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston. 2021 · 2021

Earlier work this paper cites.

BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models. In Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, NeurIPS Datasets and Benchmarks 2021

Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021

Earlier work this paper cites.

Entity-Aware Transformers for Entity Search. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22) . 1455–1465

Emma J Gerritse, Faegheh Hasibi, and Arjen P de Vries. 2022 · 2022

Earlier work this paper cites.

Unsupervised Dense Information Retrieval with Contrastive Learning

Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022

Earlier work this paper cites.

Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS (2022)

Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, and Colin Raffel. 2022 · 2022

Earlier work this paper cites.

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS (2022)

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022 · 2022

Earlier work this paper cites.

BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), ACL (2022) . 1–9

Elad Ben Zaken, Yoav Goldberg, and Shauli Ravfogel. 2022 · 2022

Cited alongside, same era.

Retrieval-based Language Models and Applications. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, ACL 2023 . 41–46

Akari Asai, Sewon Min, Zexuan Zhong, and Danqi Chen. 2023 · 2023

Cited alongside, same era.

A Test Collection of Synthetic Documents for Training Rankers: ChatGPT vs. Human Experts. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM (2023) . 5311–5315

Arian Askari, Mohammad Aliannejadi, Evangelos Kanoulas, and Suzan Verberne. 2023a · 2023

Cited alongside, same era.

Expand, Highlight, Generate: RL-driven Document Generation for Passage Reranking. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP (2023) . 10087–10099

Zephyr: Direct Distillation of LM Alignment

Original

Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, and Thomas Wolf. 2023 · 2023

Later among the works it cites.

An Empirical Comparison of LM-based Question and Answer Generation Methods. In Findings of the Association for Computational Linguistics: ACL 2023 . 14262–14272

Asahi Ushio, Fernando Alva-Manchego, and Jose Camacho-Collados. 2023 · 2023

Later among the works it cites.

Generate then Retrieve: Conversational Response Retrieval Using LLMs as Answer and Query Generators

Original

Zahra Abbasiantaeb and Mohammad Aliannejadi. 2024 · 2024

Closest in time.

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection. In The Twelfth International Conference on Learning Representations, ICLR (2024)

Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2024a · 2024

Closest in time.