Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models

Passage re-ranking with BERT

Original

Rodrigo Nogueira and Kyunghyun Cho. 2020 · 1901

Earlier work this paper cites.

Constructing A multi-hop QA dataset for comprehensive evaluation of reasoning steps

Original

Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, and Akiko Aizawa. 2020 · 2011

Earlier work this paper cites.

TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension

Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017

Earlier work this paper cites.

R3: Reinforced ranker-reader for open-domain question answering

Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerry Tesauro, Bowen Zhou, and Jing Jiang. 2018 · 2018

Earlier work this paper cites.

HotpotQA: A dataset for diverse, explainable multi-hop question answering

Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018a · 2018

Earlier work this paper cites.

HotpotQA: A dataset for diverse, explainable multi-hop question answering

Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018b · 2018

Earlier work this paper cites.

Retrieval-Augmented Generation for knowledge-intensive NLP tasks

Patrick 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.

MAUVE: Measuring the gap between neural text and human text using divergence frontiers

Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, and Zaid Harchaoui. 2021 · 2021

Earlier work this paper cites.

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Original

Omar Khattab, Keshav Santhanam, Xiang Lisa Li, David Hall, Percy Liang, Christopher Potts, and Matei Zaharia. 2022 · 2022

Earlier work this paper cites.

Sparse upcycling: Training mixture-of-experts from dense checkpoints

Original

Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, and Neil Houlsby. 2022 · 2022

Earlier work this paper cites.

QUARK: Controllable text generation with reinforced unlearning

Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, and Yejin Choi. 2022 · 2022

Earlier work this paper cites.

When not to trust language models: Investigating effectiveness of parametric and non-parametric memories

Original

Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Daniel Khashabi, and Hannaneh Hajishirzi. 2022 · 2022

Earlier work this paper cites.

Training language models to follow instructions with human feedback

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Gray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022

Earlier work this paper cites.

ASQA: Factoid questions meet long-form answers

Ivan Stelmakh, Yi Luan, Bhuwan Dhingra, and Ming-Wei Chang. 2022 · 2022

Earlier work this paper cites.

MuSiQue: Multihop questions via single-hop question composition

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2022 · 2022

Earlier work this paper cites.

Retrieval-based language models and applications

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

Cited alongside, same era.

Open LLM leaderboard

Edward Beeching, Clémentine Fourrier, Nathan Habib, Sheon Han, Nathan Lambert, Nazneen Rajani, Omar Sanseviero, Lewis Tunstall, and Thomas Wolf. 2023 · 2023

Cited alongside, same era.

Qlora: Efficient finetuning of quantized llms

Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2023 · 2023

Cited alongside, same era.

AlpacaFarm: A simulation framework for methods that learn from human feedback

Original

Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023

Cited alongside, same era.

Enabling large language models to generate text with citations

Tianyu Gao, Howard Yen, Jiatong Yu, and Danqi Chen. 2023a · 2023

Cited alongside, same era.

Llama 2: Open foundation and fine-tuned chat models

Original

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023

Later among the works it cites.

Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2023b · 2023

Later among the works it cites.

Learning to filter context for retrieval-augmented generation

Original

Zhiruo Wang, Jun Araki, Zhengbao Jiang, Md Rizwan Parvez, and Graham Neubig. 2023 · 2023

Later among the works it cites.

RECOMP: Improving retrieval-augmented lms with compression and selective augmentation

Original

Fangyuan Xu, Weijia Shi, and Eunsol Choi. 2023 · 2023

Later among the works it cites.

ReAct: Synergizing reasoning and acting in language models