CUB: Benchmarking Context Utilisation Techniques for Language Models

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

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

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Know what you don‘t know: Unanswerable questions for SQuAD

Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018

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PubMedQA: A dataset for biomedical research question answering

Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu. 2019 · 2019

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Natural questions: A benchmark for question answering research

Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019

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Language models as knowledge bases?

Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019

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Language models are unsupervised multitask learners

Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019

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Entity-based knowledge conflicts in question answering

Shayne Longpre, Kartik Perisetla, Anthony Chen, Nikhil Ramesh, Chris DuBois, and Sameer Singh. 2021 · 2021

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KILT: a benchmark for knowledge intensive language tasks

Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, Vassilis Plachouras, Tim Rocktäschel, and Sebastian Riedel. 2021 · 2021

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Retrieval augmentation reduces hallucination in conversation

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

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Lora: Low-rank adaptation of large language models

Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al. 2022 · 2022

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TempoWiC: An evaluation benchmark for detecting meaning shift in social media

Daniel Loureiro, Aminette D’Souza, Areej Nasser Muhajab, Isabella A. White, Gabriel Wong, Luis Espinosa-Anke, Leonardo Neves, Francesco Barbieri, and Jose Camacho-Collados. 2022 · 2022

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Locating and editing factual associations in GPT

Original

Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022

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Pythia: A suite for analyzing large language models across training and scaling

Stella Biderman, Hailey Schoelkopf, Quentin Gregory Anthony, Herbie Bradley, Kyle O’Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, USVSN Sai Prashanth, Edward Raff, et al. 2023 · 2023

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Dissecting recall of factual associations in auto-regressive language models

Mor Geva, Jasmijn Bastings, Katja Filippova, and Amir Globerson. 2023 · 2023

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The effect of scaling, retrieval augmentation and form on the factual consistency of language models

Lovisa Hagström, Denitsa Saynova, Tobias Norlund, Moa Johansson, and Richard Johansson. 2023 · 2023

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Large language models with controllable working memory

Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix Yu, and Sanjiv Kumar. 2023 · 2023

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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing

Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023 · 2023

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Self-refine: Iterative refinement with self-feedback

Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, and Peter Clark. 2023 · 2023

Cited alongside, same era.

FActScore: Fine-grained atomic evaluation of factual precision in long form text generation

Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Koh, Mohit Iyyer, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2023 · 2023

Cited alongside, same era.

Averitec: A dataset for real-world claim verification with evidence from the web

Michael Schlichtkrull, Zhijiang Guo, and Andreas Vlachos. 2023 · 2023

Cited alongside, same era.

ZeroSCROLLS: A zero-shot benchmark for long text understanding

Uri Shaham, Maor Ivgi, Avia Efrat, Jonathan Berant, and Omer Levy. 2023 · 2023

Cited alongside, same era.

Large language models can be easily distracted by irrelevant context

Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed Chi, Nathanael Schärli, and Denny Zhou. 2023 · 2023

Cited alongside, same era.

Desiderata for the context use of question answering systems

Sagi Shaier, Lawrence Hunter, and Katharina von der Wense. 2024 · 2024

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Assessing “implicit” retrieval robustness of large language models

Xiaoyu Shen, Rexhina Blloshmi, Dawei Zhu, Jiahuan Pei, and Wei Zhang. 2024 · 2024

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Trusting your evidence: Hallucinate less with context-aware decoding

Weijia Shi, Xiaochuang Han, Mike Lewis, Yulia Tsvetkov, Luke Zettlemoyer, and Wen-tau Yih. 2024 · 2024

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What evidence do language models find convincing?

Alexander Wan, Eric Wallace, and Dan Klein. 2024 · 2024

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Large language models can learn temporal reasoning

Siheng Xiong, Ali Payani, Ramana Kompella, and Faramarz Fekri. 2024 · 2024

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Knowledge conflicts for LLMs: A survey

Rongwu Xu, Zehan Qi, Zhijiang Guo, Cunxiang Wang, Hongru Wang, Yue Zhang, and Wei Xu. 2024 · 2024