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While recent large language models (LLMs) improve on various question answering (QA) datasets, it remains difficult for a single model to generalize across question types that require distinct reasoning abilities.
Question Answering is a Format; When is it Useful?
Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, and Sewon Min. 2019 · 1909
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Adaptive Mixtures of Local Experts
Robert A. Jacobs, Michael I. Jordan, Steven J. Nowlan, and Geoffrey E. Hinton. 1991 · 1991
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On the Foundations of Noise-free Selective Classification
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Solving general arithmetic word problems
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SQuAD: 100,000+ Questions for Machine Comprehension of Text
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TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension
Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, and Danqi Chen. 2019 · 2019
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QASC: A Dataset for Question Answering via Sentence Composition
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Natural questions: A benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur P. 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 V. Le, and Slav Petrov. 2019 · 2019
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Quizbowl: The case for incremental question answering
Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, and Jordan L. Boyd-Graber. 2019 · 2019
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MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension
Alon Talmor and Jonathan Berant. 2019 · 2019
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CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019
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How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering
Zhengbao Jiang, J. Araki, Haibo Ding, and Graham Neubig. 2020 · 2020
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Selective Question Answering under Domain Shift
Amita Kamath, Robin Jia, and Percy Liang. 2020 · 2020
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UnifiedQA: Crossing Format Boundaries With a Single QA System
Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, and Hannaneh Hajishirzi. 2020 · 2020
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GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
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Answering Open-Domain Questions of Varying Reasoning Steps from Text
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Evaluating Large Language Models Trained on Code
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Training Verifiers to Solve Math Word Problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021
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Single-dataset Experts for Multi-dataset Question Answering
Dan Friedman, Ben Dodge, and Danqi Chen. 2021 · 2021
Learning to Explain Selectively: A Case Study on Question Answering
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Unsupervised Dense Information Retrieval with Contrastive Learning
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MetaICL: Learning to Learn In Context
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Introducing ChatGPT
OpenAI. 2022 · 2022
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Measuring and narrowing the compositionality gap in language models
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Revisiting Calibration for Question Answering
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Will this Question be Answered? Question Filtering via Answer Model Distillation for Efficient Question Answering
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DEMix Layers: Disentangling Domains for Modular Language Modeling
Suchin Gururangan, Michael Lewis, Ari Holtzman, Noah A. Smith, and Luke Zettlemoyer. 2021 · 2021
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BASE Layers: Simplifying Training of Large, Sparse Models
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Generated Knowledge Prompting for Commonsense Reasoning
Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, and Hannaneh Hajishirzi. 2021 · 2021
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Cross-Task Generalization via Natural Language Crowdsourcing Instructions
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Are NLP Models really able to Solve Simple Math Word Problems?
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Qa dataset explosion: A taxonomy of nlp resources for question answering and reading comprehension
Anna Rogers, Matt Gardner, and Isabelle Augenstein. 2021 · 2021
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CommonsenseQA 2.0: Exposing the Limits of AI through Gamification
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Chenglei Si, Chen Zhao, Sewon Min, and Jordan Boyd-Graber. 2022 · 2022
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Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
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Reliable visual question answering: Abstain rather than answer incorrectly
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Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes
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Scaling Expert Language Models with Unsupervised Domain Discovery
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LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion
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ChatGPT: Jack of all trades, master of none
Jan Koco’n, Igor Cichecki, Oliwier Kaszyca, Mateusz Kochanek, Dominika Szydlo, Joanna Baran, Julita Bielaniewicz, Marcin Gruza, Arkadiusz Janz, Kamil Kanclerz, Anna Koco’n, Bartlomiej Koptyra, Wiktoria Mieleszczenko-Kowszewicz, P. Milkowski, Marcin Oleksy, Maciej Piasecki, Lukasz Radli’nski, Konrad Wojtasik, Stanislaw Wo’zniak, and Przemyslaw Kazienko. 2023 · 2023
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MetaQA: Combining Expert Agents for Multi-Skill Question Answering
Haritz Puerto, Gözde Gül Sahin, and Iryna Gurevych. 2023 · 2023
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Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang. 2023 · 2023
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Self-Consistency Improves Chain of Thought Reasoning in Language Models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Huai hsin Chi, and Denny Zhou. 2023 · 2023
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Satisfiability-Aided Language Models Using Declarative Prompting
Xi Ye, Qiaochu Chen, Işıl Dillig, and Greg Durrett. 2023 · 2023
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Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
Denny Zhou, Nathanael Scharli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, and Ed Huai hsin Chi. 2023 · 2023
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