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Although large-scale pre-trained language models (PTLMs) are shown to encode rich knowledge in their model parameters, the inherent knowledge in PTLMs can be opaque or static, making external knowledge necessary.
Reducing the dimensionality of data with neural networks
Geoffrey E Hinton and Ruslan R Salakhutdinov · 2006
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Choice of plausible alternatives: An evaluation of commonsense causal reasoning
Melissa Roemmele, Cosmin Adrian Bejan, and Andrew S Gordon · 2011
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Semantic parsing on Freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang · 2013
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Improvements to bm25 and language models examined
Andrew Trotman, Antti Puurula, and Blake Burgess · 2014
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Yodaqa: a modular question answering system pipeline
Petr Baudiš · 2015
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Deep learning
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun · 2015
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer · 2017
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e-snli: Natural language inference with natural language explanations
Oana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz, and Phil Blunsom · 2018
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ATOMIC: an atlas of machine commonsense for if-then reasoning
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Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning · 2018
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Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Dense passage retrieval for open-domain question answering
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D. Khashabi, S. Min, T. Khot, A. Sabhwaral, O. Tafjord, P. Clark, and H. Hajishirzi · 2020
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Colbert: Efficient and effective passage search via contextualized late interaction over bert
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Calibrated language model fine-tuning for in- and out-of-distribution data
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Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, and Laurent Sifre · 2022
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Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George Bm Van Den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego De Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack Rae, Erich Elsen, and Laurent Sifre · 2022
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Understanding dataset difficulty with 𝒱 \mathcal{V} -usable information
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Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies
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Sensitivity as a Complexity Measure for Sequence Classification Tasks
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Teaching models to express their uncertainty in words, 2022
Stephanie Lin, Jacob Hilton, and Owain Evans · 2022
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A meta-framework for spatiotemporal quantity extraction from text
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Entity cloze by date: What LMs know about unseen entities
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Knowledge-in-context: Towards knowledgeable semi-parametric language models
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Hindsight: Posterior-guided training of retrievers for improved open-ended generation
Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, and Christopher D Manning · 2022
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ColBERTv2: Effective and efficient retrieval via lightweight late interaction
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Black-box tuning for language-model-as-a-service
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, and Denny Zhou · 2022
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A survey of knowledge-intensive nlp with pre-trained language models
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CIKQA: Learning commonsense inference with a unified knowledge-in-the-loop QA paradigm
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Opt: Open pre-trained transformer language models, 2022
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On measuring the intrinsic few-shot hardness of datasets
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Can lms learn new entities from descriptions? challenges in propagating injected knowledge, 2023
Yasumasa Onoe, Michael J. Q. Zhang, Shankar Padmanabhan, Greg Durrett, and Eunsol Choi · 2023
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