Detecting Edit Failures In Large Language Models: An Improved Specificity Benchmark

Language models as knowledge bases?

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Language models are unsupervised multitask learners

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How can we know what language models know?

Zhengbao Jiang, Frank F. Xu, Jun Araki, and Graham Neubig. 2020 · 2020

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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

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How context affects language models’ factual predictions

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Exploring the limits of transfer learning with a unified text-to-text transformer

Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020

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How much knowledge can you pack into the parameters of a language model?

Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2020

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Modifying memories in transformer models

Original

Chen Zhu, Ankit Singh Rawat, Manzil Zaheer, Srinadh Bhojanapalli, Daliang Li, Felix Yu, and Sanjiv Kumar. 2020 · 2020

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Editing factual knowledge in language models

Nicola De Cao, Wilker Aziz, and Ivan Titov. 2021 · 2021

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Measuring and Improving Consistency in Pretrained Language Models

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Transformer feed-forward layers are key-value memories

Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy. 2021 · 2021

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GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model

Ben Wang and Aran Komatsuzaki. 2021 · 2021

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Calibrate before use: Improving few-shot performance of language models

Original

Tony Z. Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021

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Factual probing is [MASK]: Learning vs. learning to recall

Zexuan Zhong, Dan Friedman, and Danqi Chen. 2021 · 2021

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Knowledge neurons in pretrained transformers

Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei. 2022 · 2022

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Fast model editing at scale

Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, and Christopher D Manning. 2022 · 2022

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