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Transformer-based Large Language Models (LLMs) are the state-of-the-art for natural language tasks.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler · 2015
Earlier work this paper cites.
A mathematical framework for transformer circuits, 2021
Nelson Elhage, Neel Nanda, Catherine Olsson, Tom Henighan, Nicholas Joseph, Ben Mann, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, Nova DasSarma, Dawn Drain, Deep Ganguli, Zac Hatfield-Dodds, Danny Hernandez, Andy Jones, Jackson Kernion, Liane Lovitt, Kamal Ndousse, Dario Amodei, Tom Brown, Jack Clark, Jared Kaplan, Sam McCandlish, and Chris Olah · 2021
Earlier work this paper cites.
Transformer feed-forward layers are key-value memories
Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy · 2021
Earlier work this paper cites.
Logit Lens on non-GPT2 models + extensions, 2021
nostalgebraist · 2021
Earlier work this paper cites.
Analyzing transformers in embedding space
Guy Dar, Mor Geva, Ankit Gupta, and Jonathan Berant · 2022
Earlier work this paper cites.
Locating and editing factual associations in GPT
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov · 2022
Earlier work this paper cites.
In-context learning and induction heads
Catherine Olsson, Nelson Elhage, Neel Nanda, Nicholas Joseph, Nova DasSarma, Tom Henighan, Ben Mann, Amanda Askell, Yuntao Bai, Anna Chen, et al · 2022
Cited alongside, same era.
Ignore previous prompt: Attack techniques for language models
Fábio Perez and Ian Ribeiro · 2022
Cited alongside, same era.
Interpretability in the wild: A circuit for indirect object identification in GPT-2 Small
Kevin Wang, Alexandre Variengien, Arthur Conmy, Buck Shlegeris, and Jacob Steinhardt · 2022
Cited alongside, same era.
Eliciting latent predictions from transformers with the tuned lens
Nora Belrose, Zach Furman, Logan Smith, Danny Halawi, Igor Ostrovsky, Lev McKinney, Stella Biderman, and Jacob Steinhardt · 2023
Cited alongside, same era.
Backdoor attacks for in-context learning with language models
Nikhil Kandpal, Matthew Jagielski, Florian Tramèr, and Nicholas Carlini · 2023
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PMET: Precise model editing in a transformer
Xiaopeng Li, Shasha Li, Shezheng Song, Jing Yang, Jun Ma, and Jie Yu · 2023
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The Hydra effect: Emergent self-repair in language model computations
Thomas McGrath, Matthew Rahtz, Janos Kramar, Vladimir Mikulik, and Shane Legg · 2023
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Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, and Ian Foster · 2023
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Activation addition: Steering language models without optimization
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Mor Geva, Jasmijn Bastings, Katja Filippova, and Amir Globerson · 2023
Cited alongside, same era.
Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz · 2023
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever
Cited in the paper.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al
Cited in the paper.
Alex Turner, Lisa Thiergart, David Udell, Gavin Leech, Ulisse Mini, and Monte MacDiarmid · 2023
Closest in time.