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We present Backpacks: a new neural architecture that marries strong modeling performance with an interface for interpretability and control.
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Attention is all you need
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Deep contextualized word representations
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A framework for few-shot language model evaluation
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Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Re. 2021 · 2021
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Obtaining better static word embeddings using contextual embedding models
Prakhar Gupta and Martin Jaggi. 2021 · 2021
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Multilingual and multilabel emotion recognition using virtual adversarial training
Vikram Gupta. 2021 · 2021
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Assessing the quality of human-generated summaries with weakly supervised learning
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Openwebtext corpus
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Linguistic knowledge and transferability of contextual representations
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GPT-J-6B: A 6 billion parameter autoregressive language model
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Twitter topic classification
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Scalable interpretability via polynomials
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Probing for incremental parse states in autoregressive language models
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Training compute-optimal large language models
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Locating and editing factual associations in GPT
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In-context learning and induction heads
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Neural basis models for interpretability
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Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018 · 2022
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Mass-editing memory in a transformer
Kevin Meng, Arnab Sen Sharma, Alex J Andonian, Yonatan Belinkov, and David Bau. 2023 · 2023
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