Discover p-lambda/incontext-learning Open Source project

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Created almost 3 years ago
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p-lambda

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Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"

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verified_calibration

Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlight).

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The Stanford Word Substitution (Swords) Benchmark

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in-n-out

Code for the ICLR 2021 Paper "In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness"

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robust_tradeoff

Code for the ICML 2020 paper "Understanding and Mitigating the Tradeoff Between Robustness and Accuracy", Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, and Percy Liang. Paper available at https://arxiv.org/pdf/2002.10716.pdf.

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composed_finetuning

Code for the ICML 2021 paper "Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization" by Sang Michael Xie, Tengyu Ma, Percy Liang

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p-lambda/incontext-learning

p-lambda

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