DSIR large-scale data selection framework for language model training

A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.

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

Perform transfer learning for MIR using Jukebox!

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

[NeurIPS 2022] DRAGON : Deep Bidirectional Language-Knowledge Graph Pretraining

[ACL 2022] LinkBERT: A Knowledgeable Language Model Pretrained with Document Links

The Stanford Word Substitution (Swords) Benchmark

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

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