8 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.LG2025
BoxingGym: Benchmarking Progress in Automated Experimental Design and Model Discovery
Kanishk Gandhi, Michael Y. Li, Lyle Goodyear +5
Understanding the world and explaining it with scientific theories is a central aspiration of artificial intelligence research. Proposing theories, designing experiments to test th…
cs.CL2023★ 8 cited
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
Zhengxuan Wu, Atticus Geiger, Thomas Icard +2
Obtaining human-interpretable explanations of large, general-purpose language models is an urgent goal for AI safety. However, it is just as important that our interpretability met…
cs.LG2021★ 6 cited
DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning
Alex Tamkin, Vincent Liu, Rongfei Lu +3
Self-supervised learning algorithms, including BERT and SimCLR, have enabled significant strides in fields like natural language processing, computer vision, and speech processing.…