1 citations · 1 across the 1 of their papers we have counts for
5 papers
Two Stages of Folding: Convergent Mechanisms in AI Protein Folding Trunks
Kevin Lu, Jannik Brinkmann, Stefan Huber +4
How do protein structure prediction models fold proteins? We investigate this question through causal interventions on the folding trunks of ESMFold, OpenFold, and Boltz-1. Across…
Mixture of Complementary Agents for Robust LLM Ensemble
Yichi Zhang, Kevin Lu, Yuang Zhang +3
Multi-AI collaboration, such as ensembling or debating large language models (LLMs), is a promising paradigm for aggregating information and boosting performance. A foundational st…
When Are Concepts Erased From Diffusion Models?
Kevin Lu, Nicky Kriplani, Rohit Gandikota +4
In concept erasure, a model is modified to selectively prevent it from generating a target concept. Despite the rapid development of new methods, it remains unclear how thoroughly…
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
Shaona Ghosh, Heather Frase, Adina Williams +99
The rapid advancement and deployment of AI systems have created an urgent need for standard safety-evaluation frameworks. This paper introduces AILuminate v1.0, the first comprehen…
LAG-MMLU: Benchmarking Frontier LLM Understanding in Latvian and Giriama
Naome A. Etori, Kevin Lu, Randu Karisa +1
As large language models (LLMs) rapidly advance, evaluating their performance is critical. LLMs are trained on multilingual data, but their reasoning abilities are mainly evaluated…