1 citations · 1 across the 5 of their papers we have counts for
5 papers
Agentic BAIM-LLM Evaluation (ABLE): Benchmarking LLM Use of Protein Design Tools
Bryce Cai, Geetha Jeyapragasan, Samira Nedungadi +2
We introduce ABLE, a benchmark for evaluating LLM agents' ability to use biological AI models (BAIMs), such as ProteinMPNN and AlphaFold3, in dual-use protein design workflows. ABL…
ABC-Bench: An Agentic Bio-Capabilities Benchmark for Biosecurity
Andrew Bo Liu, Samira Nedungadi, Bryce Cai +3
Large language models (LLMs) are rapidly acquiring capabilities relevant to biological research, from literature synthesis to interpretation of experimental data. Increasingly, LLM…
LLM Novice Uplift on Dual-Use, In Silico Biology Tasks
Chen Bo Calvin Zhang, Christina Q. Knight, Nicholas Kruus +16
Large language models (LLMs) perform increasingly well on biology benchmarks, but it remains unclear whether they uplift novice users -- i.e., enable humans to perform better than…
Best Practices for Biorisk Evaluations on Open-Weight Bio-Foundation Models
Boyi Wei, Zora Che, Nathaniel Li +10
Open-weight bio-foundation models present a dual-use dilemma. While holding great promise for accelerating scientific research and drug development, they could also enable bad acto…
STREAM (ChemBio): A Standard for Transparently Reporting Evaluations in AI Model Reports
Tegan McCaslin, Jide Alaga, Samira Nedungadi +5
Evaluations of dangerous AI capabilities are important for managing catastrophic risks. Public transparency into these evaluations - including what they test, how they are conducte…