5 papers
Purely Agent-Driven Black-Box Optimization for Biological Design
Natalie Maus, Yimeng Zeng, Haydn Thomas Jones +11
Many key challenges in biological design -- such as small-molecule drug discovery, antimicrobial peptide development, and protein engineering -- can be framed as black-box optimiza…
AgentLongBench: A Controllable Long Benchmark For Long-Contexts Agents via Environment Rollouts
Shicheng Fang, Yuxin Wang, Xiaoran Liu +6
The evolution of Large Language Models (LLMs) into autonomous agents necessitates the management of extensive, dynamic contexts. Current benchmarks, however, remain largely static,…
Few-shot Protein Fitness Prediction via In-context Learning and Test-time Training
Felix Teufel, Aaron W. Kollasch, Yining Huang +4
Accurately predicting protein fitness with minimal experimental data is a persistent challenge in protein engineering. We introduce PRIMO (PRotein In-context Mutation Oracle), a tr…
Multi-Scale Representation Learning for Protein Fitness Prediction
Zuobai Zhang, Pascal Notin, Yining Huang +5
Designing novel functional proteins crucially depends on accurately modeling their fitness landscape. Given the limited availability of functional annotations from wet-lab experime…
Navigating Chemical Space with Latent Flows
Guanghao Wei, Yining Huang, Chenru Duan +2
Recent progress of deep generative models in the vision and language domain has stimulated significant interest in more structured data generation such as molecules. However, beyon…