GenoMAS: Guided Multi-Agent Programming for Scientific Discovery from Genomic Data
cs.AI, cs.LG, cs.MA, q-bio.GN
Submitted: 2025-07-28
Updated: 2026-10-20
Comments: Accepted to EMNLP 2026 Findings. Project page at https://liu-hy.github.io/GenoMAS/ and code at https://github.com/Liu-Hy/GenoMAS
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems