MolLingo introduces a multi-agent framework with BFE molecular representation and docking-grounded reasoning to outperform frontier LLMs on molecular design benchmarks including fourfold docking score gains.
Accelerating drug discovery through agentic ai: A multi-agent approach to laboratory automation in the dmta cycle.arXiv preprint arXiv:2507.09023, 2025
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FLARE extracts specifications from multi-agent LLM code and applies coverage-guided fuzzing to achieve 96.9% inter-agent and 91.1% intra-agent coverage while uncovering 56 new failures across 16 applications.
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MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents
MolLingo introduces a multi-agent framework with BFE molecular representation and docking-grounded reasoning to outperform frontier LLMs on molecular design benchmarks including fourfold docking score gains.
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FLARE: Agentic Coverage-Guided Fuzzing for LLM-Based Multi-Agent Systems
FLARE extracts specifications from multi-agent LLM code and applies coverage-guided fuzzing to achieve 96.9% inter-agent and 91.1% intra-agent coverage while uncovering 56 new failures across 16 applications.