{"data":{"id":16,"backendId":"26654a52-811e-4307-906a-e40b2dece20b","title":"Mozi: Governed Autonomy for Drug Discovery LLM Agents","summary":"arXiv:2603.03655v1 Announce Type: new Abstract: Tool-augmented large language model (LLM) agents promise to unify scientific reasoning with computation, yet their deployment in high-stakes domains like drug discovery is bottlenecked by two critical barriers: unconstrained tool-use governance and poor long-horizon reliability. In dependency-heavy pharmaceutical pipelines, autonomous agents often drift into irreproducible trajectories, where early-stage hallucinations multiplicatively compound int","analysis":"This research addresses the critical bottleneck of reliability in autonomous scientific agents. Its focus on governed autonomy is highly actionable for pharmaceutical R&D.","category":"technology","strategicTrack":"biotech","capitalRelevance":{"social":3,"cultural":5,"economic":8,"symbolic":4,"technological":10,"informational":9,"temporal":7,"psychological":2,"physical":8},"tags":["LLM Agents","Drug Discovery","AI4Science","Governance","Mozi"],"qualityScore":10,"valueScore":9,"interestScore":8,"potentialScore":9,"uniquenessScore":9,"sourceCount":1,"confidence":5,"detectedAt":"2026-03-06T00:09:43.308Z","createdAt":"2026-03-06 00:10:58"}}