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Mozi: Governed Autonomy for Drug Discovery LLM Agents
technology biotech March 6, 2026 1 source · confidence 5/10
#LLM Agents
#Drug Discovery
#AI4Science
#Governance
#Mozi
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.
5D Score
Capital Relevance
technological 10/10
informational 9/10
economic 8/10
physical 8/10
temporal 7/10
cultural 5/10
symbolic 4/10
social 3/10
psychological 2/10
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