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This paper presents VDSS, a human-in-the-loop multi-agent framework for ventilator decision support that uses contextual bandit preference learning to adapt to clinician-specific tuning styles, with retrospective ICU trajectory replays showing improved recommendation acceptability and reduced interaction rounds.
Announces two open-source Rust projects: Lycan (a graph execution language for contextual bandits) and Syntra (a self-hosted Docker appliance for serving Lycan capsules). The author dogfoods them on a live AI trading product, discovering that data pipeline bugs, not algorithm issues, dominated the adaptation work.
This paper introduces LQM-ContextRoute, a contextual bandit router for selecting between functionally equivalent tool providers in LLM agents, balancing latency and answer quality. It outperforms baselines on web-search and retriever benchmarks.