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This work studies whether learning from both the controller's decisions and the experts'reasoning and code improves its generation after expert removal, and introduces Rivet for collaboration internalization, supporting the effectiveness of training on the content and structure of verified collaborations.
ClinPRISM, a cost-effective multimodal LLM reasoning framework for question answering over ICTS data, is proposed and achieves state-of-the-art performance on the held-out evaluation benchmark while using only 16 time-series tokens and achieving an average inference latency of 0.15 seconds per question.
CLINLENS is introduced, a benchmark of 200 executable tasks over five linked MIMIC resources spanning structured electronic health records, notes, electrocardiograms, chest radiographs, and echocardiograms, which exposes a substantial gap between runnable submissions and correct clinical analyses.
CLIR-Bench is introduced, a benchmark for irregular clinical time series QA constructed from de-identified ICU records through a principled four-stage pipeline, enabling evaluation of both answer accuracy and evidence use.
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