DN-Hypo-Pipeline operationalizes three philosophy-of-science accounts to direct LLMs toward principle-based hypothesis generation, claims superior performance over direct prompting, and derives two new transformer algorithms from the resulting hypotheses.
Large language models as biomedical hypothesis generators: a comprehensive evaluation
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The paper introduces CoLabScience with PULI, a positive-unlabeled RL framework for proactive interventions in streaming biomedical dialogues, plus the BSDD benchmark dataset, claiming superior performance over baselines.
A survey that deconstructs LLM agent systems via a methodology-centered taxonomy linking design principles to emergent behaviors, applications, and challenges.
Position paper claims multimodal LLMs can significantly advance scientific reasoning and proposes a four-stage roadmap plus challenges and suggestions.
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"Excuse me, may I say something..." CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations
The paper introduces CoLabScience with PULI, a positive-unlabeled RL framework for proactive interventions in streaming biomedical dialogues, plus the BSDD benchmark dataset, claiming superior performance over baselines.