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Vision-language models (VLMs) have achieved strong performance in multimodal reasoning, yet they remain prone to generating plausible but incorrect answers. Self-verification offers a practical way to improve answer reliability without relying on external judges, but existing methods typically depend on a single verifi...
Action-conditioned time-series forecasting requires accounting for how future actions and exogenous forcings influence multiple targets through partially observed effects with different delays and persistence. Direct conditioning leaves the evolution and target-specific influence of these effects implicit in the predic...
DrugReason is proposed, a multi-view reasoning framework that integrates grounded KG reasoning with LLM-generated mechanistic inference for drug repurposing and achieves competitive or superior results compared with graph-based alternatives, while providing interpretable routing-based predictions.
HarnessRisk, a lifecycle oriented benchmark that organizes agent harness safety into six operational phases including Harness Configuration, Capability Extension, Runtime Operation, State Persistence, Action Control, and Incident Recovery, finds that explicit risk recognition does not reliably lead to safe action as so...
Examination of the impact of agent diversity, agent open-mindedness, and human–AI collaboration (HAIC) in a multi-LLM-agent system for automated content analysis demonstrates reliable and accurate measurement of four communication variables across three datasets, with improved performance following agent discussion.
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