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DecisionRobust is introduced, a benchmark for systematically evaluating the robustness of decision models across textual and visual inputs and shows that attacks expose vulnerabilities beyond the models used for construction and selection.
Reinforcement learning with verifiable rewards (RLVR) provides reliable supervision for software engineering agents through executable tests, but binary rewards fail to distinguish trajectories with substantially different debugging quality. We investigate whether the current policy can judge its own trajectories and u...
Auditable forecasting report that makes forecast construction explicit and supports systematic post hoc analysis, and improves forecasting accuracy and calibration relative to strong agentic baselines, surpasses market-implied references in several settings, and outperforms substantially more expensive deep-research ag...
This work introduces the \method (\methodshort), a self-evolving critic framework in which an LLM critic accumulates evidence from its own past judgments and their observed consequences, reducing ECE by up to $54\% relative to the strongest training-free baseline.
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