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EvoRS is introduced, a self-evolving RL framework that evolves the reward system from on-policy experience, representing it as an executable Reward-DAG, and is updated from on-policy rollouts and reward traces to maintain train-time reliability.
This work proposes SocialRL, a multi-turn reinforcement learning framework using PPO that propagates delayed outcome rewards back to each turn, enabling long-horizon planning and demonstrates the effectiveness of SocialRL across synthetic and real social scenes, as well as standard and challenging social scenarios.
DCFA is proposed, a training-free framework for failure attribution that integrates a global module that constructs structured causal-inspired dependency graphs from system traces to identify the initial decisive error, and a local module that applies local counterfactual-inspired reasoning to refine causal-inspired at...
AnySearch is proposed, a framework that enables a single policy to perform budget-aware search under any budget constraint through a training scaffold and curriculum reinforcement learning, and outperforms baselines across all budget scales.
This paper introduces FinED-Bench, the first publicly public benchmark for FinED-Bench, which covers nine real-world financial scenarios, and includes over 900 documents reported in 2025 that are unseen by existing language models.
Skill-Use is introduced, a benchmark that evaluates skill use under progressive disclosure, where an agent sees only a skill's name and short description and must retrieve the full procedure before following it.
A novel policy gradient method is introduced, Hindsight Policy Optimization (HPO), that projects both the current policy distribution and the hindsight distribution into an intent space and extracts low-variance learning signals from the Wasserstein distance between them.
A multi-layer taxonomy of 14 capability domains and 91 subskills across Primitive, Constructed, and Integrative layers is introduced and supports research organization, coverage audits, evaluation interpretation, and testable hypotheses for diagnosis, training, and transfer.
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