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This work proposes a novel framework, Search2Skill, that automatically identifies the agent's capability gaps, searches external sources to address them, and distills the retrieved evidence into structured, reusable skills.
Credit-Aware Hierarchical Memory Evolution (CHIME), a self-evolving memory framework that maintains a separate planning bank and execution bank and follows an attribute-before-memorize principle, which shows that CHIME consistently outperforms state-of-the-art training-based and self-evolving memory baselines.
This work proposes OM-GRPO, a label-free RLVR framework that decouples reward estimation from policy optimization and introduces Contrast-Augmented Reward, which refines reward estimation via low-cost pairwise comparisons over existing trajectories without additional rollouts.
PAMT is proposed, a process-aligned training framework that combines cold-start domain-aware Long-CoT supervision with reinforcement learning that improves over base models, outperforms MT-specialized baselines on average, and remains competitive with strong LLMs/LRMs across in-domain, OOD, and multilingual settings.
TwT (Translation with Thought), a resource-rational framework that learns to modulate inference between intuitive and deliberate reasoning, confirms that aligning translation behavior with cognitive principles enables robust generalization, high translation quality, and efficient reasoning in MDMT.
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