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cs.CL2026
Reinforcement World Model Learning for LLM-based Agents
Xiao Yu, Baolin Peng, Ruize Xu +6
Large language models (LLMs) have achieved strong performance in language-centric tasks. However, in agentic settings, LLMs often struggle to anticipate action consequences and ada…
cs.CL2025
RL from Teacher-Model Refinement: Gradual Imitation Learning for Machine Translation
Dongyub Jude Lee, Zhenyi Ye, Pengcheng He
Preference-learning methods for machine translation (MT), such as Direct Preference Optimization (DPO), have shown strong gains but typically rely on large, carefully curated prefe…
cs.CL2025
Chain of Draft: Thinking Faster by Writing Less
Silei Xu, Wenhao Xie, Lingxiao Zhao +1
Large Language Models (LLMs) have demonstrated remarkable performance in solving complex reasoning tasks through mechanisms like Chain-of-Thought (CoT) prompting, which emphasizes…