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cs.CL2026
EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning
Can Xie, Yuyi Zhou, Wen Yang +5
Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable exploration patterns embedded in i…
cs.CL2026
DialectS2S: End-to-End Speech Dialogue Modeling for Low-Resource Chinese Dialects
Yi Shu, Tianyu Peng, Yingzhuo Deng +5
Current end-to-end speech dialogue models are primarily optimized for mainstream languages and remain limited in low-resource dialect scenarios due to the scarcity of dialect speec…
cs.CL2026
TokAlign++: Advancing Vocabulary Adaptation via Better Token Alignment
Chong Li, Yingzhuo Deng, Wen Yang +2
Tokenization is a foundational step in the text process of Large Language Models (LLMs). Texts must be first tokenized into token IDs, which are then input to LLMs. Inefficient tok…