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cs.CL2026
SCOUT: Active Information Foraging for Long-Text Understanding with Decoupled Epistemic States
Zhenliang Zhang, Wenqing Wang, Yong Hu +4
Long-Text Understanding (LTU) at million-token scale requires balancing reasoning fidelity with computational efficiency. Frontier long-context LLMs can process millions of token c…
cs.CL2026
BiT-MCTS: A Theme-based Bidirectional MCTS Approach to Chinese Fiction Generation
Zhaoyi Li, Xu Zhang, Xiaojun Wan
Generating long-form linear fiction from open-ended themes remains a major challenge for large language models, which frequently fail to guarantee global structure and narrative di…
cs.CL2024
Evaluating, Understanding, and Improving Constrained Text Generation for Large Language Models
Xiang Chen, Xiaojun Wan
Advancements in natural language generation (NLG) and large language models (LLMs) have led to proficient text generation in various tasks. However, integrating intricate constrain…