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20242026
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cs.CL2026

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny

Chuanhao Yan, Fengdi Che, Xuhan Huang +12

Existing informal language-based (e.g., human language) Large Language Models (LLMs) trained with Reinforcement Learning (RL) face a significant challenge: their verification proce…

cs.CL2026

Beyond Correctness: Evaluating Subjective Writing Preferences Across Cultures

Shuangshuang Ying, Yunwen Li, Xingwei Qu +21

Current preference learning methods achieve high accuracy on standard benchmarks but exhibit significant performance degradation when objective quality signals are removed. We intr…

cs.CL2025

COIG-Writer: A High-Quality Dataset for Chinese Creative Writing with Thought Processes

Yunwen Li, Shuangshuang Ying, Xingwei Qu +16

Large language models exhibit systematic deficiencies in creative writing, particularly in non-English contexts where training data is scarce and lacks process-level supervision. W…

cs.CL2025

CodeBoost: Boosting Code LLMs by Squeezing Knowledge from Code Snippets with RL

Sijie Wang, Quanjiang Guo, Kai Zhao +7

Code large language models (LLMs) have become indispensable tools for building efficient and automated coding pipelines. Existing models are typically post-trained using reinforcem…

cs.CL2025

WirelessMathBench: A Mathematical Modeling Benchmark for LLMs in Wireless Communications

Xin Li, Mengbing Liu, Li Wei +3

Large Language Models (LLMs) have achieved impressive results across a broad array of tasks, yet their capacity for complex, domain-specific mathematical reasoning-particularly in…