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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

OmniBench: Towards The Future of Universal Omni-Language Models

Yizhi Li, Yinghao Ma, Ge Zhang +20

Recent advancements in multimodal large language models (MLLMs) have aimed to integrate and interpret data across diverse modalities. However, the capacity of these models to concu…

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

Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference

Yuxuan Song, Zheng Zhang, Cheng Luo +19

We present Seed Diffusion Preview, a large-scale language model based on discrete-state diffusion, offering remarkably fast inference speed. Thanks to non-sequential, parallel gene…

cs.CL2025

A Survey on Latent Reasoning

Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng +30

Large Language Models (LLMs) have demonstrated impressive reasoning capabilities, especially when guided by explicit chain-of-thought (CoT) reasoning that verbalizes intermediate s…