Search Results for author: Liang Wen

Found 3 papers, 1 papers with code

Original Content Is All You Need! an Empirical Study on Leveraging Answer Summary for WikiHowQA Answer Selection Task

no code implementations COLING 2022 Liang Wen, Juan Li, Houfeng Wang, Yingwei Luo, Xiaolin Wang, Xiaodong Zhang, Zhicong Cheng, Dawei Yin

And their experiments show that leveraging the answer summaries helps to attend the essential information in original lengthy answers and improve the answer selection performance under certain circumstances.

All Answer Selection

Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond

1 code implementation13 Mar 2025 Liang Wen, Yunke Cai, Fenrui Xiao, Xin He, Qi An, Zhenyu Duan, Yimin Du, Junchen Liu, Lifu Tang, Xiaowei Lv, Haosheng Zou, Yongchao Deng, Shousheng Jia, Xiangzheng Zhang

Experimental results show that this curriculum approach becomes more effective when distinct, diverse datasets are available for different training stages: fine-tuning DeepSeek-R1-Distilled models (pre-tuned by DeepSeek team on proprietary data) with 3, 000 challenging examples from our curriculum dataset yielded state-of-the-art 7B and 14B models, while the 32B model, Light-R1-32B-DS performed comparably to QwQ-32B and DeepSeek-R1.

Domain Generalization Math

Unlocking the Potential: Benchmarking Large Language Models in Water Engineering and Research

no code implementations22 Jul 2024 Boyan Xu, Liang Wen, Zihao Li, Yuxing Yang, Guanlan Wu, Xiongpeng Tang, Yu Li, Zihao Wu, Qingxian Su, Xueqing Shi, Yue Yang, Rui Tong, How Yong Ng

Overall, this study pioneered evaluating LLMs in water engineering and research by introducing the WaterER benchmark to assess the trustworthiness of their predictions.

Benchmarking

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