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cs.CL2026

D2VBench: Benchmarking Large Language Models with Value Dilemmas in Daily Scenarios

Siyi Hao, Yidi Cao, Linhao Yu +2

With the wide application of large language models (LLMs) in real-world scenarios, the value implication of their outputs is crucial. However, existing evaluation benchmarks suffer…

cs.CL2026

Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts

Jingting Zheng, Yuqi Ren, Linhao Yu +2

Large Language Models (LLMs) are increasingly deployed in contexts requiring complex moral reasoning and value trade-offs. However, existing evaluations typically rely on item-leve…

cs.CL2026

ATTNPO: Attention-Guided Process Supervision for Efficient Reasoning

Shuaiyi Nie, Siyu Ding, Wenyuan Zhang +7

Large reasoning models trained with reinforcement learning and verifiable rewards (RLVR) achieve strong performance on complex reasoning tasks, yet often overthink, generating redu…

cs.CL2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data

Haoran Sun, Renren Jin, Shaoyang Xu +10

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…

cs.CL2024

Self-Pluralising Culture Alignment for Large Language Models

Shaoyang Xu, Yongqi Leng, Linhao Yu +1

As large language models (LLMs) become increasingly accessible in many countries, it is essential to align them to serve pluralistic human values across cultures. However, pluralis…

cs.CL2024

CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models

Linhao Yu, Yongqi Leng, Yufei Huang +9

What a large language model (LLM) would respond in ethically relevant context? In this paper, we curate a large benchmark CMoralEval for morality evaluation of Chinese LLMs. The da…