5 papers
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…
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…
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…
KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance
Linhao Yu, Tianmeng Yang, Siyu Ding +8
RLVR improves reasoning in large language models, but its effectiveness is often limited by severe reward sparsity on hard problems. Recent hint-based RL methods mitigate sparsity…
Large Language Model Safety: A Holistic Survey
Dan Shi, Tianhao Shen, Yufei Huang +10
The rapid development and deployment of large language models (LLMs) have introduced a new frontier in artificial intelligence, marked by unprecedented capabilities in natural lang…