1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2025
CodeCriticBench: A Holistic Code Critique Benchmark for Large Language Models
Alexander Zhang, Marcus Dong, Jiaheng Liu +15
The critique capacity of Large Language Models (LLMs) is essential for reasoning abilities, which can provide necessary suggestions (e.g., detailed analysis and constructive feedba…
cs.AI2025★ 1 cited
Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models
Yingshui Tan, Yilei Jiang, Yanshi Li +6
Fine-tuning large language models (LLMs) based on human preferences, commonly achieved through reinforcement learning from human feedback (RLHF), has been effective in improving th…