most citedSafety Alignment of Large Language Models via Contrasting Safe and Harmful Distributions

2 citations · 3 across the 3 of their papers we have counts for

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cs.CL2024

InverseCoder: Self-improving Instruction-Tuned Code LLMs with Inverse-Instruct

Yutong Wu, Di Huang, Wenxuan Shi +13

Recent advancements in open-source code large language models (LLMs) have been driven by fine-tuning on the data generated from powerful closed-source LLMs, which are expensive to…

cs.CL2024★ 2 cited

Safety Alignment of Large Language Models via Contrasting Safe and Harmful Distributions

Xiaoyun Zhang, Zhengyue Zhao, Wenxuan Shi +3

With the widespread application of Large Language Models (LLMs), it has become a significant concern to ensure their safety and prevent harmful responses. While current safe-alignm…