28 citations · 35 across the 12 of their papers we have counts for
3 papers · 1 filter
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
Tong Wu, Shujian Zhang, Kaiqiang Song +7
Large Language Models (LLMs) are susceptible to security and safety threats, such as prompt injection, prompt extraction, and harmful requests. One major cause of these vulnerabili…
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets
Sathish Reddy Indurthi, Wenxuan Zhou, Shamil Chollampatt +4
Advancements in Large Language Models (LLMs) have significantly enhanced instruction-following capabilities. However, most Instruction Fine-Tuning (IFT) datasets are predominantly…
WPO: Enhancing RLHF with Weighted Preference Optimization
Wenxuan Zhou, Ravi Agrawal, Shujian Zhang +5
Reinforcement learning from human feedback (RLHF) is a promising solution to align large language models (LLMs) more closely with human values. Off-policy preference optimization,…