5 papers
Source-Grounded Semantic Reinforcement Learning for Low-Resource Target-Language Generation
Zeli Su, Ziyin Zhang, Zewei Pan +8
Low-resource target-language generation is often limited by scarce parallel data, while high-resource source-language monolingual data is abundant but difficult to use with standar…
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…
POSS: Position Specialist Generates Better Draft for Speculative Decoding
Langlin Huang, Chengsong Huang, Jixuan Leng +2
Speculative decoding accelerates Large Language Model (LLM) inference by using a small draft model to predict multiple tokens, and a large target model to verify these tokens in pa…
HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations
Ziyu Wang, Hao Li, Di Huang +3
Effective patient care in digital healthcare requires large language models (LLMs) that not only answer questions but also actively gather critical information through well-crafted…
Skewed Memorization in Large Language Models: Quantification and Decomposition
Hao Li, Di Huang, Ziyu Wang +1
Memorization in Large Language Models (LLMs) poses privacy and security risks, as models may unintentionally reproduce sensitive or copyrighted data. Existing analyses focus on ave…