5 papers
Personalization Meets Safety:Mechanisms,Risks,and Mitigations in Personalized LLMs
Yanyan Luo, Xue Han, Ruiqiao Bai +10
Large Language Models (LLMs) have enabled increasingly personalized interactions by adapting to users' preferences, contexts, and long-term histories. However, the mechanisms that…
ChildEval: When large language models meet children's personalities
Yanyan Luo, Xue Han, Chunxu Zhao +5
While LLMs enable personalized chatbots, their effectiveness in child-centered personalization remains unclear, as systematic evaluation of child-specific preferences is still lack…
MultiPL-MoE: Multi-Programming-Lingual Extension of Large Language Models through Hybrid Mixture-of-Experts
Qing Wang, Xue Han, Jiahui Wang +5
Despite LLMs' excellent code creation capabilities, multilingual code generation remains extremely challenging. To address this, we intent to improve the multi-programming-lingual…
Temporal Alignment of LLMs through Cycle Encoding for Long-Range Time Representations
Xue Han, Qian Hu, Yitong Wang +6
Large language models (LLMs) suffer from temporal misalignment issues especially across long span of time. The issue arises from knowing that LLMs are trained on large amounts of d…
ESCL: Equivariant Self-Contrastive Learning for Sentence Representations
Jie Liu, Yixuan Liu, Xue Han +2
Previous contrastive learning methods for sentence representations often focus on insensitive transformations to produce positive pairs, but neglect the role of sensitive transform…