5 papers
A Survey on Training-free Alignment of Large Language Models
Birong Pan, Yongqi Li, Weiyu Zhang +6
The alignment of large language models (LLMs) aims to ensure their outputs adhere to human values, ethical standards, and legal norms. Traditional alignment methods often rely on r…
Format as a Prior: Quantifying and Analyzing Bias in LLMs for Heterogeneous Data
Jiacheng Liu, Mayi Xu, Qiankun Pi +5
Large Language Models (LLMs) are increasingly employed in applications that require processing information from heterogeneous formats, including texts, tables, infoboxes, and knowl…
Privacy-protected Retrieval-Augmented Generation for Knowledge Graph Question Answering
Yunfeng Ning, Mayi Xu, Jintao Wen +5
LLMs often suffer from hallucinations and outdated or incomplete knowledge. RAG is proposed to address these issues by integrating external knowledge like that in KGs into LLMs. Ho…
Aligning VLM Assistants with Personalized Situated Cognition
Yongqi Li, Shen Zhou, Xiaohu Li +9
Vision-language models (VLMs) aligned with general human objectives, such as being harmless and hallucination-free, have become valuable assistants of humans in managing visual tas…
Toxicity Detection towards Adaptability to Changing Perturbations
Hankun Kang, Jianhao Chen, Yongqi Li +5
Toxicity detection is crucial for maintaining the peace of the society. While existing methods perform well on normal toxic contents or those generated by specific perturbation met…