1 citations · 1 across the 9 of their papers we have counts for
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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LLMs often suffer from hallucinations and outdated or incomplete knowledge.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…
Weaver: Foundation Models for Creative Writing
Tiannan Wang, Jiamin Chen, Qingrui Jia +43
This work introduces Weaver, our first family of large language models (LLMs) dedicated to content creation. Weaver is pre-trained on a carefully selected corpus that focuses on im…