733 citations · 2.4k across the 107 of their papers we have counts for
15 papers · 1 filter
Enhancing Training Data Attribution for Large Language Models with Fitting Error Consideration
Kangxi Wu, Liang Pang, Huawei Shen +1
The black-box nature of large language models (LLMs) poses challenges in interpreting results, impacting issues such as data intellectual property protection and hallucination trac…
ALiiCE: Evaluating Positional Fine-grained Citation Generation
Yilong Xu, Jinhua Gao, Xiaoming Yu +3
Large Language Model (LLM) can enhance its credibility and verifiability by generating text with citations. However, existing research on citation generation is predominantly limit…
A Theory for Token-Level Harmonization in Retrieval-Augmented Generation
Shicheng Xu, Liang Pang, Huawei Shen +1
Retrieval-augmented generation (RAG) utilizes retrieved texts to enhance large language models (LLMs). Studies show that while RAG provides valuable external information (benefit),…
Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning
Zixu Wang, Bingbing Xu, Yige Yuan +2
Graph contrastive learning (GCL), standing as the dominant paradigm in the realm of graph pre-training, has yielded considerable progress. Nonetheless, its capacity for out-of-dist…
Everything is Editable: Extend Knowledge Editing to Unstructured Data in Large Language Models
Jingcheng Deng, Zihao Wei, Liang Pang +3
Recent knowledge editing methods have primarily focused on modifying structured knowledge in large language models. However, this task setting overlooks the fact that a significant…
Knowledge Boundary and Persona Dynamic Shape A Better Social Media Agent
Junkai Zhou, Liang Pang, Ya Jing +3
Constructing personalized and anthropomorphic agents holds significant importance in the simulation of social networks. However, there are still two key problems in existing works:…