4 papers · 1 filter
Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
Shiping Yang, Jie Wu, Wenbiao Ding +7
Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustness to explicit noise (e.g., document s…
Step-Back Profiling: Distilling User History for Personalized Scientific Writing
Xiangru Tang, Xingyao Zhang, Yanjun Shao +6
Large language models (LLM) excel at a variety of natural language processing tasks, yet they struggle to generate personalized content for individuals, particularly in real-world…
Coherent Entity Disambiguation via Modeling Topic and Categorical Dependency
Zilin Xiao, Linjun Shou, Xingyao Zhang +4
Previous entity disambiguation (ED) methods adopt a discriminative paradigm, where prediction is made based on matching scores between mention context and candidate entities using…
Instructed Language Models with Retrievers Are Powerful Entity Linkers
Zilin Xiao, Ming Gong, Jie Wu +4
Generative approaches powered by large language models (LLMs) have demonstrated emergent abilities in tasks that require complex reasoning abilities. Yet the generative nature stil…