1 citations · 2 across the 12 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.LG2024★ 1 cited
RAGraph: A General Retrieval-Augmented Graph Learning Framework
Xinke Jiang, Rihong Qiu, Yongxin Xu +7
Graph Neural Networks (GNNs) have become essential in interpreting relational data across various domains, yet, they often struggle to generalize to unseen graph data that differs…
cs.LG2024★ 1 cited
3DS: Medical Domain Adaptation of LLMs via Decomposed Difficulty-based Data Selection
Hongxin Ding, Yue Fang, Runchuan Zhu +6
Large Language Models(LLMs) excel in general tasks but struggle in specialized domains like healthcare due to limited domain-specific knowledge.Supervised Fine-Tuning(SFT) data con…
cs.CL2024
Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning
Yongxin Xu, Ruizhe Zhang, Xinke Jiang +7
Retrieval-Augmented Generation (RAG) offers an effective solution to the issues faced by Large Language Models (LLMs) in hallucination generation and knowledge obsolescence by inco…