18 citations · 41 across the 16 of their papers we have counts for
5 papers · 1 filter
Enhance Graph Alignment for Large Language Models
Haitong Luo, Xuying Meng, Suhang Wang +4
Graph-structured data is prevalent in the real world. Recently, due to the powerful emergent capabilities, Large Language Models (LLMs) have shown promising performance in modeling…
Sketch: A Toolkit for Streamlining LLM Operations
Xin Jiang, Xiang Li, Wenjia Ma +8
Large language models (LLMs) represented by GPT family have achieved remarkable success. The characteristics of LLMs lie in their ability to accommodate a wide range of tasks throu…
Open-domain Implicit Format Control for Large Language Model Generation
Yiqun Yao, Wenjia Ma, Xuezhi Fang +7
Controlling the format of outputs generated by large language models (LLMs) is a critical functionality in various applications. Current methods typically employ constrained decodi…
Not All Layers of LLMs Are Necessary During Inference
Siqi Fan, Xin Jiang, Xiang Li +6
Due to the large number of parameters, the inference phase of Large Language Models (LLMs) is resource-intensive. However, not all requests posed to LLMs are equally difficult to h…
Spectral-Based Graph Neural Networks for Complementary Item Recommendation
Haitong Luo, Xuying Meng, Suhang Wang +4
Modeling complementary relationships greatly helps recommender systems to accurately and promptly recommend the subsequent items when one item is purchased. Unlike traditional simi…