5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.LG2026
SupportCal: Label-Free Calibration of Post-Trained LLMs via Reference Support and Corroboration
Linhan Luo, Lequan Lin, Dai Shi +3
Post-training often improves task performance but can degrade confidence calibration, leaving post-trained language models (PoLMs) more overconfident than their corresponding pretr…
cs.LG2026
SGNN: Efficient Global Mixing and Local Message Passing for Long-Range Graph Learning
Dai Shi, Luke Thompson, Linhan Luo +4
Message-passing neural networks (MPNNs) often suffer from an information bottleneck when capturing long-range dependencies, leading to the oversquashing (OSQ) phenomenon. Alongside…
cs.IR2021★ 5 cited
DAGNN: Demand-aware Graph Neural Networks for Session-based Recommendation
Liqi Yang, Linhan Luo, Lifeng Xin +2
Session-based recommendations have been widely adopted for various online video and E-commerce Websites. Most existing approaches are intuitively proposed to discover underlying in…