135 citations · 557 across the 54 of their papers we have counts for
4 papers · 1 filter
Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs
Honglin Zhang, Qianyue Hao, Fengli Xu +1
Large language models (LLMs) acquire extensive prior knowledge through large-scale pretraining and can be further enhanced via supervised fine-tuning (SFT) or reinforcement learnin…
Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network
Lin Chen, Fengli Xu, Nian Li +4
Heterogeneous information networks (HIN) have gained increasing popularity in recent years for capturing complex relations between diverse types of nodes. Meta-structures are propo…
AttnMove: History Enhanced Trajectory Recovery via Attentional Network
Tong Xia, Yunhan Qi, Jie Feng +4
A considerable amount of mobility data has been accumulated due to the proliferation of location-based service. Nevertheless, compared with mobility data from transportation system…
Automorphic Equivalence-aware Graph Neural Network
Fengli Xu, Quanming Yao, Pan Hui +1
Distinguishing the automorphic equivalence of nodes in a graph plays an essential role in many scientific domains, e.g., computational biologist and social network analysis. Howeve…