10 citations · 15 across the 6 of their papers we have counts for
6 papers
T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration
Chuxiong Sun, Zehua Zang, Jiabao Li +4
Communication stands as a potent mechanism to harmonize the behaviors of multiple agents. However, existing works primarily concentrate on broadcast communication, which not only l…
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
Jiangmeng Li, Fei Song, Yifan Jin +4
As a novel and effective fine-tuning paradigm based on large-scale pre-trained language models (PLMs), prompt-tuning aims to reduce the gap between downstream tasks and pre-trainin…
M2HGCL: Multi-Scale Meta-Path Integrated Heterogeneous Graph Contrastive Learning
Yuanyuan Guo, Yu Xia, Rui Wang +3
Inspired by the successful application of contrastive learning on graphs, researchers attempt to impose graph contrastive learning approaches on heterogeneous information networks.…
Information Theory-Guided Heuristic Progressive Multi-View Coding
Jiangmeng Li, Hang Gao, Wenwen Qiang +1
Multi-view representation learning aims to capture comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning to differe…
Atomic and Subgraph-aware Bilateral Aggregation for Molecular Representation Learning
Jiahao Chen, Yurou Liu, Jiangmeng Li +2
Molecular representation learning is a crucial task in predicting molecular properties. Molecules are often modeled as graphs where atoms and chemical bonds are represented as node…
Interventional Contrastive Learning with Meta Semantic Regularizer
Wenwen Qiang, Jiangmeng Li, Changwen Zheng +2
Contrastive learning (CL)-based self-supervised learning models learn visual representations in a pairwise manner. Although the prevailing CL model has achieved great progress, in…