3 citations · 7 across the 10 of their papers we have counts for
10 papers
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference
Junzhi Li, Peng He, Qirui Ji +3
The performance of large language model (LLM)-based multi-agent systems (MAS) largely depends on effective communication topologies. Existing topology generation methods, however,…
TIDE-Bench: Task-Aware and Diagnostic Evaluation of Tool-Integrated Reasoning
Yize Li, Junzhi Li, Jason Song +3
Tool-integrated reasoning has emerged as a promising paradigm for enhancing large language models with external computation, retrieval, and execution capabilities. However, the fie…
Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration
Jinglin Xu, Yi Li, Chuxiong Sun +3
Multi-modal test-time adaptation (TTA) enhances the resilience of benchmark multi-modal models against distribution shifts by leveraging the unlabeled target data during inference.…
HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning
Qirui Ji, Bin Qin, Yifan Jin +5
Graph contrastive learning (GCL) aims to learn discriminative semantic invariance by contrasting different views of the same graph that share critical topological patterns. However…
Group Causal Policy Optimization for Post-Training Large Language Models
Ziyin Gu, Jingyao Wang, Ran Zuo +4
Recent advances in large language models (LLMs) have broadened their applicability across diverse tasks, yet specialized domains still require targeted post training. Among existin…
Rethinking Multi-Modal Learning from Gradient Uncertainty
Peizheng Guo, Jingyao Wang, Wenwen Qiang +3
Multi-Modal Learning (MML) integrates information from diverse modalities to improve predictive accuracy. While existing optimization strategies have made significant strides by mi…
Beyond All-to-All: Causal-Aligned Transformer with Dynamic Structure Learning for Multivariate Time Series Forecasting
Xingyu Zhang, Hanyun Du, Zeen Song +3
Most existing multivariate time series forecasting methods adopt an all-to-all paradigm that feeds all variable histories into a unified model to predict their future values withou…
Revisiting Communication Efficiency in Multi-Agent Reinforcement Learning from the Dimensional Analysis Perspective
Chuxiong Sun, Peng He, Rui Wang +1
In this work, we introduce a novel perspective, i.e., dimensional analysis, to address the challenge of communication efficiency in Multi-Agent Reinforcement Learning (MARL). Our f…
M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference
Chuxiong Sun, Peng He, Qirui Ji +4
Communication is essential in coordinating the behaviors of multiple agents. However, existing methods primarily emphasize content, timing, and partners for information sharing, of…
Rethinking Generalizability and Discriminability of Self-Supervised Learning from Evolutionary Game Theory Perspective
Jiangmeng Li, Zehua Zang, Qirui Ji +6
Representations learned by self-supervised approaches are generally considered to possess sufficient generalizability and discriminability. However, we disclose a nontrivial mutual…