13 citations · 26 across the 19 of their papers we have counts for
10 papers · 1 filter
Learning Multi-Modal Mobility Dynamics for Generalized Next Location Recommendation
Junshu Dai, Yu Wang, Tongya Zheng +6
The precise prediction of human mobility has produced significant socioeconomic impacts, such as location recommendations and evacuation suggestions. However, existing methods suff…
Neural Graph Navigation for Intelligent Subgraph Matching
Yuchen Ying, Yiyang Dai, Wenda Li +6
Subgraph matching, a cornerstone of relational pattern detection in domains ranging from biochemical systems to social network analysis, faces significant computational challenges…
Towards Efficient LLM-aware Heterogeneous Graph Learning
Wenda Li, Tongya Zheng, Shunyu Liu +7
Heterogeneous graphs are widely present in real-world complex networks, where the diversity of node and relation types leads to complex and rich semantics. Efforts for modeling com…
Capturing Context-Aware Route Choice Semantics for Trajectory Representation Learning
Ji Cao, Yu Wang, Tongya Zheng +6
Trajectory representation learning (TRL) aims to encode raw trajectory data into low-dimensional embeddings for downstream tasks such as travel time estimation, mobility prediction…
VeriWeb: Verifiable Long-Chain Web Benchmark for Agentic Information-Seeking
Shunyu Liu, Minghao Liu, Huichi Zhou +31
Recent advances have showcased the extraordinary capabilities of Large Language Model (LLM) agents in tackling web-based information-seeking tasks. However, existing efforts mainly…
Bi-level Mean Field: Dynamic Grouping for Large-Scale MARL
Yuxuan Zheng, Yihe Zhou, Feiyang Xu +2
Large-scale Multi-Agent Reinforcement Learning (MARL) often suffers from the curse of dimensionality, as the exponential growth in agent interactions significantly increases comput…
SeRL: Self-Play Reinforcement Learning for Large Language Models with Limited Data
Wenkai Fang, Shunyu Liu, Yang Zhou +5
Recent advances have demonstrated the effectiveness of Reinforcement Learning (RL) in improving the reasoning capabilities of Large Language Models (LLMs). However, existing works…
Adaptive Location Hierarchy Learning for Long-Tailed Mobility Prediction
Yu Wang, Junshu Dai, Yuchen Ying +4
Human mobility prediction is crucial for applications ranging from location-based recommendations to urban planning, which aims to forecast users' next location visits based on his…
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
Jie Yang, Yuwen Wang, Kaixuan Chen +6
Interpretable Graph Neural Networks (GNNs) aim to reveal the underlying reasoning behind model predictions, attributing their decisions to specific subgraphs that are informative.…
Parallelized Planning-Acting for Efficient LLM-based Multi-Agent Systems in Minecraft
Yaoru Li, Shunyu Liu, Tongya Zheng +2
Recent advancements in Large Language Model~(LLM)-based Multi-Agent Systems (MAS) have demonstrated remarkable potential for tackling complex decision-making tasks. However, existi…