activity
20212026
most citedReal-time intelligent big data processing: technology, platform, and applications

68 citations · 150 across the 32 of their papers we have counts for

collaborators

37 papers

cs.CR2026

CryptoFlowBench: Benchmarking Multi-Hop Reasoning on Blockchains for Cryptocurrency Fund Tracing

Runang He, Tongya Zheng, Jing Cao +7

Pseudonymous accounts and complex smart-contract ecosystems substantially hinder the tracing of illicit cryptocurrency fund flows. Existing Graph Neural Networks (GNNs) have achiev…

cs.AI2026

GraphCert: Bootstrap Agentic Graph Reasoning with Certified Evidence Rubrics

Weiqi Jiang, Yuchen Ying, Rui Wang +5

Graph agents extend large language models (LLMs) with the ability to actively explore and reason over knowledge graphs through multi-step interactions with graph tools. However, tr…

cs.LG2026

CodeTS: Verifiable Text-to-Time Series Generation via Executable Code

Xudong Yuan, Shunyu Liu, Tongya Zheng +3

Text-to-Time Series Generation (Text-to-TS) provides a promising paradigm for synthesizing time series from natural language, enabling scenario-specific generation when real observ…

cs.IR2026

Making Collaborative Signals Count: Graph-Aware Large Language Models for Sequential Recommendation

Fenglin Yan, Bohao Wang, Jian Zhang +5

Large language models (LLMs) have been widely adopted as backbones for recommender systems. However, their language-centric pretraining makes it difficult to capture collaborative…

cs.CR2026

Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection

Runang He, Tongya Zheng, Huiling Peng +6

Ever-evolving transaction patterns have significantly hindered anomaly detection on emerging cryptocurrency blockchains due to the vast number of addresses and diverse anomalous be…

cs.AI2026

GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning

Yuchen Ying, Weiqi Jiang, Tongya Zheng +4

Knowledge graphs provide structured and reliable information for many real-world applications, motivating increasing interest in combining large language models (LLMs) with graph-b…

cs.AI2026

Physics-informed Diffusion Generation for Geomagnetic Map Interpolation

Wenda Li, Tongya Zheng, Kaixuan Chen +8

Geomagnetic map interpolation aims to infer unobserved geomagnetic data at spatial points, yielding critical applications in navigation and resource exploration. However, existing…

cs.AI2025

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…

cs.IR2025

Tree of Preferences for Diversified Recommendation

Hanyang Yuan, Ning Tang, Tongya Zheng +7

Diversified recommendation has attracted increasing attention from both researchers and practitioners, which can effectively address the homogeneity of recommended items. Existing…

cs.LG2025

Dual-branch Spatial-Temporal Self-supervised Representation for Enhanced Road Network Learning

Qinghong Guo, Yu Wang, Ji Cao +5

Road network representation learning (RNRL) has attracted increasing attention from both researchers and practitioners as various spatiotemporal tasks are emerging. Recent advanced…

cs.AI2025

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…

cs.CL2025

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…

cs.CV2025

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…

cs.CL2025

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…

cs.AI2025

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…

cs.LG2025

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.…

cs.AI2025

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…

cs.CV2025★ 2 cited

Holistic Semantic Representation for Navigational Trajectory Generation

Ji Cao, Tongya Zheng, Qinghong Guo +6

Trajectory generation has garnered significant attention from researchers in the field of spatio-temporal analysis, as it can generate substantial synthesized human mobility trajec…

cs.LG2024

Learning a Mini-batch Graph Transformer via Two-stage Interaction Augmentation

Wenda Li, Kaixuan Chen, Shunyu Liu +3

Mini-batch Graph Transformer (MGT), as an emerging graph learning model, has demonstrated significant advantages in semi-supervised node prediction tasks with improved computationa…

cs.LG2024★ 8 cited

Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks

Yuwen Wang, Shunyu Liu, Tongya Zheng +2

Graph Neural Networks (GNNs) have emerged as a prominent framework for graph mining, leading to significant advances across various domains. Stemmed from the node-wise representati…

cs.LG2024

Curriculum Negative Mining For Temporal Networks

Ziyue Chen, Tongya Zheng, Mingli Song

Temporal networks are effective in capturing the evolving interactions of networks over time, such as social networks and e-commerce networks. In recent years, researchers have pri…

cs.AI2024

Odyssey: Empowering Minecraft Agents with Open-World Skills

Shunyu Liu, Yaoru Li, Kongcheng Zhang +5

Recent studies have delved into constructing generalist agents for open-world environments like Minecraft. Despite the encouraging results, existing efforts mainly focus on solving…

cs.LG2024★ 13 cited

COLA: Cross-city Mobility Transformer for Human Trajectory Simulation

Yu Wang, Tongya Zheng, Yuxuan Liang +2

Human trajectory data produced by daily mobile devices has proven its usefulness in various substantial fields such as urban planning and epidemic prevention. In terms of the indiv…

cs.LG2024

Simple Graph Condensation

Zhenbang Xiao, Yu Wang, Shunyu Liu +3

The burdensome training costs on large-scale graphs have aroused significant interest in graph condensation, which involves tuning Graph Neural Networks (GNNs) on a small condensed…