7 papers · 1 filter
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…
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…
LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation
Hongchen Li, Bohao Wang, Jingbang Chen +5
Large language models (LLMs) have recently emerged as powerful backbones for recommender systems by reformulating recommendation as a token-level generation task. Despite their pro…
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…
Informative Graph Structure Learning
Shen Han, Zhiyao Zhou, Jiawei Chen +6
The quality of graph-structured data is fundamental to the success of modern graph analysis techniques such as Graph Neural Networks (GNNs). However, real-world graph data is often…
Adaptive Forensic Feature Refinement via Intrinsic Importance Perception
Jiazhen Yang, Junjun Zheng, Kejia Chen +5
With the rapid development of generative models and multimodal content editing technologies, the key challenge in synthetic image detection (SID) lies in cross-distribution general…
SpatCode: Rotary-based Unified Encoding Framework for Efficient Spatiotemporal Vector Retrieval
Bingde Hu, Enhao Pan, Wanjing Zhou +3
Spatiotemporal vector retrieval has emerged as a critical paradigm in modern information retrieval, enabling efficient access to massive, heterogeneous data that evolve over both t…