activity
20232026
collaborators

7 papers

cs.MA2026

Skill Description Deception Attack against Task Routing in Internet of Agents

Jiayi He, Xiaofeng Luo, Jiawen Kang +3

A new paradigm, Internet of Agents (IoA), is transforming networked systems into LLM-driven service networks, where heterogeneous agents collaborate through task routing based on t…

cs.CL2026

Prototype-Regularized Federated Learning for Cross-Domain Aspect Sentiment Triplet Extraction

Zongming Cai, Jianhang Tang, Zhenyong Zhang +3

Aspect Sentiment Triplet Extraction (ASTE) aims to extract all sentiment triplets of aspect terms, opinion terms, and sentiment polarities from a sentence. Existing methods are typ…

cs.AI2025

LMM-Incentive: Large Multimodal Model-based Incentive Design for User-Generated Content in Web 3.0

Jinbo Wen, Jiawen Kang, Linfeng Zhang +5

Web 3.0 represents the next generation of the Internet, which is widely recognized as a decentralized ecosystem that focuses on value expression and data ownership. By leveraging b…

cs.AI2025

Inspire or Predict? Exploring New Paradigms in Assisting Classical Planners with Large Language Models

Wenkai Yu, Jianhang Tang, Yang Zhang +4

Addressing large-scale planning problems has become one of the central challenges in the planning community, deriving from the state-space explosion caused by growing objects and a…

cs.NI2025

HybridRAG-based LLM Agents for Low-Carbon Optimization in Low-Altitude Economy Networks

Jinbo Wen, Cheng Su, Jiawen Kang +5

Low-Altitude Economy Networks (LAENets) are emerging as a promising paradigm to support various low-altitude services through integrated air-ground infrastructure. To satisfy low-l…

cs.NI2025

Diffusion-based Dynamic Contract for Federated AI Agent Construction in Mobile Metaverses

Jinbo Wen, Jiawen Kang, Yang Zhang +5

Mobile metaverses are envisioned as a transformative digital ecosystem that delivers immersive, intelligent, and ubiquitous services through mobile devices. Driven by Large Languag…

cs.CV2023

Long-Tailed Classification Based on Coarse-Grained Leading Forest and Multi-Center Loss

Jinye Yang, Ji Xu, Di Wu +3

Long-tailed (LT) classification is an unavoidable and challenging problem in the real world. Most existing long-tailed classification methods focus only on solving the class-wise i…