activity
20242026
collaborators

7 papers

cs.AI2026

Intent-Driven Situation Tracking for User-Centric Multi-Turn Agents

Meiling Tao, Yiling Tao, Peng Wang

User-centric multi-turn agents must act on an evolving task situation shaped by changing user intents, accumulated tool-grounded facts, missing information, and execution constrain…

cs.CL2026

When Search Agents Should Ask: DiscoBench for Clarification-Aware Deep Search

Yiling Tao, Shihan Deng, Meiling Tao +3

Search agents powered by large language models (LLMs) are increasingly used to solve complex information-seeking tasks, requiring multi-step retrieval and reasoning to fulfill user…

cs.AI2026

GroupGuard: A Framework for Modeling and Defending Collusive Attacks in Multi-Agent Systems

Yiling Tao, Xinran Zheng, Shuo Yang +2

While large language model-based agents demonstrate great potential in collaborative tasks, their interactivity also introduces security vulnerabilities. In this paper, we propose…

cs.CV2025

MARS2 2025 Challenge on Multimodal Reasoning: Datasets, Methods, Results, Discussion, and Outlook

Peng Xu, Shengwu Xiong, Jiajun Zhang +125

This paper reviews the MARS2 2025 Challenge on Multimodal Reasoning. We aim to bring together different approaches in multimodal machine learning and LLMs via a large benchmark. We…

cs.CV2025

Aesthetic Image Captioning with Saliency Enhanced MLLMs

Yilin Tao, Jiashui Huang, Huaze Xu +1

Aesthetic Image Captioning (AIC) aims to generate textual descriptions of image aesthetics, becoming a key research direction in the field of computational aesthetics. In recent ye…

cs.CL2025

Decompose, Plan in Parallel, and Merge: A Novel Paradigm for Large Language Models based Planning with Multiple Constraints

Zhengdong Lu, Weikai Lu, Yiling Tao +6

Despite significant advances in Large Language Models (LLMs), planning tasks still present challenges for LLM-based agents. Existing planning methods face two key limitations: heav…

cs.CL2024

Enhancing Commentary Strategies for Imperfect Information Card Games: A Study of Large Language Models in Guandan Commentary

Meiling Tao, Xuechen Liang, Xinyuan Song +4

Recent advancements in large language models (LLMs) have unlocked the potential for generating high-quality game commentary. However, producing insightful and engaging commentary f…