collaborators

5 papers

cs.CV2026

Detecting AI-Generated Video: A Vision-Language Dual-View Survey

Dylan Xinming Hou, Juntian Zhang, Xu Gu +5

The evolving realism of AI-generated Videos (AIGC-V) is rapidly rendering traditional artifact-centric detection insufficient, necessitating a paradigm shift from low-level inspect…

cs.CL2026

AI Security Beyond Core Domains: Resume Screening as a Case Study of Adversarial Vulnerabilities in Specialized LLM Applications

Honglin Mu, Jinghao Liu, Kaiyang Wan +4

Large Language Models (LLMs) excel at text comprehension and generation, making them ideal for automated tasks like code review and content moderation. However, our research identi…

cs.AI2026

Breaking the Martingale Curse: Multi-Agent Debate via Asymmetric Cognitive Potential Energy

Yuhan Liu, Juntian Zhang, Yichen Wu +4

Multi-Agent Debate (MAD) has emerged as a promising paradigm for enhancing large language model reasoning. However, recent work reveals a limitation:standard MAD cannot improve bel…

cs.SI2025

From Individuals to Crowds: Dual-Level Public Response Prediction in Social Media

Jinghui Zhang, Kaiyang Wan, Longwei Xu +3

Public response prediction is critical for understanding how individuals or groups might react to specific events, policies, or social phenomena, making it highly valuable for cris…

cs.CL2025

Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching

Mingzhe Li, Jing Xiang, Qishen Zhang +2

Knowledge distillation typically involves transferring knowledge from a Large Language Model (LLM) to a Smaller Language Model (SLM). However, in tasks such as text matching, fine-…