activity
20242026
collaborators

8 papers

cs.AI2026

AgentPatch: Coarse-to-Fine Weak-Task Repair for Merging Agentic Multimodal Large Language Models

Zibo Shao, Baochen Xiong, Chengdong Xu +6

Agentic multimodal large language models (MLLMs) extend multimodal perception and reasoning with planning, tool use, and interaction in dynamic environments. Yet current models are…

cs.HC2026

Preference-Driven Online Adaptation for Personalized Interaction Initiation in Proactive AI Assistants

Yufeng Wang, Wei Zhang, Zhiquan Wen +5

AI assistants are typically reactive, relying on users to initiate interactions. Proactive assistants go beyond this paradigm by autonomously initiating interactions based on users…

cs.LG2026

A Survey on the Green Development of Large Models: From Resource-Efficient Architectures to Hardware-Software Co-Design

Linhui Xiao, Guiping Cao, Mingyue Guo +6

The rapid expansion of large-scale AI models has led to significant performance breakthroughs across diverse domains, yet it has also raised critical concerns regarding computation…

cs.CV2026

RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios

Tianyi Zhao, Jiawen Xi, Linhui Xiao +4

Visual grounding (VG) localizes target objects in an image from natural-language expressions. In real-world perception, RGB cues often degrade under low illumination and adverse we…

cs.CV2026

BARE: Towards Bias-Aware and Reasoning-Enhanced One-Tower Visual Grounding

Hongbing Li, Linhui Xiao, Zihan Zhao +4

Visual Grounding (VG), which aims to locate a specific region referred to by expressions, is a fundamental yet challenging task in the multimodal understanding fields. While recent…

cs.CV2025

Toward Visual Grounding: A Survey

Linhui Xiao, Xiaoshan Yang, Xiangyuan Lan +2

Visual Grounding, also known as Referring Expression Comprehension and Phrase Grounding, aims to ground the specific region(s) within the image(s) based on the given expression tex…