activity
20242026
most citedMol-R1: Towards Explicit Long-CoT Reasoning in Molecule Discovery

1 citations · 1 across the 6 of their papers we have counts for

collaborators

11 papers

cs.CV2026

StreamMeCo: Long-Term Agent Memory Compression for Efficient Streaming Video Understanding

Junxi Wang, Te Sun, Jiayi Zhu +6

Vision agent memory has shown remarkable effectiveness in streaming video understanding. However, storing such memory for videos incurs substantial memory overhead, leading to high…

cs.CR2026

AttnDiff: Attention-based Differential Fingerprinting for Large Language Models

Haobo Zhang, Zhenhua Xu, Junxian Li +3

Protecting the intellectual property of open-weight large language models (LLMs) requires verifying whether a suspect model is derived from a victim model despite common laundering…

cs.CV2026

PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Tasks

Junxian Li, Kai Liu, Leyang Chen +7

Unified multimodal models (UMMs) have shown impressive capabilities in generating natural images and supporting multimodal reasoning. However, their potential in supporting compute…

cs.CV2025

S-MLLM: Boosting Spatial Reasoning Capability of MLLMs for 3D Visual Grounding with Structural Guidance

Beining Xu, Siting Zhu, Zhao Jin +2

3D Visual Grounding (3DVG) focuses on locating objects in 3D scenes based on natural language descriptions, serving as a fundamental task for embodied AI and robotics. Recent advan…

cs.AI2025

Faithful-First Reasoning, Planning, and Acting for Multimodal LLMs

Junxian Li, Xinyue Xu, Sai Ma +2

Multimodal Large Language Models (MLLMs) frequently suffer from unfaithfulness, generating reasoning chains that drift from visual evidence or contradict final predictions. We prop…

cs.AI2025

AI for Service: Proactive Assistance with AI Glasses

Zichen Wen, Yiyu Wang, Chenfei Liao +10

In an era where AI is evolving from a passive tool into an active and adaptive companion, we introduce AI for Service (AI4Service), a new paradigm that enables proactive and real-t…