activity
20242026
collaborators

16 papers

cs.CV2026

SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models

Hongxiang Li, Hongxu Chen, Chenyang Zhu +5

Multimodal Large Language Models (MLLMs) have achieved remarkable success in visual understanding but remain constrained in visual generation due to the fundamental feature discrep…

cs.CL2026

Preference-Aware Rubric Learning for Personalized Evaluation

Yilun Qiu, Xiaoyan Zhao, Yang Zhang +7

As Large Language Models (LLMs) evolve from general-purpose assistants to user-centric agents, personalization has become central to aligning model behavior with individual prefere…

cs.CV2026

AgentCVR: Active Multi-Agent Cross-Video Reasoning via Script-Simulated Reinforcement Learning

Yilun Qiu, Jiahe Wang, Cilin Yan +4

Cross-Video Reasoning (CVR) has emerged as a critical frontier in multimodal intelligence, requiring models to retrieve, align, and aggregate evidence distributed across multiple v…

cs.CV2026

VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation

Yiming Zhao, Yu Zeng, Wenxuan Huang +11

Large Vision-Language Models (LVLMs) have shown significant progress in video understanding, yet they face substantial challenges in tasks requiring precise spatiotemporal localiza…

cs.CV2026

Improving the Reasoning of Multi-Image Grounding in MLLMs via Reinforcement Learning

Bob Zhang, Haoran Li, Tao Zhang +5

Multimodal Large Language Models (MLLMs) perform well in single-image visual grounding but struggle with real-world tasks that demand cross-image reasoning and multi-modal instruct…

cs.CV2026

GIR-Bench: Versatile Benchmark for Generating Images with Reasoning

Hongxiang Li, Yaowei Li, Bin Lin +7

Unified multimodal models integrate the reasoning capacity of large language models with both image understanding and generation, showing great promise for advanced multimodal inte…