activity
20242026
collaborators

9 papers

cs.RO2026

Towards Ultrafast Depth Sensing Via Active Event-based Stereo Vision

Jianing Li, Yunjian Zhang, Haiqian Han +2

Conventional frame-based imaging for active stereo systems has encountered major challenges in fast-motion scenarios. However, how to design a novel paradigm for ultrafast depth se…

cs.CV2026

Beyond SFT-to-RL: Pre-alignment via Black-Box On-Policy Distillation for Multimodal RL

Sudong Wang, Weiquan Huang, Xiaomin Yu +9

The standard post-training recipe for large multimodal models (LMMs) applies supervised fine-tuning (SFT) on curated demonstrations followed by reinforcement learning with verifiab…

cs.CV2026

EventFlash: Towards Efficient MLLMs for Event-Based Vision

Shaoyu Liu, Jianing Li, Guanghui Zhao +4

Event-based multimodal large language models (MLLMs) enable robust perception in high-speed and low-light scenarios, addressing key limitations of frame-based MLLMs. However, curre…

cs.AI2026

Resource-Efficient Reinforcement for Reasoning Large Language Models via Dynamic One-Shot Policy Refinement

Yunjian Zhang, Sudong Wang, Yang Li +5

Large language models (LLMs) have exhibited remarkable performance on complex reasoning tasks, with reinforcement learning under verifiable rewards (RLVR) emerging as a principled…

cs.CV2025

EventBench: Towards Comprehensive Benchmarking of Event-based MLLMs

Shaoyu Liu, Jianing Li, Guanghui Zhao +2

Multimodal large language models (MLLMs) have made significant advancements in event-based vision, yet the comprehensive evaluation of their capabilities within a unified benchmark…

cs.AI2025

SpatialBench: Benchmarking Multimodal Large Language Models for Spatial Cognition

Peiran Xu, Sudong Wang, Yao Zhu +3

Spatial cognition is fundamental to real-world multimodal intelligence, allowing models to effectively interact with the physical environment. While multimodal large language model…

cs.CV2025

Bridging the Gap Between Ideal and Real-world Evaluation: Benchmarking AI-Generated Image Detection in Challenging Scenarios

Chunxiao Li, Xiaoxiao Wang, Meiling Li +5

With the rapid advancement of generative models, highly realistic image synthesis has posed new challenges to digital security and media credibility. Although AI-generated image de…

cs.CV2025

Towards Understanding How Knowledge Evolves in Large Vision-Language Models

Sudong Wang, Yunjian Zhang, Yao Zhu +4

Large Vision-Language Models (LVLMs) are gradually becoming the foundation for many artificial intelligence applications. However, understanding their internal working mechanisms h…

cs.CV2024

EventGPT: Event Stream Understanding with Multimodal Large Language Models

Shaoyu Liu, Jianing Li, Guanghui Zhao +5

Event cameras record visual information as asynchronous pixel change streams, excelling at scene perception under unsatisfactory lighting or high-dynamic conditions. Existing multi…