collaborators

10 papers

cs.CV2026

Verus-Insight: Towards Explainable Artifact Detection in AI-Generated Videos

Zhuoran Zhang, Yang Shi, Qixun Wang +11

Recent advances in video generation have made synthetic videos increasingly realistic, placing greater demands on reliable AI-generated video detection. Existing artifact-based det…

cs.CV2026

FocusMem: Factorizing Content, Readout, and Trust in Latent GUI Memory

Zhuoran Zhang, Bowen Li, Jingcheng Ju +5

GUI agents must remember both useful experience from earlier tasks and unfinished progress in the current interaction. Latent memory offers a compact solution by compressing multim…

cs.CV2026

OmniPack: Unified Token Compression for Efficient Omni-modal Large Language Models

Wanshun Su, Yang Shi, Feihu Liu +10

Omni-modal large language models (Omni-LLMs) have achieved remarkable performance on audio-visual understanding tasks, but processing long and highly redundant visual and audio tok…

cs.CV2026

Beacon: Knowing When and How to Perform Agentic Visual Reasoning

Qixun Wang, Yang Shi, Letian Cheng +11

The fundamental goal of agentic visual reasoning is to improve the success rate of multimodal large language models (MLLMs) on complex tasks. We rethink agentic visual reasoning th…

cs.CV2026

RefCaptioner: Multi-Reference Image-Grounded Video Captioning

Tengfei Liu, Yang Shi, Yuran Wang +16

Existing video captioning models generate natural descriptions of video content but cannot explicitly ground local visual elements to multiple reference images. We introduce multi-…

cs.CV2026

KeyFrame-Compass: Towards Comprehensive Evaluation of Keyframe-Conditioned Video Generation

Yuqi Tang, Tengfei Liu, Yizheng Lai +18

Video generation increasingly relies on keyframe-based workflows, where creators specify a sequence of reference images to guide generation. Although recent models support multi-ke…

cs.CV2026

LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV

Tengfei Liu, Yang Shi, Xuanyu Zhu +17

Audio-visual generation is rapidly advancing from short clips to minute-long content, while existing evaluation protocols remain largely confined to short-form settings. Existing b…

cs.CV2026

Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos

Yuqi Tang, Yang Shi, Zhuoran Zhang +21

Recent video generative models have greatly improved the realism of AI-generated videos, yet their outputs still exhibit artifacts such as temporal inconsistencies, structural dist…

cs.AI2025

RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark

Yang Shi, Yuhao Dong, Yue Ding +22

The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question rem…

cs.CV2025

MME-VideoOCR: Evaluating OCR-Based Capabilities of Multimodal LLMs in Video Scenarios

Yang Shi, Huanqian Wang, Wulin Xie +20

Multimodal Large Language Models (MLLMs) have achieved considerable accuracy in Optical Character Recognition (OCR) from static images. However, their efficacy in video OCR is sign…