collaborators

11 papers

cs.CV2026

Human-Centric Image Captioning with Subject-Centered Spatial Understanding

Bozhou Li, Jiahang Zhang, Yue Ding +11

While multimodal large language models (MLLMs) achieve remarkable performance on generic image captioning, they frequently suffer from structural hallucinations in human-centric sc…

cs.AI2026

ABot-AgentOS: A General Robotic Agent OS with Lifelong Multi-modal Memory

Jiayi Tian, Shiao Liu, Yuting Xu +30

Recent VLM and VLA systems have improved robotic perception and action prediction, yet long-horizon embodied agents still require a general runtime layer for reasoning, memory, too…

cs.AI2026

CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents

Zhanbo Hua, Yifan Yao, Weihao Xie +14

While recent LLM-based terminal agents have demonstrated promising capabilities, the scarcity of high-quality, executable training data remains a critical bottleneck. Existing synt…

cs.CV2026

CapRiCorn-1K: A Comprehensive Benchmark for Video Captioning and Subject Referential Consistency Across Temporal Scales

Xinlong Chen, Jiafu Tang, Yue Ding +12

Accurate and comprehensive video captions with consistent subject references are critical for downstream understanding and generation tasks. However, few existing benchmarks can ob…

cs.AI2026

SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision

Yuxuan Liu, Zhaochen Su, Lingyun Xie +11

Agent skills are procedural artifacts that enable LLM agents to execute workflows, verify constraints, and recover from failures. Existing self-evolving methods refine skills using…

cs.CL2026

LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning

Yifan Dai, Zhenhua Wu, Bohan Zeng +18

Joint audio-visual reasoning is essential for omnimodal understanding, yet current multimodal large language models (MLLMs) still struggle when reasoning requires fine-grained evid…

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.CV2026

Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling

Xuehai Bai, Yang Shi, Yi-Fan Zhang +7

Recent image editing models have achieved remarkable progress in instruction following, multimodal understanding, and complex visual editing. However, existing benchmarks often fai…

cs.CV2026

Semantic Routing: Exploring Multi-Layer LLM Feature Weighting for Diffusion Transformers

Bozhou Li, Yushuo Guan, Haolin Li +7

Recent DiT-based text-to-image models increasingly adopt LLMs as text encoders, yet text conditioning remains largely static and often utilizes only a single LLM layer, despite pro…

cs.CL2026

OmniSIFT: Modality-Asymmetric Token Compression for Efficient Omni-modal Large Language Models

Yue Ding, Yiyan Ji, Jungang Li +12

Omni-modal Large Language Models (Omni-LLMs) have demonstrated strong capabilities in audio-video understanding tasks. However, their reliance on long multimodal token sequences le…

cs.AI2025

OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs

Caorui Li, Yu Chen, Yiyan Ji +40

Recent advances in multimodal large language models (MLLMs) have demonstrated substantial potential in video understanding. However, existing benchmarks fail to comprehensively eva…