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cs.CV2026

Factuality Matters: When Image Generation and Editing Meet Structured Visuals

Le Zhuo, Songhao Han, Yuandong Pu +8

While modern visual generation models excel at creating aesthetically pleasing natural images, they struggle with producing or editing structured visuals like charts, diagrams, and…

cs.CV2026

PICABench: How Far Are We from Physically Realistic Image Editing?

Yuandong Pu, Le Zhuo, Songhao Han +10

Image editing has achieved remarkable progress recently. Modern editing models could already follow complex instructions to manipulate the original content. However, beyond complet…

cs.CV2025

Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency

Hongyu Li, Songhao Han, Yue Liao +4

Understanding real-world videos with complex semantics and long temporal dependencies remains a fundamental challenge in computer vision. Recent progress in multimodal large langua…

cs.CV2024

VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection

Songhao Han, Wei Huang, Hairong Shi +7

The advancement of Large Vision Language Models (LVLMs) has significantly improved multimodal understanding, yet challenges remain in video reasoning tasks due to the scarcity of h…

cs.CV2024

LLMs as Visual Explainers: Advancing Image Classification with Evolving Visual Descriptions

Songhao Han, Le Zhuo, Yue Liao +1

Vision-language models (VLMs) offer a promising paradigm for image classification by comparing the similarity between images and class embeddings. A critical challenge lies in craf…