works on

From the 1 of 14 linked papers with an AI index.

collaborators

14 papers

cs.CV2026

AVCap: Reinforcing Audio-Video Joint Caption with Detail-Aware Reward

Mingyang Wu, Kaituo Feng, Bohao Li +3

Detailed audio-video joint captioning is essential for multimodal video understanding and generation. However, prior works are constrained by three main limitations: (1) the scarci…

cs.CV2026

Visko Orbis 1.0: A Live Model for Real-Time Interactive Long Video Generation

Xiangbo Gao, Siyuan Yang, Ping He +12

Visko Orbis 1.0 is a live model that generates long videos in real time, letting users change prompts on the fly while preserving subject, scene, and style consistency across hour‑…

cs.CL2026

When Knowledge Is Not Free: Cost-Aware Evidence Selection in Retrieval-Augmented Generation

Mingyan Wu, Han Yang, Omer Ben-Porat +1

Retrieval-Augmented Generation (RAG) typically assumes that external knowledge is free, but many high-quality sources are paywalled, licensed, restricted, or otherwise costly to ac…

cs.CV2026

CV-Arena: An Open Benchmark for Instructional Computer Vision Problem Solving with Human-AI Collaborative Preferences

Fangzhou Lin, Peiran Li, Lingyu Xu +12

Instruction-guided image editing is becoming a general interface for visual work, yet existing benchmarks still focus largely on narrow appearance edits and do not fully capture th…

cs.CV2026

4KLSDB: A Large-Scale Dataset for 4K Image Restoration and Generation

Zihao Zhu, Kuan-Ru Huang, Zhaoming Xu +6

High-resolution datasets are essential for advancing super-resolution (SR) and text-to-image (T2I) diffusion research. However, current publicly available datasets lack both the na…

cs.CV2026

VEFX-Bench: A Holistic Benchmark for Generic Video Editing and Visual Effects

Xiangbo Gao, Sicong Jiang, Bangya Liu +12

As AI-assisted video creation becomes increasingly practical, instruction-guided video editing has become essential for refining generated or captured footage to meet professional…