From the 1 of 19 linked papers with an AI index.
2 citations · 3 across the 12 of their papers we have counts for
11 papers · 1 filter
A Comprehensive Ecosystem for Open-Domain Customized Video Generation
Jingxu Zhang, Yuqian Hong, Daneul Kim +6
Recent progress in video generation has shown impressive visual synthesis capabilities. However, open-domain customized video generation remains limited by the lack of large-scale,…
Covering Human Action Space for Computer Use: Data Synthesis and Benchmark
Miaosen Zhang, Xiaohan Zhao, Zhihong Tan +14
Computer-use agents (CUAs) automate on-screen work, as illustrated by GPT-5.4 and Claude. Yet their reliability on complex, low-frequency interactions is still poor, limiting user…
AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation
Ziwei Zhou, Zeyuan Lai, Rui Wang +6
Text-to-Audio-Video (T2AV) generation is rapidly becoming a core interface for media creation, yet its evaluation remains fragmented. Existing benchmarks largely assess audio and v…
High-Fidelity Text-to-Image Generation from Pre-Trained Vision-Language Models via Distribution-Conditioned Diffusion Decoding
Ji Woo Hong, Hee Suk Yoon, Gwanhyeong Koo +5
Recent large-scale vision-language models (VLMs) have shown remarkable text-to-image generation capabilities, yet their visual fidelity remains constrained by the discrete image to…
LLM2CLIP: Powerful Language Model Unlocks Richer Cross-Modality Representation
Weiquan Huang, Aoqi Wu, Yifan Yang +10
CLIP is a seminal multimodal model that maps images and text into a shared representation space through contrastive learning on billions of image-caption pairs. Inspired by the rap…
Video-in-the-Loop: Span-Grounded Long Video QA with Interleaved Reasoning
Chendong Wang, Donglin Bai, Yifan Yang +11
We present \emph{Video-in-the-Loop} (ViTL), a two-stage long-video QA framework that preserves a fixed token budget by first \emph{localizing} question-relevant interval(s) with a…