3 papers
cs.CV2025
The Scalability of Simplicity: Empirical Analysis of Vision-Language Learning with a Single Transformer
Weixian Lei, Jiacong Wang, Haochen Wang +4
This paper introduces SAIL, a single transformer unified multimodal large language model (MLLM) that integrates raw pixel encoding and language decoding within a singular architect…
cs.CV2025
UVE: Are MLLMs Unified Evaluators for AI-Generated Videos?
Yuanxin Liu, Rui Zhu, Shuhuai Ren +4
With the rapid growth of video generative models (VGMs), it is essential to develop reliable and comprehensive automatic metrics for AI-generated videos (AIGVs). Existing methods e…
cs.CV2024
World to Code: Multi-modal Data Generation via Self-Instructed Compositional Captioning and Filtering
Jiacong Wang, Bohong Wu, Haiyong Jiang +4
Recent advances in Vision-Language Models (VLMs) and the scarcity of high-quality multi-modal alignment data have inspired numerous researches on synthetic VLM data generation. The…