3 papers
cs.LG2026
Meta-TTRL: A Metacognitive Framework for Self-Improving Test-Time Reinforcement Learning in Unified Multimodal Models
Lit Sin Tan, Junzhe Chen, Xiaolong Fu +5
Existing test-time scaling (TTS) methods for unified multimodal models (UMMs) in text-to-image (T2I) generation primarily rely on search or sampling strategies that produce only in…
cs.CV2025
RePainter: Empowering E-commerce Object Removal via Spatial-matting Reinforcement Learning
Zipeng Guo, Lichen Ma, Xiaolong Fu +13
In web data, product images are central to boosting user engagement and advertising efficacy on e-commerce platforms, yet the intrusive elements such as watermarks and promotional…
cs.CV2024
CharGen: High Accurate Character-Level Visual Text Generation Model with MultiModal Encoder
Lichen Ma, Tiezhu Yue, Pei Fu +4
Recently, significant advancements have been made in diffusion-based visual text generation models. Although the effectiveness of these methods in visual text rendering is rapidly…