4 citations · 6 across the 9 of their papers we have counts for
9 papers
An Empirical Study of Training Pixel-Space Text-to-Image Diffusion Models
Dengyang Jiang, Ruoyi Du, Zhennan Chen +10
This paper investigates an increasingly important topic in generative modeling: pixel-space diffusion models. Although numerous studies have explored this topic, most focus on smal…
Z-Reward: Beyond Scalar Rewards by Internalizing Reasoning into Score Distributions
Xin Jin, Huanqia Cai, Zhen Li +9
Reward models are central to text-to-image post-training, but visual preference is subjective and better represented as a distribution over rubric scores than as a deterministic sc…
Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer
Image Team, Huanqia Cai, Sihan Cao +21
The landscape of high-performance image generation models is currently dominated by proprietary systems, such as Nano Banana Pro and Seedream 4.0. Leading open-source alternatives,…
MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models
Huanqia Cai, Yijun Yang, Winston Hu
IQ testing has served as a foundational methodology for evaluating human cognitive capabilities, deliberately decoupling assessment from linguistic background, language proficiency…
System-2 Mathematical Reasoning via Enriched Instruction Tuning
Huanqia Cai, Yijun Yang, Zhifeng Li
Solving complex mathematical problems via system-2 reasoning is a natural human skill, yet it remains a significant challenge for current large language models (LLMs). We identify…
Embedding Self-Correction as an Inherent Ability in Large Language Models for Enhanced Mathematical Reasoning
Kuofeng Gao, Huanqia Cai, Qingyao Shuai +2
Accurate mathematical reasoning with Large Language Models (LLMs) is crucial in revolutionizing domains that heavily rely on such reasoning. However, LLMs often encounter difficult…
TransMatting: Tri-token Equipped Transformer Model for Image Matting
Huanqia Cai, Fanglei Xue, Lele Xu +1
Image matting aims to predict alpha values of elaborate uncertainty areas of natural images, like hairs, smoke, and spider web. However, existing methods perform poorly when faced…
TransMatting: Enhancing Transparent Objects Matting with Transformers
Huanqia Cai, Fanglei Xue, Lele Xu +1
Image matting refers to predicting the alpha values of unknown foreground areas from natural images. Prior methods have focused on propagating alpha values from known to unknown re…
NTIRE 2021 Multi-modal Aerial View Object Classification Challenge
Jerrick Liu, Nathan Inkawhich, Oliver Nina +30
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR. This challenge is comp…