5 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…
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…