4 citations · 4 across the 4 of their papers we have counts for
4 papers
MILR: Improving Multimodal Image Generation via Test-Time Latent Reasoning
Yapeng Mi, Yanpeng Zhao, Hengli Li +6
Reasoning-augmented machine learning systems have shown improved performance in various domains, including image generation. However, existing reasoning-based methods for image gen…
Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space
Hengli Li, Chenxi Li, Tong Wu +8
Reasoning ability, a core component of human intelligence, continues to pose a significant challenge for Large Language Models (LLMs) in the pursuit of AGI. Although model performa…
Aligner: One Global Token is Worth Millions of Parameters When Aligning Large Language Models
Zhou Ziheng, Yingnian Wu, Song-Chun Zhu +1
We introduce Aligner, a novel Parameter-Efficient Fine-Tuning (PEFT) method for aligning multi-billion-parameter-sized Large Language Models (LLMs). Aligner employs a unique design…
Neural-Symbolic Recursive Machine for Systematic Generalization
Qing Li, Yixin Zhu, Yitao Liang +3
Current learning models often struggle with human-like systematic generalization, particularly in learning compositional rules from limited data and extrapolating them to novel com…