4 citations · 10 across the 14 of their papers we have counts for
7 papers · 1 filter
Geometric Trajectory Diffusion Models
Jiaqi Han, Minkai Xu, Aaron Lou +2
Generative models have shown great promise in generating 3D geometric systems, which is a fundamental problem in many natural science domains such as molecule and protein design. H…
Trans4D: Realistic Geometry-Aware Transition for Compositional Text-to-4D Synthesis
Bohan Zeng, Ling Yang, Siyu Li +9
Recent advances in diffusion models have demonstrated exceptional capabilities in image and video generation, further improving the effectiveness of 4D synthesis. Existing 4D gener…
-PO: Generalizing Preference Optimization with -divergence Minimization
Jiaqi Han, Mingjian Jiang, Yuxuan Song +2
Preference optimization has made significant progress recently, with numerous methods developed to align language models with human preferences. This paper introduces -divergenc…
Energy-Based Diffusion Language Models for Text Generation
Minkai Xu, Tomas Geffner, Karsten Kreis +5
Despite remarkable progress in autoregressive language models, alternative generative paradigms beyond left-to-right generation are still being actively explored. Discrete diffusio…
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
Juntong Shi, Minkai Xu, Harper Hua +3
Synthesizing high-quality tabular data is an important topic in many data science tasks, ranging from dataset augmentation to privacy protection. However, developing expressive gen…
SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction
Ling Yang, Zhaochen Yu, Tianjun Zhang +4
Large language models (LLMs) like GPT-4, DeepSeek-R1, and ReasonFlux have shown significant improvements in various reasoning tasks. However, smaller LLMs still struggle with compl…
TFG: Unified Training-Free Guidance for Diffusion Models
Haotian Ye, Haowei Lin, Jiaqi Han +6
Given an unconditional diffusion model and a predictor for a target property of interest (e.g., a classifier), the goal of training-free guidance is to generate samples with desira…