4 citations · 10 across the 14 of their papers we have counts for
15 papers
SciTrace: Trajectory-Aware Safety Reasoning for Scientific Discovery Agents
Tanush Swaminathan, Runmin Jiang, Letian Zhang +1
LLM-based scientific agents have shown strong capacity for autonomous research, yet their safety layers remain structurally divorced from core reasoning: they inspect pipeline outp…
Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective
Jingyang Ou, Jiaqi Han, Minkai Xu +5
Reinforcement Learning (RL) has proven highly effective for autoregressive language models, but adapting these methods to diffusion large language models (dLLMs) presents fundament…
Generative Modeling Enables Molecular Structure Retrieval from Coulomb Explosion Imaging
Xiang Li, Till Jahnke, Rebecca Boll +12
Capturing the structural changes that molecules undergo during chemical reactions in real space and time is a long-standing dream and an essential prerequisite for understanding an…
RFG: Self-Improving Diffusion Large Language Models with Reward-Free Guidance
Tianlang Chen, Minkai Xu, Jure Leskovec +1
Diffusion Large Language Models (dLLMs) have shown strong reasoning capabilities, yet further improving them typically requires costly post-training with additional data and superv…
CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
Jiaqi Han, Haotian Ye, Puheng Li +3
Diffusion-based generative models have become dominant generators of high-fidelity images and videos but remain limited by their computationally expensive inference procedures. Exi…
Divergence Minimization Preference Optimization for Diffusion Model Alignment
Binxu Li, Minkai Xu, Jiaqi Han +2
Diffusion models have achieved remarkable success in generating realistic and versatile images from text prompts. Inspired by the recent advancements of language models, there is a…
Discrete Diffusion Trajectory Alignment via Stepwise Decomposition
Jiaqi Han, Austin Wang, Minkai Xu +6
Discrete diffusion models have demonstrated great promise in modeling various sequence data, ranging from human language to biological sequences. Inspired by the success of RL in l…
RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models
Valter Hudovernik, Minkai Xu, Juntong Shi +4
Real-world databases are predominantly relational, comprising multiple interlinked tables that contain complex structural and statistical dependencies. Learning generative models o…
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…