activity
20232026
most citedDeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies

8 citations · 16 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2026

UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective

Xiaoyi Jiang, Jingyuan Li, Yixuan Jiang +4

Existing methods mainly adapt pretrained autoregressive (AR) language models to masked diffusion, whereas we directly adapt them to uniform-noise diffusion, where every token remai…

cs.LG2026

Mean-to-Score Discrete Diffusion: Posterior-Mean Denoisers for Score Entropy

Jingyuan Li, Xiaoyi Jiang, Yixuan Jiang +4

Score Entropy Discrete Diffusion (SEDD) parameterizes discrete reverse processes with unconstrained positive score ratios. While positivity guarantees nonnegative reverse jump rate…

cs.LG2026

OLEDLM: A Unified Language Model for OLED Molecular Design

Fukang Wen, Yuchong Tang, Jingyuan Li +9

The development of organic light-emitting diode (OLED) materials faces the compounded challenges of an astronomically large chemical space, stringent quantum-chemical constraints,…

cs.AI2026

Constant-Target Energy Matching: A Unified Framework for Continuous and Discrete Density Estimation

Zhijun Zeng, Yixuan Jiang, Pipi Hu +1

Density estimation is a central primitive in probabilistic modeling, yet continuous, discrete, and mixed-variable domains are often treated by separate objectives, limiting the abi…

cs.LG2026

Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction

Jingyuan Li, Xiaoyi Jiang, Fukang Wen +5

Discrete diffusion models based on continuous-time Markov chains (CTMCs) have shown strong performance on language and discrete data generation, yet existing approaches typically p…

physics.chem-ph2026

Drifting to Boltzmann: Million-Fold Acceleration in Boltzmann Sampling with Force-Guided Drifting

Pipi Hu

Sampling molecular conformations from the Boltzmann distribution is essential for computational chemistry, but iterative diffusion methods are prohibitively slow. Drifting Models o…

cs.LG2025

Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance

Liya Guo, Zun Wang, Chang Liu +3

The ensemble average of physical properties of molecules is closely related to the distribution of molecular conformations, and sampling such distributions is a fundamental challen…

cs.LG2025★ 2 cited

UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials

Gongbo Zhang, Yanting Li, Renqian Luo +31

Function in natural systems arises from one-dimensional sequences forming three-dimensional structures with specific properties. However, current generative models suffer from crit…

cs.LG2025★ 6 cited

HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model

Mingqian Ma, Guoqing Liu, Chuan Cao +12

Advances in natural language processing and large language models have sparked growing interest in modeling DNA, often referred to as the "language of life". However, DNA modeling…

cs.AI2023★ 8 cited

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies

Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang +89

In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scient…