7 citations · 8 across the 13 of their papers we have counts for
13 papers
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…
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…
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,…
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…
Deep-Picard Iteration for Space-time Fractional Diffusion PDEs
Zhijun Zeng, Zhitong Chen, Ling Qin +1
We propose a Deep-Picard iteration framework for high-dimensional nonlinear space-time fractional diffusion equations.The method is based on a nonlinear fractional Feynman--Kac fix…
DGRO: Enhancing LLM Reasoning via Exploration-Exploitation Control and Reward Variance Management
Xuerui Su, Liya Guo, Yue Wang +4
Inference scaling further accelerates Large Language Models (LLMs) toward Artificial General Intelligence (AGI), with large-scale Reinforcement Learning (RL) to unleash long Chain-…
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…
Weak Collocation Regression for Inferring Stochastic Dynamics with Lévy Noise
Liya Guo, Liwei Lu, Zhijun Zeng +2
With the rapid increase of observational, experimental and simulated data for stochastic systems, tremendous efforts have been devoted to identifying governing laws underlying the…
Reconstruction of dynamical systems from data without time labels
Zhijun Zeng, Pipi Hu, Chenglong Bao +2
In this paper, we study the method to reconstruct dynamical systems from data without time labels. Data without time labels appear in many applications, such as molecular dynamics,…
Weak Collocation Regression method: fast reveal hidden stochastic dynamics from high-dimensional aggregate data
Liwei Lu, Zhijun Zeng, Yan Jiang +2
Revealing hidden dynamics from the stochastic data is a challenging problem as randomness takes part in the evolution of the data. The problem becomes exceedingly complex when the…
On Constructing Confidence Region for Model Parameters in Stochastic Gradient Descent via Batch Means
Yi Zhu, Jing Dong
In this paper, we study a simple algorithm to construct asymptotically valid confidence regions for model parameters using the batch means method. The main idea is to cancel out th…
Uncertainty Quantification and Exploration for Reinforcement Learning
YI Zhu, Jing Dong, Henry Lam
We investigate statistical uncertainty quantification for reinforcement learning (RL) and its implications in exploration policy. Despite ever-growing literature on RL applications…
Three Asymptotic Regimes for Ranking and Selection with General Sample Distributions
Jing Dong, Yi Zhu
In this paper, we study three asymptotic regimes that can be applied to ranking and selection (R&S) problems with general sample distributions. These asymptotic regimes are constru…