activity
20242026
collaborators

7 papers

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

hep-ex2025

Observation and branching fraction measurement of the decay

M. Ablikim, M. N. Achasov, P. Adlarson +612

The first observation of the decays and is reported using $J\…

stat.ME2025

Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations

Mengbing Li, Briana Stephenson, Zhenke Wu

Dietary patterns synthesize multiple related diet components, which can be used by nutrition researchers to examine diet-disease relationships. Latent class models (LCMs) have been…

stat.ME2025

Incorporating Auxiliary Variables to Improve the Efficiency of Time-Varying Treatment Effect Estimation

Jieru Shi, Zhenke Wu, Walter Dempsey

Contextual sensing and delivery of digital interventions to improve health outcomes have gained significant traction in behavioral and psychiatric studies. Micro-randomized trials…

stat.ML2025

Doubly Inhomogeneous Reinforcement Learning

Liyuan Hu, Mengbing Li, Chengchun Shi +2

This paper studies reinforcement learning (RL) in doubly inhomogeneous environments under temporal non-stationarity and subject heterogeneity. In a number of applications, it is co…

stat.ML2025

Testing Stationarity and Change Point Detection in Reinforcement Learning

Mengbing Li, Chengchun Shi, Zhenke Wu +1

We consider offline reinforcement learning (RL) methods in possibly nonstationary environments. Many existing RL algorithms in the literature rely on the stationarity assumption th…