25 citations · 35 across the 8 of their papers we have counts for
10 papers
DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression
DeepSeek-AI, :, Anyi Xu +585
The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation…
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…
DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
DeepSeek-AI, Aixin Liu, Aoxue Mei +260
We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 ar…
An Accelerated Mixed Weighted-Unweighted MMSE Approach for MU-MIMO Beamforming
Xi Gao, Akang Wang, Junkai Zhang +2
Precoding design based on weighted sum-rate (WSR) maximization is a fundamental problem in downlink multi-user multiple-input multiple-output (MU-MIMO) systems. While the weighted…
Organ-Agents: Virtual Human Physiology Simulator via LLMs
Rihao Chang, He Jiao, Weizhi Nie +13
Recent advances in large language models (LLMs) have enabled new possibilities in simulating complex physiological systems. We introduce Organ-Agents, a multi-agent framework that…
Solving Quadratic Programs via Deep Unrolled Douglas-Rachford Splitting
Jinxin Xiong, Xi Gao, Linxin Yang +3
Convex quadratic programs (QPs) are fundamental to numerous applications, including finance, engineering, and energy systems. Among the various methods for solving them, the Dougla…
A Learning-Based Inexact ADMM for Solving Quadratic Programs
Xi Gao, Jinxin Xiong, Linxin Yang +3
Convex quadratic programs (QPs) constitute a fundamental computational primitive across diverse domains including financial optimization, control systems, and machine learning. The…
IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs
Xi Gao, Jinxin Xiong, Akang Wang +3
Solving constrained nonlinear programs (NLPs) is of great importance in various domains such as power systems, robotics, and wireless communication networks. One widely used approa…
Differentiable Combinatorial Losses through Generalized Gradients of Linear Programs
Xi Gao, Han Zhang, Aliakbar Panahi +1
When samples have internal structure, we often see a mismatch between the objective optimized during training and the model's goal during inference. For example, in sequence-to-seq…
Approximation Capabilities of Neural ODEs and Invertible Residual Networks
Han Zhang, Xi Gao, Jacob Unterman +1
Neural ODEs and i-ResNet are recently proposed methods for enforcing invertibility of residual neural models. Having a generic technique for constructing invertible models can open…