6 papers
DD-RNO: A Domain-Decomposed Routed Neural Operator for Airfoil Flow Prediction
T. A. Mehta, P. S. Bhati, H. D. Akolekar
Deep learning surrogates for RANS flow prediction around airfoils face two persistent bottlenecks. A single neural architecture cannot simultaneously resolve sharp near-wall bounda…
TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation
Lin Sun, Guangxiang Zhao, Xiaoqi Jian +18
The challenge of reducing the size of Large Language Models (LLMs) while maintaining their performance has gained significant attention. However, existing methods, such as model di…
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…
Large Language Models Badly Generalize across Option Length, Problem Types, and Irrelevant Noun Replacements
Guangxiang Zhao, Saier Hu, Xiaoqi Jian +5
In this paper, we propose a ``Generalization Stress Test" to assess Large Language Models' (LLMs) generalization ability under slight and controlled perturbations, including option…
Router Upcycling: Leveraging Mixture-of-Routers in Mixture-of-Experts Upcycling
Junfeng Ran, Guangxiang Zhao, Yuhan Wu +7
The Mixture-of-Experts (MoE) models have gained significant attention in deep learning due to their dynamic resource allocation and superior performance across diverse tasks. Howev…
Evaluation is All You Need: Strategic Overclaiming of LLM Reasoning Capabilities Through Evaluation Design
Lin Sun, Weihong Lin, Jinzhu Wu +8
Reasoning models represented by the Deepseek-R1-Distill series have been widely adopted by the open-source community due to their strong performance in mathematics, science, progra…