activity
20242026
collaborators

7 papers

cs.CL2026

TrainBridge: Agentic NPU Training Optimization Guided by GPU Compilation Evidence

Yupeng Chen, Kunxiang Zhao, Xingjian Wang +6

We study how to improve training efficiency on Ascend NPUs. In the NPU training programs we study, framework-level compilation optimizations such as operator fusion are only partia…

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…

cs.AI2026

-Monitor: Dynamic Safety Monitoring for Diffusion LLMs via Hesitation Signals

Aoxi Liu, Yupeng Chen, James Oldfield +5

Despite the emergence of diffusion large language models (D-LLMs) as an alternative to autoregressive large language models (AR-LLMs), safety monitoring for D-LLMs remains largely…

cs.AI2026

Scientific reasoning does not reliably translate into scientific forecasting in frontier AI

Sean Wu, Pan Lu, Yupeng Chen +7

AI systems are increasingly used to support forward-looking scientific judgment, but it remains unclear whether they can form reliable expectations about future scientific advances…

cs.LG2025

Exploring and Improving Initialization for Deep Graph Neural Networks: A Signal Propagation Perspective

Senmiao Wang, Yupeng Chen, Yushun Zhang +2

Graph Neural Networks (GNNs) often suffer from performance degradation as the network depth increases. This paper addresses this issue by introducing initialization methods that en…

cs.LG2024

MoFO: Momentum-Filtered Optimizer for Mitigating Forgetting in LLM Fine-Tuning

Yupeng Chen, Senmiao Wang, Yushun Zhang +5

Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks. Typically, LLMs are first pre-trained on large corpora and subsequently fine-tu…

cs.LG2024

PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming

Bingheng Li, Linxin Yang, Yupeng Chen +8

Solving large-scale linear programming (LP) problems is an important task in various areas such as communication networks, power systems, finance and logistics. Recently, two disti…