Publications (9)
E2ATST: A Temporal-Spatial Optimized Energy-Efficient Architecture for Training Spiking Transformer
Yunhao Ma, Yanyu Lin, Mingjing Li +9
(1) Pengcheng Laboratory, (2) Southern University of Science and Technology, (3) Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, (4) University of Chinese…
GameUIAgent: An LLM-Powered Framework for Automated Game UI Design with Structured Intermediate Representation
Wei Zeng, Fengwei An, Zhen Liu +1
Game UI design requires consistent visual assets across rarity tiers yet remains a predominantly manual process. We present GameUIAgent, an LLM-powered agentic framework that trans…
Scalable Generative Game Engine: Breaking the Resolution Wall via Hardware-Algorithm Co-Design
Wei Zeng, Xuchen Li, Ruili Feng +3
Real-time generative game engines represent a paradigm shift in interactive simulation, promising to replace traditional graphics pipelines with neural world models. However, exist…
Gait Patterns as Biomarkers: A Video-Based Approach for Classifying Scoliosis
Zirui Zhou, Junhao Liang, Zizhao Peng +3
Scoliosis presents significant diagnostic challenges, particularly in adolescents, where early detection is crucial for effective treatment. Traditional diagnostic and follow-up me…
Pose as Clinical Prior: Learning Dual Representations for Scoliosis Screening
Zirui Zhou, Zizhao Peng, Dongyang Jin +3
Recent AI-based scoliosis screening methods primarily rely on large-scale silhouette datasets, often neglecting clinically relevant postural asymmetries-key indicators in tradition…
Genetic Quantization-Aware Approximation for Non-Linear Operations in Transformers
Pingcheng Dong, Yonghao Tan, Dong Zhang +11
Non-linear functions are prevalent in Transformers and their lightweight variants, incurring substantial and frequently underestimated hardware costs. Previous state-of-the-art wor…
Energy-Oriented Computing Architecture Simulator for SNN Training
Yunhao Ma, Wanyi Jia, Yanyu Lin +4
With the growing demand for intelligent computing, neuromorphic computing, a paradigm that mimics the structure and functionality of the human brain, offers a promising approach to…
BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation
Peng Xu, Wenqi Shao, Mengzhao Chen +6
Large language models (LLMs) have demonstrated outstanding performance in various tasks, such as text summarization, text question-answering, and etc. While their performance is im…
The limits of bio-molecular modeling with large language models : a cross-scale evaluation
Yaxin Xu, Yue Zhou, Tianyu Zhao +2
The modeling of bio-molecular system across molecular scales remains a central challenge in scientific research. Large language models (LLMs) are increasingly applied to bio-molecu…