14 citations · 24 across the 7 of their papers we have counts for
7 papers
From Self-Attention to Connection Laplacian: A Unified Operator View of Transformers
Binbin Lin, Wei Chen, Yalun Li +3
Self-attention is a ubiquitous primitive in modern sequence models, yet its operator-level geometry is only partially understood. We view a token sequence as a vector field over th…
HydraHead: From Head-Level Functional Heterogeneity to Specialized Attention Hybridization
Zhentao Tan, Wei Chen, Jingyi Shen +4
The quadratic complexity of attention poses a critical bottleneck for long-context processing, spurring interest in hybrid attention designs. Most open-source hybrid models adopt a…
SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits
Edward Lin, Sahil Modi, Siva Kumar Sastry Hari +30
As agentic AI systems become increasingly capable of generating and optimizing GPU kernels, progress is constrained by benchmarks that reward speedup over software baselines rather…
How Confident Is the First Token? An Uncertainty-Calibrated Prompt Optimization Framework for Large Language Model Classification and Understanding
Wei Chen, Guoyang Ju, Yuanyuan Qi
With the widespread adoption of large language models (LLMs) in natural language processing, prompt engineering and retrieval-augmented generation (RAG) have become mainstream to e…
From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
Wei Chen, Zhen Huang, Liang Xie +9
Large Language Models (LLMs) tend to prioritize adherence to user prompts over providing veracious responses, leading to the sycophancy issue. When challenged by users, LLMs tend t…
Model Compression and Efficient Inference for Large Language Models: A Survey
Wenxiao Wang, Wei Chen, Yicong Luo +6
Transformer based large language models have achieved tremendous success. However, the significant memory and computational costs incurred during the inference process make it chal…
CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale Attention
Wenxiao Wang, Wei Chen, Qibo Qiu +5
While features of different scales are perceptually important to visual inputs, existing vision transformers do not yet take advantage of them explicitly. To this end, we first pro…