1 citations · 1 across the 5 of their papers we have counts for
6 papers
D2K-Bench: Can LLM Agents Turn Expert Designs into Efficient GPU Kernels?
Daifeng Li, Huiqiang Jiang, Chengruidong Zhang +6
GPU kernels generated by large language model (LLM) agents can remain less efficient than expert implementations, but runtime alone does not reveal how the gap relates to design di…
Formal O(N3)-Scaling Second-Order Perturbation Theory by Block Tensor Decomposition: Implementation on MP2 and rPT2
Yueyang Zhang, Wei Wu, Peifeng Su
Block tensor decomposition (BTD) and canonical polyadic decomposition (CPD) are combined into a unified -scaling framework for second-order perturbation theory (PT2), demon…
OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond
Zunhai Su, Rui Yang, Chao Zhang +12
The rapid advancement toward long-context reasoning and multi-modal intelligence has made the memory footprint of the Key-Value (KV) cache a dominant memory bottleneck for efficien…
LongCat-Flash Technical Report
Meituan LongCat Team, Bayan, Bei Li +179
We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…
Introducing LongCat-Flash-Thinking: A Technical Report
Meituan LongCat Team, Anchun Gui, Bei Li +122
We present LongCat-Flash-Thinking, an efficient 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model. Its advanced capabilities are cultivated through a metic…
Flash Communication: Reducing Tensor Parallelization Bottleneck for Fast Large Language Model Inference
Qingyuan Li, Bo Zhang, Liang Ye +5
The ever-increasing sizes of large language models necessitate distributed solutions for fast inference that exploit multi-dimensional parallelism, where computational loads are sp…