From the 1 of 28 linked papers with an AI index.
1 citations · 1 across the 5 of their papers we have counts for
9 papers · 1 filter
Agentic Routing: The Harness-Native Data Flywheel
Xinchen Liu, Hang Zhou, Yingjie Zong +12
The paper introduces a step‑level routing framework for large language model agents that selects the most suitable model(s) based on the full execution harness state, using logged…
MemoryFormer: Minimize Transformer Computation by Removing Fully-Connected Layers
Ning Ding, Yehui Tang, Haochen Qin +6
In order to reduce the computational complexity of large language models, great efforts have been made to to improve the efficiency of transformer models such as linear attention a…
EAQuant: Enhancing Post-Training Quantization for MoE Models via Expert-Aware Optimization
Zhongqian Fu, Tianyi Zhao, Ning Ding +4
Mixture-of-Experts (MoE) models enable scalable computation and performance in large-scale deep learning but face quantization challenges due to sparse expert activation and dynami…
Transferable text data distillation by trajectory matching
Rong Yao, Hailin Hu, Yifei Fu +5
In the realm of large language model (LLM), as the size of large models increases, it also brings higher training costs. There is a urgent need to minimize the data size in LLM tra…
PanGu- Pro:Rethinking Optimization and Architecture for Tiny Language Models
Yehui Tang, Kai Han, Fangcheng Liu +7
The power of large language models (LLMs) has been demonstrated through numerous data and computing resources. However, the application of language models on mobile devices is faci…
SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs
Shibo Jie, Yehui Tang, Kai Han +2
Transformer-based large language models (LLMs) have already achieved remarkable results on long-text tasks, but the limited GPU memory (VRAM) resources struggle to accommodate the…