7 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
Kernel-Smith: A Unified Recipe for Evolutionary Kernel Optimization
He Du, Qiming Ge, Jiakai Hu +18
We present Kernel-Smith, a framework for high-performance GPU kernel and operator generation that combines a stable evaluation-driven evolutionary agent with an evolution-oriented…
TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration
Zerun Ma, Guoqiang Wang, Xinchen Xie +7
While Large Language Models (LLMs) have empowered AI research agents to perform isolated scientific tasks, automating complex, real-world workflows, such as LLM training, remains a…
Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale
Yicheng Zou, Dongsheng Zhu, Lin Zhu +174
We introduce Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model. Scaling to this unprecedented size, the model delivers a comprehensive enhancem…
DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning
Yicheng Chen, Zerun Ma, Xinchen Xie +2
In the current landscape of Large Language Models (LLMs), the curation of large-scale, high-quality training data is a primary driver of model performance. A key lever is the \emph…