4 papers
Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding
StepFun, :, Bin Wang +195
Large language models (LLMs) face low hardware efficiency during decoding, especially for long-context reasoning tasks. This paper introduces Step-3, a 321B-parameter VLM with hard…
Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models
Houyi Li, Wenzhen Zheng, Qiufeng Wang +8
Training Large Language Models (LLMs) is prohibitively expensive, creating a critical scaling gap where insights from small-scale experiments often fail to transfer to resource-int…
Predictable Scale: Part I, Step Law -- Optimal Hyperparameter Scaling Law in Large Language Model Pretraining
Houyi Li, Wenzhen Zheng, Qiufeng Wang +10
The impressive capabilities of Large Language Models (LLMs) across diverse tasks are now well established, yet their effective deployment necessitates careful hyperparameter optimi…
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Siming Huang, Tianhao Cheng, J. K. Liu +16
Large language models (LLMs) for code have become indispensable in various domains, including code generation, reasoning tasks and agent systems. While open-access code LLMs are in…