11 citations · 15 across the 5 of their papers we have counts for
6 papers
SP-DocReader: Difference-Aware Self-Play for Precise Document OCR
Wenjie Liao, Xiaohui Song, Liangjie Zhao +1
Accurate page transcription remains difficult for vision language models under limited input and training budgets. We present SP-DocReader, a self-play framework for optical charac…
IRIS: Interpolative Rényi Iterative Self-play for Large Language Model Fine-Tuning
Wenjie Liao, Like Wu, Liangjie Zhao +2
Self-play fine-tuning enables large language models to improve beyond supervised fine-tuning without additional human annotations by contrasting annotated responses with self-gener…
Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models -- The Story Goes On
Liang Zeng, Liangjun Zhong, Liang Zhao +9
In this paper, we investigate the underlying factors that potentially enhance the mathematical reasoning capabilities of large language models (LLMs). We argue that the data scalin…
Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models
Tianwen Wei, Bo Zhu, Liang Zhao +13
In this technical report, we introduce the training methodologies implemented in the development of Skywork-MoE, a high-performance mixture-of-experts (MoE) large language model (L…
LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models
Liang Zhao, Tianwen Wei, Liang Zeng +12
We introduce LongSkywork, a long-context Large Language Model (LLM) capable of processing up to 200,000 tokens. We provide a training recipe for efficiently extending context lengt…
Skywork: A More Open Bilingual Foundation Model
Tianwen Wei, Liang Zhao, Lichang Zhang +27
In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3.2 trillion tokens drawn from both English and Chinese texts…