29 citations · 34 across the 6 of their papers we have counts for
6 papers
MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale
Bin Wang, Tianyao He, Linke Ouyang +40
Current document parsing methods advance primarily through model architecture innovation, while systematic engineering of training data remains underexplored. Yet state-of-the-art…
Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation
Junyan Ye, Dongzhi Jiang, Zihao Wang +9
Recently, GPT-4o has garnered significant attention for its strong performance in image generation, yet open-source models still lag behind. Several studies have explored distillin…
Topic Over Source: The Key to Effective Data Mixing for Language Models Pre-training
Jiahui Peng, Xinlin Zhuang, Jiantao Qiu +4
The performance of large language models (LLMs) is significantly affected by the quality and composition of their pre-training data, which is inherently diverse, spanning various l…
WanJuanSiLu: A High-Quality Open-Source Webtext Dataset for Low-Resource Languages
Jia Yu, Fei Yuan, Rui Min +20
This paper introduces the open-source dataset WanJuanSiLu, designed to provide high-quality training corpora for low-resource languages, thereby advancing the research and developm…
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…
A Comprehensive Survey for Evaluation Methodologies of AI-Generated Music
Zeyu Xiong, Weitao Wang, Jing Yu +2
In recent years, AI-generated music has made significant progress, with several models performing well in multimodal and complex musical genres and scenes. While objective metrics…