29 citations · 42 across the 31 of their papers we have counts for
7 papers · 1 filter
VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks
Shiduo Zhang, Zhe Xu, Peiju Liu +8
General-purposed embodied agents are designed to understand the users' natural instructions or intentions and act precisely to complete universal tasks. Recently, methods based on…
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…
WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset
Jiantao Qiu, Haijun Lv, Zhenjiang Jin +23
This paper presents WanJuan-CC, a safe and high-quality open-sourced English webtext dataset derived from Common Crawl data. The study addresses the challenges of constructing larg…
Turn Waste into Worth: Rectifying Top- Router of MoE
Zhiyuan Zeng, Qipeng Guo, Zhaoye Fei +7
Sparse Mixture of Experts (MoE) models are popular for training large language models due to their computational efficiency. However, the commonly used top- routing mechanism su…
Balanced Data Sampling for Language Model Training with Clustering
Yunfan Shao, Linyang Li, Zhaoye Fei +3
Data plays a fundamental role in the training of Large Language Models (LLMs). While attention has been paid to the collection and composition of datasets, determining the data sam…
InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning
Huaiyuan Ying, Shuo Zhang, Linyang Li +19
The math abilities of large language models can represent their abstract reasoning ability. In this paper, we introduce and open-source our math reasoning LLMs InternLM-Math which…
Unearthing Large Scale Domain-Specific Knowledge from Public Corpora
Zhaoye Fei, Yunfan Shao, Linyang Li +6
Large language models (LLMs) have demonstrated remarkable potential in various tasks, however, there remains a significant lack of open-source models and data for specific domains.…