activity
20242026
most citedInternLM2 Technical Report

29 citations · 29 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Intern-S2-Mobius: Foundation Model with Decoupled Knowledge and Reasoning

Kai Chen, Jifeng Ding, Ning Ding +44

We introduce Mobius-v0, an architecture that comprises a globally shared Memory (FFN) that stores knowledge vectors and multiple Reasoners (Self-Attn) that iteratively achieve comp…

cs.LG2026

Intern-S2-Preview: Scientific Agentic Foundation Model

Lei Bai, Jiaqi Cao, Chiyu Chen +121

Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sus…

cs.CV2026

Scalable Visual Pretraining for Language Intelligence

Yiming Zhang, Zhonghan Zhao, Wenwei Zhang +14

The rapid progress of large foundation models has been driven predominantly by pretraining on large-scale text corpora. However, many forms of knowledge are conveyed through visual…

cs.CL2026

OpenCompass: A Universal Evaluation Platform for Large Language Models

Maosong Cao, Kai Chen, Haodong Duan +27

In recent years, the field of artificial intelligence has undergone a paradigm shift from task-specific small-scale models to general-purpose large language models (LLMs). With the…

cs.LG2026

Dimensional Balance Improves Large Scale Spatiotemporal Prediction Performance

Jing Chen, Shixiang Pan, Yujie Fan +3

Accurate spatiotemporal pattern analysis is critical in fields such as urban traffic, meteorology, and public health monitoring. However, existing methods face performance bottlene…

cs.LG2026

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…

cs.CL2025

MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space

Yicheng Chen, Yining Li, Kai Hu +3

Data quality and diversity are key to the construction of effective instruction-tuning datasets. % With the increasing availability of open-source instruction-tuning datasets, it i…

cs.CL2024★ 29 cited

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…