activity
20242026
most citedInternLM2 Technical Report

29 citations · 53 across the 14 of their papers we have counts for

collaborators

16 papers

cs.AI2026

Scaling Scientific Discovery Environments for Turn-Level Agentic RL

Yucheng Xu, Keyi Zhang, Yuyang Yu +4

Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution environment and produces a stati…

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

AICC: Parse HTML Finer, Make Models Better -- A 7.3T AI-Ready Corpus Built by a Model-Based HTML Parser

Ren Ma, Jiantao Qiu, Chao Xu +26

While web data quality is crucial for large language models, most curation efforts focus on filtering and deduplication,treating HTML-to-text extraction as a fixed pre-processing s…

cs.CL2025

Dripper: Token-Efficient Main HTML Extraction with a Lightweight LM

Mengjie Liu, Jiahui Peng, Wenchang Ning +14

High-quality main content extraction from web pages is a critical prerequisite for constructing large-scale training corpora. While traditional heuristic extractors are efficient,…

astro-ph.IM2025★ 1 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.CV2025★ 2 cited

MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing

Junbo Niu, Zheng Liu, Zhuangcheng Gu +58

We introduce MinerU2.5, a 1.2B-parameter document parsing vision-language model that achieves state-of-the-art recognition accuracy while maintaining exceptional computational effi…

cs.LG2025

Intern-S1: A Scientific Multimodal Foundation Model

Lei Bai, Zhongrui Cai, Yuhang Cao +173

In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…

cs.CV2025

VRBench: A Benchmark for Multi-Step Reasoning in Long Narrative Videos

Jiashuo Yu, Yue Wu, Meng Chu +14

We present VRBench, the first long narrative video benchmark crafted for evaluating large models' multi-step reasoning capabilities, addressing limitations in existing evaluations…

cs.CV2025★ 1 cited

Consensus Entropy: Harnessing Multi-VLM Agreement for Self-Verifying and Self-Improving OCR

Yulong Zhang, Tianyi Liang, Xinyue Huang +5

Optical Character Recognition (OCR) is fundamental to Vision-Language Models (VLMs) and high-quality data generation for LLM training. Yet, despite progress in average OCR accuracy…

cs.CL2025

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…

cs.CV2024★ 3 cited

OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations

Linke Ouyang, Yuan Qu, Hongbin Zhou +17

Document content extraction is a critical task in computer vision, underpinning the data needs of large language models (LLMs) and retrieval-augmented generation (RAG) systems. Des…

cs.CV2024★ 16 cited

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Zhe Chen, Weiyun Wang, Yue Cao +39

We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…

cs.CL2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data

Haoran Sun, Renren Jin, Shaoyang Xu +10

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…

cs.CV2024★ 1 cited

OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text

Qingyun Li, Zhe Chen, Weiyun Wang +37

Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…

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…

cs.CL2024

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…