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20242026
most citedInternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

4 citations · 5 across the 10 of their papers we have counts for

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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.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.AI2026

AIDABench: AI Data Analytics Benchmark

Yibo Yang, Fei Lei, Yixuan Sun +24

As AI-driven document understanding and processing tools become increasingly prevalent in real-world applications, the need for rigorous evaluation standards has grown increasingly…

cs.CV2026

ScaleEdit-12M: Scaling Open-Source Image Editing Data Generation via Multi-Agent Framework

Guanzhou Chen, Erfei Cui, Changyao Tian +6

Instruction-based image editing has emerged as a key capability for unified multimodal models (UMMs), yet constructing large-scale, diverse, and high-quality editing datasets witho…

cs.CV2026

InternVL-U: Democratizing Unified Multimodal Models for Understanding, Reasoning, Generation and Editing

Changyao Tian, Danni Yang, Guanzhou Chen +26

Unified multimodal models (UMMs) that integrate understanding, reasoning, generation, and editing face inherent trade-offs between maintaining strong semantic comprehension and acq…