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20242026
most citedExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast

7 citations · 21 across the 28 of their papers we have counts for

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13 papers · 1 filter

cs.LG2026

ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research

Wanghan Xu, Shuo Li, Tianlin Ye +48

AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We present ResearchClawBench, a benchma…

cs.LG2026

Dynamic Mixture of Latent Memories for Self-Evolving Agents

Dianzhi Yu, Vireo Zhang, Hongru Wang +7

Achieving self-evolution in intelligent agents requires the continual accumulation of new knowledge across changing task sequences without forgetting previously acquired abilities.…

cs.LG2026

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning

Wanghan Xu, Yuhao Zhou, Hengyuan Zhao +8

Large language models can fail in critic interaction not only by answering incorrectly, but also by abandoning an initially correct scientific solution after user criticism. This i…

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.LG2025

DAWP: A framework for global observation forecasting via Data Assimilation and Weather Prediction in satellite observation space

Junchao Gong, Jingyi Xu, Ben Fei +7

Weather prediction is a critical task for human society, where impressive progress has been made by training artificial intelligence weather prediction (AIWP) methods with reanalys…

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…