7 citations · 21 across the 28 of their papers we have counts for
11 papers · 1 filter
Atria Dawn: The Dawn of Agentic Superintelligence
Honglin Guo, Tao Gui, Yicheng Chen +139
As AI agents become participants in the development of their successors, they reshape both the production of intelligence and the role of human researchers. We introduce Atria Dawn…
SeekBrain: An Autonomous Multi-Agent System for Accelerating Neuroscience Discovery
Jiamin Wu, Peishan Xiang, Jingyang Chen +26
Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytical challenges posed by highly…
Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation
Yifan Zhou, Qihao Yang, Yan Li +14
Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biological genomes. Current benc…
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…
SCI-PRM: A Tool Aware Process Reward Model for Scientific Reasoning Verification
Xiangyu Zhao, Henry Hengyuan Zhao, Yiheng Wang +7
While Process Reward Models (PRMs) have achieved remarkable success in mathematical reasoning, their application in complex scientific domains-such as biology, chemistry, and physi…
Earth Science Foundation Models: From Perception to Reasoning and Discovery
Xiangyu Zhao, Bo Liu, Yuehan Zhang +9
Large foundation models (FMs) are transforming Earth science by integrating heterogeneous multimodal data, such as multi-platform imagery, gridded reanalysis data, diverse geophysi…
SciOrch: Learning to Orchestrate Expert LLMs for Solving Frontier Multimodal Scientific Reasoning Tasks
Jingru Guo, Xiangyuan Xue, Lian Zhang +6
Frontier scientific reasoning remains a major challenge for large language models (LLMs), where even the strongest commercial systems fall short of expert-level performance. A clos…
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.…
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…
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…
SciEvalKit: An Open-source Evaluation Toolkit for Scientific General Intelligence
Yiheng Wang, Yixin Chen, Shuo Li +33
We introduce SciEvalKit, a unified benchmarking toolkit designed to evaluate AI models for science across a broad range of scientific disciplines and task capabilities. Unlike gene…