arXiv:2608. 19625v1 Announce Type: new Abstract: Scientific data are increasingly used by AI agents, yet existing dataset representations provide limited support for autonomous discovery, interpretation, and invocation.
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arXiv:2607. 16845v1 Announce Type: new Abstract: Scientists at European XFEL conduct experiments that generate very large and complex datasets.
arXiv:2607. 22677v1 Announce Type: cross Abstract: Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reuse.
arXiv:2603. 01421v3 Announce Type: replace Abstract: While large language models accelerate scientific discovery, existing agents face severe limitations in adaptability, domain generalization, and multimodal scalability, often struggling to autonomously process raw, domain-specific experimental data.
arXiv:2606. 12736v1 Announce Type: new Abstract: AI agents are increasingly being developed to accelerate scientific discovery, yet their practical capabilities in real research settings remain poorly understood.
arXiv:2607. 20926v1 Announce Type: new Abstract: Scientific research involves complex information-seeking and reasoning workflows across heterogeneous sources.
arXiv:2607. 02771v1 Announce Type: new Abstract: Leadership computing facilities steward large-scale scientific datasets that routinely require substantial transformation before serving as AI training data.