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arXiv:2610.08691v1 Announce Type: new Abstract: Large language model agents are accelerating scientific automation, yet verified executions rarely become persistent program-level improvements, and ex...
We introduce and release ScienceBuddy, an interactive scientific research workspace that brings continually improving scientific agents into researchers' everyday workflows. ScienceBuddy supports rese...
arXiv:2609.17523v1 Announce Type: new Abstract: We introduce and release ScienceBuddy, an interactive scientific research workspace that brings continually improving scientific agents into researcher...
SAIL is an open model with 35 B total and 3 B active parameters designed for literature research, scientific coding, and multi‑step research workflows. It is developed through a science‑aware improvement loop in which agents built on frontier AI models analyze task failures, create training tasks to address capability gaps, and iterate this process across multiple development cycles. The training pipeline combines supervised fine‑tuning, specialist training, multi‑teacher on‑policy distillation, and agentic reinforcement learning, enabling SAIL to achieve competitive performance on scientific research tasks with fewer parameters than leading open‑weight models.
arXiv:2609.19134v1 Announce Type: new Abstract: Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain con...
arXiv:2604. 17406v3 Announce Type: replace Abstract: The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science.