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ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments

Paper recorded by Signals 4 on 2026-09-16 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17

Category: cs.CL · 自然语言处理 · first seen 2026-09-17

Abstract

Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain conventions, and specialized correctness criteria make this knowledge difficult to convert into reliable learning experience-a challenge we call the scientific experience bottleneck. We introduce ScienceIDE, infrastructure for turning the world's scien

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#14 most recent of 186 cs.CL papers we have recorded · ↑ newer: PANORAMA: Panoptic Grounded Captioning via Mask Proposal Selection · ↓ older: Playing log(N)-Questions over Wikipedia Abstracts: Communication Effic
Cite this page: ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments: the #14 most recent of 186 cs.CL papers we have recorded (as of 2026-09-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/scienceide-turning-world-s-scientific-codebase-into-agent-learnable-environments.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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