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Self-Building Labs

Paper recorded by Signals 4 on 2026-10-16 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.AI · 人工智能 · first seen 2026-10-19

Abstract

Self-driving laboratories (SDLs) accelerate scientific discovery by automating experimental execution and optimization. AI agents can increasingly propose new experiments, but existing SDLs can only run the procedures they were built for. Adapting them to a new experiment still takes extensive manual engineering, which makes laboratory flexibility the bottleneck for scaling discovery. We introduce

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#264 most recent of 960 cs.AI papers we have recorded · ↑ newer: AI-Driven Reproducibility and Analytical Robustness in Scientific Disc · ↓ older: Beyond SAEs: Consistent Concept Discovery with Sparse Coding
Cite this page: Self-Building Labs: the #264 most recent of 960 cs.AI papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/self-building-labs.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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