arXiv (All)
open access
POSEIDON: Scaling Training Environments for Scientific Agents from Code Repositories
Training environments remain a major bottleneck for agents in data-driven scientific discovery. Existing collections of executable and verifiable training environments are small, and their construction remains difficult to scale. To address this limitation, we introduce Poseidon, an automated pipeli
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments#1013337
- Praxist: From Experimental Artifacts to Solution Lineages#1356162
- AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists#1118396
- AutoSciBench: Autonomous Benchmark Generation for Evaluating Scientific Agents#1201153
- ExpEvolve: Structuring and Reusing Experience for Open-Ended Discovery#1413908
Record · ID 1447815
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive