arXiv (All)
open access
DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale
Large-scale agentic training and evaluation with large language models (LLMs) rely on isolated, stateful execution environments in which models inspect repositories, invoke tools, execute commands, and interact with task-specific services. These workloads create sandboxes in large bursts, span heter
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
- DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale#1028669
- Delta-Based Neural Architecture Search: LLM Fine-Tuning via Code Diffs#158578
- Mr.LHDR: A Benchmark for Multimodal Real-World Long-Horizon Deep Research Agents#1069954
- StateFlow: Sequence Pipeline Parallelism for Long-Context Modeling with Linear Recurrence#440341
- LongWoF-Bench: Evaluating EvoMap Genes for Verifiable Long-Workflow Tasks#1014808
Record · ID 1048373
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