←Back to feed
🧠 AI🟢 Bullish
DeepXiv-SDK: An Agentic Data Interface for Scientific Papers
arXiv – CS AI|Hongjin Qian, Ziyi Xia, Ze Liu, Jianlv Chen, Kun Luo, Minghao Qin, Chaofan Li, Lei Xiong, Sen Wang, Zhengyang Liang, Zheng Liu||3 views
🤖AI Summary
DeepXiv-SDK introduces a new agentic data interface for scientific papers that enables AI research agents to access and process academic literature more efficiently. The SDK provides structured, budget-aware views of papers and supports progressive access patterns, currently deployed at arXiv scale with free API access.
Key Takeaways
- →DeepXiv-SDK solves the bottleneck of inefficient paper access for AI research agents by providing structured data interfaces instead of raw PDF/HTML parsing.
- →The system offers progressive access with header-first screening, section-structured navigation, and on-demand evidence-level verification to optimize token usage.
- →Currently deployed at arXiv scale with daily synchronization and plans to extend to other open-access corpora like PubMed Central and bioRxiv.
- →Provides RESTful APIs, open-source Python SDK, and web demo with free registration-based access.
- →Enables constraint-driven search and curation over paper sets through multi-faceted retrieval and aggregation capabilities.
#ai-research#scientific-papers#arxiv#sdk#research-agents#api#data-interface#evidence-grounding#open-source
Read Original →via arXiv – CS AI
Act on this with AI
Stay ahead of the market.
Connect your wallet to an AI agent. It reads balances, proposes swaps and bridges across 15 chains — you keep full control of your keys.
Related Articles