{"enrichment":{"faq":[{"a":"DeepXiv lets you search arxiv papers by topic\u2014enter your query like 'machine learning' and browse results with metadata and summaries. You can filter by time window to find recent papers, then open specific papers by ID to read progressively without loading the full document at once.","q":"How do I search arxiv papers on machine learning with DeepXiv?"},{"a":"Yes. DeepXiv supports section-level access, so you can retrieve just the introduction, methods, results, or conclusion from a paper. This saves tokens and time by letting you read only the parts you need rather than loading the entire document.","q":"Can I read a specific section of a research paper instead of the full text?"},{"a":"DeepXiv's trending papers discovery lets you find popular open-access research by topic or time window\u2014such as papers trending in the last 2 weeks or this month. Results include metadata and brief summaries so you can quickly assess relevance before diving deeper.","q":"What does DeepXiv's trending papers feature show?"},{"a":"DeepXiv pulls paper metadata and brief summaries without requiring full-text loads, often integrating with Semantic Scholar for citation context. This lightweight approach lets you look up arxiv IDs, get abstracts and section listings, and decide which papers to read in detail.","q":"How does DeepXiv retrieve paper metadata and summaries?"},{"a":"Yes. DeepXiv supports author-based searches\u2014you can search for papers by researchers like Karpathy. Combined with topic and time-window filters, this helps you locate specific researchers' work within the open-access literature.","q":"Can DeepXiv search for papers by author name?"},{"a":"DeepXiv integrates with Semantic Scholar and arxiv for comprehensive literature discovery. This combination enables web search for AI papers, metadata enrichment, and citation tracking alongside arxiv's native search and trending features.","q":"What integrations does DeepXiv offer for literature search?"}],"shadow_tags":["section-level-reading","progressive-access","arxiv-integration","token-efficient","layered-retrieval","academic-search","open-access-papers","metadata-focused","trending-content","lightweight-reading"],"summary_rewrite":"DeepXiv enables layered exploration of open-access research papers, letting you search by topic or ID and read specific sections without loading entire documents. It supports trending paper discovery, web search, and integrates with Semantic Scholar metadata for citation context."},"files":[{"bytes":8231,"path":"skills/deepxiv/SKILL.md","sha256":"cbf5e46d7140d78a4e28191cf773e3d645b1c75a4926e414906d2dfa03ee22bc","url":"https://skillfed.io/files/wanshuiyin/Auto-claude-code-research-in-sleep/deepxiv/c144bc6e/SKILL.md"}],"id":"wanshuiyin/Auto-claude-code-research-in-sleep/deepxiv","links":{"html":"https://skillfed.io/wanshuiyin/Auto-claude-code-research-in-sleep/deepxiv","md":"https://skillfed.io/wanshuiyin/Auto-claude-code-research-in-sleep/deepxiv.md","repo":"https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":1247,"language":"Python","last_updated":"2026-07-22","license":"MIT","name":"deepxiv","publisher":"wanshuiyin","stars":13939},"relations":{"similar":[{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/research-lit"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/arxiv"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/exa-search"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/wiki-enrich"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/semantic-scholar"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/alphaxiv"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/research-wiki"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/openalex"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/idea-creator"},{"id":"wanshuiyin/Auto-claude-code-research-in-sleep/result-to-claim"}]},"slug":{"owner":"wanshuiyin","repo":"Auto-claude-code-research-in-sleep","skill":"deepxiv"},"version":"c144bc6e"}