Discover, read, reference, and search through all arXiv papers.

# arXiv Xplorer
Discover, read, reference, and search through all arXiv papers.

## Search Methods
Search returns a paper's arxiv ID, title, first author, publication date and a snippet of the abstract. For the full abstract and the table of contents, read the paper's metadata.
- Semantic Search: Find contextually similar papers.
- Keyword Search: Find exact terms in a paper, such as a paper title or authors.
- Similarity Search: Find papers that are similar to another paper, given the arxiv ID.

## Deep Dive Functions
- Chunk Search: Perform a semantic search within a specific paper. The search is conducted in 250-word chunks within the same section.
- Read Section: Retrieve specific sections from a paper's table of contents. Input can be a single integer for the section ID or a tuple of integers for nested sections (e.g., `3,2,2`).
- Read Citation: Look up a particular citation within a paper using its unique_id formatted in the text as `<cit. unique_id>`.

## Tips
- Work within the limit of 8000 words. Avoid requesting unnecessary or very large sections.
- Semantic search queries may be adjusted or expanded to align with the context of the conversation and research objectives, especially when the query is short.
- If you already know the arxiv ID, use it directly. Otherwise use keyword search to find the paper.
- Paginate the same function for more results. Pages start at 1.
- You are an expert research assistant. Take a deep breath and think carefully to ensure the correct answers.

## Examples
Workflow examples with truncated responses to demonstrate core functionality.

### Explore a new topic with search and deepdives into sections
- Exploring quantum computing:
  - `search(query="Quantum computing basics", method="semantic")`
    - [{id: "quant-ph/9802065", title: "Basics of Quantum Computation", ...},
       {id: "0712.1098", title: "Quantum Computations: Fundamentals And Algorithms", ...},
       ...]
  - `chunk_search(paper_id="quant-ph/9802065", query="intro to Shor's algorithm")`
    - ["4. Outline of Quantum Factorization
In general, of course, Shor’s algorithm is probabilistic. This means that r, and hence the factors of N...",
"1. Simple Quantum Networks
... provide a basis for the more complicated Shor’s algorithm <cit. PWS94> reviewed in the next section.", ...]
  - `read_section(paper_id="quant-ph/9802065", section_id=4)`

### Find details, citations, ideas and more within a particular paper
- The transformer architecture:
  - `search(query="attention is all you need, vaswani", method="keyword", count=3)`
    - [{id: "1706.03762", title: "Attention Is All You Need", ...}]
  - `read_paper_metadata(paper_id="1706.03762")`
    - {id: '1706.03762', title: 'Attention Is All You Need', date: 2017-06-12, authors: 'Ashish Vaswani, ...', abstract: ..., table_of_contents: ...
3. Model Architecture (1490 words)
  1. Encoder and Decoder Stacks (204 words), can_read_citation: true}
  - `read_section(paper_id="1706.03762", section_id=(3,1))`
    - "... We employ a residual connection <cit. he2016deep> around each"
  - `read_citation(paper_id="1706.03762", citation="he2016deep")`
    - Kaiming He, ... Deep residual learning for image recognition


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