> ## Documentation Index
> Fetch the complete documentation index at: https://www.meilisearch.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Paperscope

> Search, explore, and chat with 6,000 AI research papers using hybrid search, similar documents, and conversational search

> [!NOTE]
>
> **Live demo**: [paperscope-one.vercel.app](https://paperscope-one.vercel.app)

Paperscope indexes around 6,000 AI and machine learning papers from arXiv, enriched with citation counts from Semantic Scholar. Type a title, an author, or describe an idea in your own words: Meilisearch matches both the words and the meaning. Open any paper to find related work, then ask questions across the whole corpus, your reading list, or a single paper.

![Paperscope search page showing a hybrid search for "attention is all you need" with category and year facets](https://mintcdn.com/meilisearch-6b28dec2/0UjPeEQ3J8rC88I0/assets/images/demos/paperscope-demo.png?fit=max\&auto=format\&n=0UjPeEQ3J8rC88I0\&q=85\&s=646e4654af683b615bdac436de2a9803)

## Key features

* **Hybrid search slider**: Move from exact words to meaning in real time by changing `semanticRatio`. The results header shows how many papers were found only by meaning, using `semanticHitCount`.
* **Built-in embeddings**: Documents and queries are embedded inside Meilisearch with a HuggingFace model (`BAAI/bge-small-en-v1.5`), with no external embedding service.
* **Similar papers**: Each paper lists its nearest neighbours from the `/similar` endpoint, optionally filtered to the same arXiv category.
* **Faceted navigation**: Filter by category, topic, author, and year. The year slider uses `facetStats`, and the author box uses facet search.
* **Citation-aware ranking**: A custom ranking rule on `citationCount` breaks ties in favor of influential papers, and results can be sorted by citations or date.
* **Multi-search**: Papers and matching authors come back in a single request across two indexes.
* **Chat with the papers**: The "Ask the papers" page uses the `/chats` route. The LLM runs hybrid searches as a tool and streams its progress and sources.
* **Scoped chat with tenant tokens**: Chatting with a reading list or a single paper uses a short-lived tenant token whose search rule restricts retrieval to those papers.

## Links

> **[Try the demo](https://paperscope-one.vercel.app)**
>
> Search and chat with AI research papers

> **[Hybrid search](/docs/capabilities/hybrid_search/overview)**
>
> Combine keyword and semantic search

> **[Chat route](/docs/capabilities/agentic_search/overview)**
>
> Learn about the chat route

> **[Tenant tokens](/docs/capabilities/security/overview)**
>
> Restrict what each user can search


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.