Xplorer-AI-powered academic research assistant

Example

A user wants to find papers related to 'quantum entanglement in condensed matter physics'. Using semantic search, Xplorer retrieves papers that contextually match the query.

Scenario

Researchers often need to find papers that discuss specific concepts or developments within their field. Xplorer's search functions help locate the most relevant papers, even if the exact terms are not used, by understanding the context and related terms.

Example

A user retrieves metadata for the paper 'Attention Is All You Need' to understand its abstract, authors, and main sections before diving into the full text.

Scenario

Before reading a full paper, researchers can use this function to get an overview of the paper's content, including the abstract, authorship, and section breakdown. This helps in quickly assessing the paper's relevance.

Example

A user looks for detailed explanations of 'Shor's algorithm' within a specific paper on quantum computing. Chunk search identifies the relevant sections that discuss this algorithm.

Scenario

When looking for specific information within a paper, this function allows users to pinpoint exact sections or chunks of text that contain the information they need, saving time and effort in sifting through the entire document.

Example

A user needs a specific figure from a paper to understand a complex diagram related to neural network architectures.

Scenario

Visual aids are crucial for comprehending detailed and technical information. Xplorer's ability to retrieve and display figures from papers helps users quickly access and understand visual data.

Example

A user encounters a citation '<cit. he2016deep>' within a paper and retrieves the full reference to Kaiming He's work on deep residual learning.

Scenario

Researchers often follow citation trails to build a comprehensive understanding of a topic. This function allows them to quickly access full citation details, facilitating deeper research and literature reviews.