WisPaper

Overview

WisPaper is an AI academic search and literature reading tool designed for research scenarios, launched by the Fudan team and positioned to help researchers complete literature retrieval, screening, reading, and organization more efficiently. It supports natural language questions, can understand users' research intent, and find more relevant paper results based on full-text search and semantic analysis.

Compared with traditional keyword search, WisPaper places greater emphasis on "intent understanding" and "relevance verification": the system can intelligently break down queries, reduce interference from irrelevant results, and support marking highly relevant literature in the results, helping users lock onto target materials more quickly. In addition, the product also provides local literature database management, literature Q&A, paragraph translation, abstract refinement, and other capabilities, making it suitable for paper research, proposal preparation, review writing, and daily research reading.

Main Features

• AI Academic Search

  • Supports using natural language to describe research questions, rather than being limited to keyword input only
  • Can connect with mainstream academic resources for literature retrieval
  • Improves retrieval accuracy through semantic understanding, question breakdown, and deep search
  • Provides highly relevant result markers for quick paper screening

• Full-Text-Level Retrieval and Intent Matching

  • Does not rely only on title or abstract matching
  • Even if keywords do not appear directly in the title, it can still determine relevance by combining the main text content
  • Helps discover "hidden relevant" paper materials

• Local Knowledge Base / Literature Database Management

  • Supports importing local files to build a personal research materials database
  • Provides a literature management and citation organization experience similar to Zotero
  • Supports retrieval and Q&A based on a personal literature database

• AI Literature Reading

  • Supports paragraph-level translation of English papers
  • Allows users to ask questions about selected text and obtain explanations based on the original content
  • Supports extracting core arguments, research methods, and key conclusions to generate structured summaries

• Scholar QA and Literature Dialogue

  • Users can ask questions directly around paper content
  • Suitable for understanding complex concepts, comparing viewpoints, or quickly grasping article highlights

• AI Feeds

  • Attention conditions can be configured by research topic
  • The system will proactively push the latest research progress and potentially important papers
  • Suitable for continuously tracking frontier developments in a certain direction

Product Pricing

The official website provides an entry to the Pricing page, but the specific pricing plans are not currently shown in the captured content. Whether a free version, trial quota, or paid subscription is available is recommended to be confirmed based on the latest information on the official website: https://www.wispaper.ai/

Frequently Asked Questions

Who is WisPaper suitable for?

It is mainly suitable for university teachers, doctoral/master's students, researchers, and users who need to frequently search and read English literature.

What is the difference between WisPaper and traditional academic search?

Traditional search relies more on keyword matching; WisPaper places greater emphasis on natural language understanding, full-text retrieval, and research intent recognition, which can reduce irrelevant results and improve screening efficiency.

Does it support managing your own paper materials?

Yes. WisPaper can import local files and build a personal literature database, making it convenient for unified management, retrieval, and Q&A based on document content.

Does it support assistance for reading English papers?

Yes. It provides paragraph translation, key point summarization, and dialogue functions based on paper content, which can help users understand English literature more quickly.