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Xplorer is an innovative tool designed for researchers and enthusiasts to seamlessly discover, read, and reference arXiv papers. With its advanced semantic search capabilities, Xplorer allows users to perform detailed queries across 250-word chunks of paper sections, ensuring relevant results tailored to their needs. Users can easily access essential paper metadata, including titles, abstracts, and authors, while also obtaining direct links to figures and their captions for enhanced comprehension. The app supports citation lookups, making it simple to verify references and their contexts. Additionally, Xplorer enables users to read specific sections from the table of contents, facilitating targeted research. With the ability to upload files and execute Python code, users can perform advanced data analysis and visualize results effortlessly. Whether you're seeking summaries of complex topics or detailed insights into the latest research, Xplorer empowers you to navigate the vast landscape of academic papers with ease and efficiency, making it an indispensable tool for anyone engaged in scholarly pursuits. For more information, visit https://chat.openai.com/g/g-WeT9tE7SR-arxiv-xplorer.
What Can You Do With Xplorer?
- Perform Semantic Searches
Effortlessly search through arXiv papers using natural language queries, yielding relevant results from 250-word chunks across various sections, ensuring precise and meaningful insights.
- Extract Figures and Captions
Quickly obtain figure URLs, captions, and section titles from papers, allowing you to visually comprehend complex data and enhance your research presentations effectively.
- Lookup Citation Metadata
Access detailed citation metadata for specific papers, facilitating easy reference checks and ensuring you can track relevant literature seamlessly for your academic work.
- Read Paper Metadata
Dive into comprehensive metadata, including titles, abstracts, authors, and more, helping you evaluate papers at a glance and streamline your research process.
- Analyze Sections of Papers
Read specific sections from the table of contents, allowing you to focus on relevant parts of papers without sifting through unnecessary content, saving you valuable time.
Features and Functions
Enhance Your Journey with Cutting-Edge Features and Functions
- GPT Action arXiv Xplorer > get_figure(Get a figure URL, caption, and section title.)
- GPT Action arXiv Xplorer > read_citation(Lookup a particular citation id of a paper, if paper_metadata.can_read_citation == True.)
- GPT Action arXiv Xplorer > read_section(Read a specific section from the table of contents of a paper.)
- Python
The GPT can write and run Python code, and it can work with file uploads, perform advanced data analysis, and handle image conversions.
- Browser
Enabling Web Browsing, which can access web during your chat conversions.
- File attachments
You can upload files to this GPT.
Prompt Starters
Unleash your creativity with our prompt starters, sparking ideas and inspiration right from the start.
- Show me the transformer model architecture and tell me the hyperparams of each layer
- How is the reward model implemented in instructGPT: https://arxiv.org/abs/2203.02155
- Find me a good summary paper/book on quantum computing for beginners
- What are the key improvements made in SDXL: https://arxiv.org/pdf/2307.01952.pdf
- Write a literature review of model based reinforcement learning.
- Tabulate the results of https://arxiv.org/pdf/2311.05997.pdf
- What are the latest efficiency improvements in perovskite solar cells
- What regularization methods were used in the transformer paper?
GPTs Categories
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