
Zerve AI
Quadratic
DataLab
Hex
Metabase
Saturn Cloud
Observable
Data notebook built for speed, visibility, and collaboration

Google Scholar
elicit
Connected Papers
ResearchGate
Research Rabbit
Perplexity.ai
Scopus
An academic search engine that utilizes artificial intelligence methods to provide highly relevant results and novel tools to filter them with ease.

Which is more popular?
Based on our record, SemanticScholar seems to be more popular. It has been mentioned 4 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | hyperquery.ai | semanticscholar.org |
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What each product offers, as listed by its team.


No features have been listed yet.
Possible disadvantages
How often each product is chosen within a category, 0–100% relative to the other.


Share your experience with using Hyperquery and SemanticScholar. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


Tracking Hyperquery since Feb 2023.
Cool project, the space is very crowded: https://x.com/JeffDean/status/1991053401061536027 and http://semanticscholar.org/ come to mind. - Source: Hacker News / 11 months ago
Hi everyone, I have been playing with a few new AI tools for literature reviews that you might like: - Seamless https://seaml.es/ - Semantic Scholar https://semanticscholar.org - Epsilon https://epsilon.ai/ I hope you find them useful. Source: almost 3 years ago
I rely mostly on Microsoft Academic Search. I find an article I need and then usually Google the exact title followed by filetype:pdf. For example: "Toward creating a fairer ranking in search engine results" filetype:pdf. Other services... Source: about 5 years ago
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