Alternatives
Products that do what ScholarXIV Papers API does
Search 3 million+ research papers with a single API call
- 1SA
2024 · github.com
- 2IM
As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…
2024 · papermatch.mitanshu.tech
- 3AV
2017 · arxiv-vanity.com
- 4
- 5NI
Understanding scientific articles can be tough, even in your own field. Trying to comprehend articles from others? Good luck. Enter, Now I Get It! I made this app for curious people. Simply upload an article and after a few minutes you'll have an interactive web page showcasing the highlights. Generated pages are stored in the cloud and can be viewed from a gallery. Now I Get It! uses the best LLMs out there, which means the app will improve as AI improves. Free for now - it's capped at 20 articles per day so I don't burn cash. A few things I (and maybe you will) find interesting: * This is…
Feb 2026 · nowigetit.us
- 6DS
Built an automated system to run a deep search of ArXiv and carefully find all the precise papers that exist on a complex topic. It's different from simple RAG because it searches, classifies, and adapts based on relevant papers it uncovers, and then continues until it finds every paper on a topic (trying to mimic the human research process). Benchmarked 10x higher accuracy and total retrieval compared to Google Scholar for a median search (whitepaper on website). Also knows when it is complete, and misses virtually nothing (< 3% or so, once it's converged). Website has a free trial and a…
2024 · app.undermind.ai
- 7IM
When I read papers, I have to jump between multiple tabs to find the dataset, code, videos, peer reviews, and so on. I tried to fix this with this project. It started as a project just for papers on arXiv, but after its initial success on Twitter (got like 1.9k views: the most I have gotten for a post), I have now expanded it to include other openly available papers from PubMed Central, bioRxiv, medRxiv, and eLife. These papers have been linked with their genes, proteins, diseases, drugs, clinical trials, 3D protein structures, code, and cited and similar papers. This project now has four…
Jul 2026 · tomesphere.com
- 8
- 9AArXivTok▲105
I made this, and it's fully open source so if someone wants to contribute here you have the url: https://github.com/Miguel07Alm/arxivtok. For this project I was inspired by https://wikitok.vercel.app.
2025 · arxivtok.vercel.app
- 10TT
Hello HN, Talk2Arxiv is a small open-source RAG application I've been building for a few weeks. To use it just prepend any arxiv.org link with 'talk2' to load the paper into a responsive RAG chat application (e.g. www.arxiv.org/abs/1706.03762 -> www.talk2arxiv.org/abs/1706.03762). All implementation details are in the GitHub. Currently, because I've opted to extract text from the PDF of the paper rather than reading the LaTeX source code (since I wanted to build a more generic PDF RAG in the process), it struggles with symbolic text / mathematics, and sometimes fails…
2023 · github.com
- 11
- 12
- 13BA
2023 · bulletpapers.ai
- 14SP
Some of the features: * Quickly preview or jump to figures/references/equations/etc. (even if the PDF doesn't have links) * Search paper names in google scholar by middle clicking on their name * Searchable table of contents * Searchable highlights/bookmarks * Browser-like history navigation * Mark locations for quick navigation (Vim style) * Synctex support Video demo of some features: https://www.youtube.com/watch?v=yTmCI0Xp5vI
2022 · github.com
- 15TB
May 2026 · andreaturchet.github.io
- 16RA
2018 · semanticscholar.org
- 17AO
I built this yesterday to help understand papers I'm interested in. It's using the gemini 2.5 flash lite model, but you can run it yourself[1] and switch to 2.5 pro for better results. Happy to answer any questions or take suggestions on how I can improve it! 1. https://github.com/montanaflynn/asxiv
Sep 2025 · asxiv.org
- 18AS
So, I spend a ton of time on arXiv, like probably most of you. And while it's obviously amazing for keeping up with new papers, I always found the actual searching and browsing part a bit... clunky? Especially when you're trying to quickly figure out if a paper is even worth diving into. I got a bit fed up with it, so I ended up building this little web app called ArxivLens (https://arxivlens.com/). My main goal was to make it way quicker to skim papers and find what you're actually looking for. The big thing I added that I think is pretty useful is an AI overview feature.…
2025 · arxivlens.com
- 19
- 20
- 21
- 22DC
Uses hybrid semantic search (combination of dense embeddings and sparse vectors) to retrieve high quality answers across your documents. Features - Significantly faster than competition (Process a 200 page PDF in <5s) - Much better answer quality - Fast summarization tool - Beta API for end to end extractive document QA ([email protected]) Try it out (no login) - Llama 2 paper https://www.dankgpt.com/chat/346f444d-e286-4671-b157-540f4cb... - Scott Aaronson Quantum Information Science lectures…
2023 · dankgpt.com
- 23GA
I needed a way to grab a random paper from arXiv, so I built one and wanted to share it with you. It 1) picks a random topic (of all the cs., econ., math.* etc. topics) 2) finds the maximum amount of papers in that topic, and 3) queries for a random paper in that topic. Note that this skews the distribution heavily in favor of topics that are less common, but it should get the job done. Suggestions for improvements are welcome.
2025 · jepedersen.dk
- 24IV
Hey HN! This has been my project for a few years now. I recently brought it back to life after taking a pause to focus on my studies. My goal with this project is to separate fluff from science when shopping for supplements. I am doing this in 3 steps: 1.) I index every supplement on the market (extract each ingredient, normalize by quantity) 2.) I index every research paper on supplementation (rank every claim by effect type and effect size) 3.) I link data between supplements and research papers Earlier last year, I took pause on a project because I've ran into a few issues: Legal: Shady…
Jan 2026 · pillser.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →