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AI · October 21, 2025

arXivSub

AI-assisted research paper searching tool

What it does

arXivSub is an AI-powered research assistant that automatically collects the latest arXiv CS papers and conference papers: CVPR/ICCV/ICML/ICLR/NeurIPS/AAAI/MICCAI, generates multi-dimensional AI summaries, supports keyword filtering, and trend analytics.

Does a similar job

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    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…

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    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…

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    Hey HN! I've always found it hard to keep up with the latest AI research, so I built Arxiv Feed! https:&#x2F;&#x2F;arxiv-feed.vercel.app&#x2F; It's basically a feed of AI research papers + a one-liner explaining what problem its solving, etc. You can also click on any paper to get a TL;DR. Right now, I've only indexed a few hundred large language model papers, but will expand to indexing AI papers in other topics. Thinking of also adding a way for people to up-vote&#x2F;down-vote papers. Would love to hear any thoughts&#x2F;feedback! :D Thanks!

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