
RAG Daily Papers
Generated-app
RAG Daily Papers launched on September 22, 2025 with 6 votes, #3,421 of 8,160 launches that month. The site was still online in September 2026, 1 year on.
What it does
RAG Daily Papers curates the latest Retrieval-Augmented Generation (RAG) research papers from arXiv. Updated daily with summaries for researchers, engineers, and AI enthusiasts
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Deep search of all ML papers2024 · app.undermind.ai · ▲109Built 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…

Talk to any ArXiv paper just by changing the URL2023 · github.com · ▲194Hello 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…
- IMI made a website to semantically search ArXiv papers2024 · papermatch.mitanshu.tech · ▲324
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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