
OpenScholarXIV
FOSS App to Discover and Research Papers
What it does
OpenScholarXIV is an open-source, aesthetic, minimal and AI powered app that allows users to search, read, bookmark, share, download and view summaries of academic papers from the arXiv repository.
Does the same job
all alternatives →- SAScholArxiv – an open-source, aesthetic, minimal research paper explorer2024 · github.com · ▲147
- AVArxiv Vanity – Read academic papers from Arxiv as responsive web pages2017 · arxiv-vanity.com · ▲721
- AArXivTok2025 · arxivtok.vercel.app · ▲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.
- BABulletpapers – ArXiv AI paper summarizer, won Anthropic Hackathon2023 · bulletpapers.ai · ▲178
- 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…
- DSDeep search of all ML papers2024 · app.undermind.ai · ▲109
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, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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