PaperPop - Journal Impact & Ranking
Your AI Co-Pilot for Academic Research
What it does
🆓 Free Chrome extension; 🏷️ Journal info auto-display — Impact factor and quartiles on 20+ sites (Google Scholar, PubMed, ScienceDirect…) 📊 100+ ranking systems — SCI/SSCI, CiteScore, Nature Index, and more 🤖 AI triple-pack — Search-result analysis, abstract interpretation, mind maps with role depth 🔗 DOI direct + Excel export — Configure Sci-Hub prefix to grab full text in one click
Does the same job
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- IVI've been using AI to analyze every supplement on the marketJan 2026 · pillser.com · ▲94
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…
- SYScholium, Your Own Research Assistant2025 · github.com · ▲23
I built an AI-powered research agent designed to efficiently discover, summarize, and cite relevant academic papers based on user queries. As a university student, I've written my share of essays and have also served as a copy editor for our student newspaper. During fact-checking, I noticed that Google often prioritizes unreliable and unscholarly resources—such as Medium articles, Reddit posts, and LinkedIn content—in its top results over scholarly ones. For instance, searching "Transformers" yields six blogs and articles before finally listing the Vaswani (2017) paper. This makes gathering…
- WBWe built a modern research paper readerOct 2025 · ontosyn.com · ▲11
Over the past year, we’ve been frustrated with how clunky it is to manage research papers. So we built Ontosyn, a modern research paper reader, with clean ui, better in paper navigation (bookmarks, jumping back up after clicking on a reference), an integrated ai chat with useful tools such as recommending relevant papers that you can directly add to your library, and, of course, library functionality to keep everything organized. We launched a closed alpha last week, and our first users are quite pleased with it. One user asked for author-based search for paper recommendations yesterday, and…
More ai this month
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
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…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com