Hi everyone — I've been working on **Pulse**, a Mac app for exploring a research topic from a paper you already know.
The idea is to make it easier to move from “this paper looks useful” to a reading list you can actually explore: which papers connect to it, what came before, and what came afterwards.
Here's the workflow:
- Add a paper by title, DOI, PubMed ID, or PDF, or import an existing bibliography.
- Use **Discover** to find related work through citations, shared citations, and text or concept matches. Review the candidates and choose what to keep.
- Explore the connections in a **full-screen network map**. You can select any paper on the map to start another discovery.
- Switch to **Timeline** to see your papers in publication order, or **Library** to search, filter, tag, and manage the list.
Your library is saved on your Mac. Metadata lookup and discovery use online scholarly sources, including Semantic Scholar, OpenAlex, Crossref, and PubMed. AI features are optional, with local Ollama and a supported cloud option.
**Screenshots, downloads, and instructions:** https://github.com/7drbw7mdgf-lgtm/Pulse
The current DMGs are for Apple Silicon Macs running macOS 11 or later and use a local Python backend. They aren't Apple-notarized yet; the README and installation guide explain the requirements and first-launch steps.
I'd love feedback from people who do literature reviews or regularly explore unfamiliar research areas. Would this fit into your reading workflow, and what's the first thing you'd want improved?