metadata

title: Inkling
emoji: 🌐
colorFrom: indigo
colorTo: yellow
python_version: 3.1
sdk: gradio
sdk_version: 5.23.1
app_file: app.py
pinned: true
license: agpl-3.0
short_description: Use AI to find obvious research links in unexpected places.
datasets:
  - nomadicsynth/arxiv-dataset-abstract-embeddings
models:
  - nomadicsynth/research-compass-arxiv-abstracts-embedding-model

Inkling: AI-assisted research discovery

Inkling is an AI-assisted tool that helps you discover meaningful connections between research papers — the kind of links a domain expert might spot, if they had time to read everything.

Rather than relying on superficial similarity or shared keywords, Inkling is trained to recognize reasoning-based relationships between papers. It evaluates conceptual, methodological, and application-level connections — even across disciplines — and surfaces links that may be overlooked due to the sheer scale of the research landscape.

This demo uses the first prototype of the model, trained on a dataset of 10,000+ rated abstract pairs, built from a larger pool of arXiv triplets. The system will continue to improve with feedback and will be released alongside the dataset for public research.

What it does

Accepts a research abstract, idea, or question
Searches for papers with deep, contextual relevance
Highlights key conceptual links and application overlaps
Offers reasoning-based analysis between selected papers
Gathers user feedback to improve the model over time

Why Inkling?

Because the right connection is often obvious — once someone points it out.

Researchers today are overwhelmed by volume. Inkling helps restore those missed-but-meaningful links between ideas, methods, and fields — links that could inspire new directions, clarify existing work, or enable cross-pollination across domains.

Status

Inkling is in alpha and under active development. The current model is hosted via Gradio, with a Hugging Face Space available for live interaction and feedback. Contributions, feedback, and collaboration are welcome.