paper-impactfulness-embeddings

Paper Impactfulness Embeddings

This lab studies whether a paper's impactfulness can be measured or predicted from its position in embedding space.

The core idea is to embed papers, citations, metadata, and related scholarly signals, then analyze geometric features such as centrality, neighborhood structure, novelty, distance from prior work, and movement of later work toward a paper's region of the space.

Initial goals:

• Build reproducible paper embedding pipelines.
• Compare embedding-space features against downstream impact signals.
• Track whether influential papers occupy distinctive positions before their impact is fully visible.
• Document datasets, evaluation metrics, and limitations clearly enough for follow-up experiments.

This repository is currently a starting point for the lab setup. dogfood 2026-05-22T03:21:05Z