A map of the latest 11 million papers split by semantic similarity and time slices [P]
Summary
A large-scale mapping of 11 million academic papers using semantic similarity and time-based slices, enabling analysis of research trends and connections.
Similar Articles
Interactive Semantic Flow Analysis of arXiv AI Papers from the Last 6 Months
TraceScope provides an interactive web-based tool for exploring semantic flows of recent AI papers from arXiv, with an open-source library available on GitHub.
SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research
SciAtlas is a large-scale, multi-disciplinary academic knowledge graph containing over 43 million papers and 3 billion triplets, designed to provide structured knowledge for AI-driven automated scientific research with a neuro-symbolic retrieval algorithm.
Exploring Academic Influence of Algorithms by Co-occurrence Network Based on Full-text of Academic Papers
This paper constructs large-scale algorithm co-occurrence networks from the full text of academic papers to study the collective influence of algorithms in NLP, finding that classic, high-performing, and intersectional algorithms hold central network positions.
The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale
This paper introduces the Scientific Contribution Graph, a large-scale resource containing 2 million scientific contributions extracted from 230k open-access papers connected by 12.5 million prerequisite edges, and formulates the task of automated technological roadmapping and prerequisite prediction.
Built a tool that maps research gaps from PDFs — beta, would love ML researchers to break it
The author introduces Papira, a beta tool that analyzes uploaded research papers to map coverage and identify gaps in machine learning and NLP subfields.