DeepAI AI Chat
Log In Sign Up

Trends in Explainable AI (XAI) Literature

by   Alon Jacovi, et al.

The XAI literature is decentralized, both in terminology and in publication venues, but recent years saw the community converge around keywords that make it possible to more reliably discover papers automatically. We use keyword search using the SemanticScholar API and manual curation to collect a well-formatted and reasonably comprehensive set of 5199 XAI papers, available at . We use this collection to clarify and visualize trends about the size and scope of the literature, citation trends, cross-field trends, and collaboration trends. Overall, XAI is becoming increasingly multidisciplinary, with relative growth in papers belonging to increasingly diverse (non-CS) scientific fields, increasing cross-field collaborative authorship, increasing cross-field citation activity. The collection can additionally be used as a paper discovery engine, by retrieving XAI literature which is cited according to specific constraints (for example, papers that are influential outside of their field, or influential to non-XAI research).


page 5

page 6

page 10


Discovering seminal works with marker papers

Bibliometric information retrieval in databases can employ different str...

Geographic Citation Gaps in NLP Research

In a fair world, people have equitable opportunities to education, to co...

Trends at NIME – Reflections on Editing "A NIME Reader"

This paper provides an overview of the process of editing the forthcomin...

DRIFT: A Toolkit for Diachronic Analysis of Scientific Literature

In this work, we present to the NLP community, and to the wider research...

Embedding-based Scientific Literature Discovery in a Text Editor Application

Each claim in a research paper requires all relevant prior knowledge to ...

Code Repositories


Cross-field empirical trends analysis of XAI literature

view repo