arXiv AI

From Stochastic to Stable: Rank Stability and Structural Sufficiency in AI Visibility Measurement

arXiv:2607. 10341v1 Announce Type: cross Abstract: AI visibility measurement is comparative: practitioners want to know which domains generative search engines cite most often and whether observed differences are large enough to support decisions.

arXiv Computation and Language
Sep 15

CITECHOICE: A Causal Audit of How Document Presentation Redistributes Citation Credit in Agentic Search

CITECHOICE is a causal audit that examines how the presentation of documents in an agentic search engine redistributes citation credit. Using 129 everyday‑query transcripts, the study compares structured versus prose renderings of the same source while keeping all other transcript elements fixed. The results show that structured rendering increases the target’s citation count by about half a citation per answer without adding total citations or diminishing competitors’ credit, while also revealing that rank position has a larger effect on citation rates than presentation order alone.

By Sriram Selvam, Anneswa Ghosh
arXiv AI
Sep 12

Benchmark Radar: A Living Database and Search Engine for AI Benchmarks and Evaluation

Benchmark Radar is a living database and search engine that aggregates AI benchmark papers, datasets, code, and score histories. It automatically discovers new benchmark resources from 37 sources, maintains a catalog of 1,283 records with 12,916 numeric observations, and provides tools such as a web dashboard, CLI, and downloadable evidence for researchers. The system also offers visualizations like a Pareto frontier and trend views to help users assess benchmark saturation and adoption.

By Koutian Wu, Junjie Zhou, Ergan Shang, Jiayu Wang, Pengqian Han, Junkai Wang, Wanghan Xu