# EvalRS 2023. Well-Rounded Recommender Systems For Real-World Deployments

arXiv: https://arxiv.org/abs/2304.07145 · HTML: https://mlsanity.com/paper/2304.07145/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2023.

## Built on by (most cited first, 1 of 1)

- [Bridging Offline-Online Evaluation with a Time-dependent and Popularity Bias-free Offline Metric for Recommenders](https://mlsanity.com/paper/2308.06885/) (2023)

## Abstract (arXiv)

EvalRS aims to bring together practitioners from industry and academia to foster a debate on rounded evaluation of recommender systems, with a focus on real-world impact across a multitude of deployment scenarios. Recommender systems are often evaluated only through accuracy metrics, which fall short of fully characterizing their generalization capabilities and miss important aspects, such as fairness, bias, usefulness, informativeness. This workshop builds on the success of last year's workshop at CIKM, but with a broader scope and an interactive format.