LensKit 2026.1.0 arrived!
LensKit 2026.1.0 (Website; GitHub) has been released, and it is best understood as a continuation of the refactoring effort that reshaped the library in 2025....
ZenDNN v5.0: A Major Step Forward for Recommender Systems Researchers and Developers
On November 15, 2024, AMD released ZenDNN v5.0, the latest deep neural network library version. This update delivers hardware-specific optimizations, including support for Zen5 EPYC™...
‘Microsoft Recommenders’ + ‘Linux Foundation of AI and Data’ = ‘recommenders-team’
Microsoft Recommenders was introduced a few years ago, and it provided guidelines and a collection of software libraries relating to recommender systems. Today I found...
TorchRec, a new Recommender-Systems Library by PyTorch
The PyTorch team (and Meta.ai aka Facebook AI team) announced a new software library for recommender systems: TorchRec (GitHub). PyTorch is one of the major...
LensKit 0.14.0 released (“Cleaning Up”)
LensKit just announced on Twitter that they released a new version of LensKit, one of the most popular recommender-systems software libraries. It seems there were...
Zalando publishes its RESTful API and Event Guidelines
It’s a bit off-topic, but since APIs have some relevance for recommender systems, this is worthwhile news*: Zalando – one of the world’s largest fashion...
RecList: A RecSys software library for behavioral testing
Patrick John Chia, Jacopo Tagliabue, Federico Bianchi, Chloe He, and Brian Ko have released a new software library for recommender-systems testing. Source code is on...
Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation [Guest Post]
In the last decade, Recommendation Systems (RSs) have gained momentum as the pivotal choice for personalized decision-support systems. The recommendation task is essentially a retrieval...
Google AI releases ‘RecSim NG’, a “Flexible, Scalable, Differentiable Simulation of Recommender Systems”
One or two years ago, Google AI released RecSim — A Configurable Simulation Platform for Recommender Systems. Now, Martin Mladenov from Google AI announced the...
‘Spotify Confidence’: convenience wrappers around stat models various functions
Spotify released Spotify Confidence, which provides “convenience wrappers around stats model’s various functions for computing p-values and confidence intervals. With Spotify Confidence, it’s easy to...