Sign up to save your podcasts
Or
Share [QA] MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
[QA] MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
MLE-bench is a benchmark for evaluating AI agents in machine learning engineering, featuring 75 Kaggle competitions and establishing human baselines, with open-source code for future research.
https://arxiv.org/abs//2410.07095
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
View all episodes
By Igor Melnyk
5
33 ratings
MLE-bench is a benchmark for evaluating AI agents in machine learning engineering, featuring 75 Kaggle competitions and establishing human baselines, with open-source code for future research.
https://arxiv.org/abs//2410.07095
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
More shows like Arxiv Papers
View all
Exchanges
960 Listeners
Odd Lots
1,930 Listeners
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
432 Listeners
The Daily
112,200 Listeners
All-In with Chamath, Jason, Sacks & Friedberg
9,925 Listeners
Hard Fork
5,512 Listeners
UnHerd with Freddie Sayers
211 Listeners
Unsupervised Learning with Jacob Effron
49 Listeners
Latent Space: The AI Engineer Podcast
93 Listeners
BG2Pod with Brad Gerstner and Bill Gurley
466 Listeners