activity
20182026
most citedLeakage and the Reproducibility Crisis in ML-based Science

141 citations · 297 across the 34 of their papers we have counts for

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12 papers · 1 filter

cs.LG2026

Births are difficult to predict even with rich survey and full-population register data

Elizaveta Sivak, Emily M. Cantrell, Thomas Emery +109

Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine one outcome - having a child w…

cs.LG2025

Bridging Prediction and Intervention Problems in Social Systems

Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou +32

Many automated decision systems (ADS) are designed to solve prediction problems -- where the goal is to learn patterns from a sample of the population and apply them to individuals…

cs.LG2024★ 1 cited

The Limits of Inference Scaling Through Resampling

Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan

Recent research has generated hope that inference scaling, such as resampling solutions until they pass verifiers like unit tests, could allow weaker models to match stronger ones.…

cs.LG2024★ 8 cited

The 2024 Foundation Model Transparency Index

Rishi Bommasani, Kevin Klyman, Sayash Kapoor +4

Foundation models are increasingly consequential yet extremely opaque. To characterize the status quo, the Foundation Model Transparency Index (FMTI) was launched in October 2023 t…

cs.LG2024★ 6 cited

AI Agents That Matter

Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel +2

AI agents are an exciting new research direction, and agent development is driven by benchmarks. Our analysis of current agent benchmarks and evaluation practices reveals several s…

cs.LG2024★ 4 cited

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources

Shayne Longpre, Stella Biderman, Alon Albalak +20

Foundation model development attracts a rapidly expanding body of contributors, scientists, and applications. To help shape responsible development practices, we introduce the Foun…