NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (25)

cs.LG2024

Large Scale Transfer Learning for Tabular Data via Language Modeling

Josh Gardner, Juan C. Perdomo, Ludwig Schmidt

cs.LG2021

Advances and Open Problems in Federated Learning

Peter Kairouz, H. Brendan McMahan, Brendan Avent +56

cs.CV2023

OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Anas Awadalla, Irena Gao, Josh Gardner +13

cs.LG2023

Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity

Josh Gardner, Renzhe Yu, Quan Nguyen +2

cs.CL2023

VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use

Yonatan Bitton, Hritik Bansal, Jack Hessel +6

cs.SD2022

Multi-instrument Music Synthesis with Spectrogram Diffusion

Curtis Hawthorne, Ian Simon, Adam Roberts +4

cs.CY2018

Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining

Josh Gardner, Yuming Yang, Ryan Baker +1

cs.SD2025

OLMoASR: Open Models and Data for Training Robust Speech Recognition Models

Huong Ngo, Matt Deitke, Martijn Bartelds +4

cs.SD2022

The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling

Yusong Wu, Josh Gardner, Ethan Manilow +3

cs.LG2023

Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation

Josh Gardner, Zoran Popović, Ludwig Schmidt

cs.SD2024

LLark: A Multimodal Instruction-Following Language Model for Music

Josh Gardner, Simon Durand, Daniel Stoller +1

stat.AP2018

Dropout Model Evaluation in MOOCs

Josh Gardner, Christopher Brooks

cs.CL2025

Language Models Improve When Pretraining Data Matches Target Tasks

David Mizrahi, Anders Boesen Lindbo Larsen, Jesse Allardice +7

stat.AP2019

Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments

Timothy NeCamp, Josh Gardner, Christopher Brooks

cs.LG2025

Apple Intelligence Foundation Language Models: Tech Report 2025

Ethan Li, Anders Boesen Lindbo Larsen, Chen Zhang +395

stat.AP2018

Evaluating Predictive Models of Student Success: Closing the Methodological Gap

Josh Gardner, Christopher Brooks

cs.SD2022

MT3: Multi-Task Multitrack Music Transcription

Josh Gardner, Ian Simon, Ethan Manilow +2

cs.SE2018

MORF: A Framework for Predictive Modeling and Replication At Scale With Privacy-Restricted MOOC Data

Josh Gardner, Christopher Brooks, Juan Miguel L. Andres +1

cs.CL2026

Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pretraining

Jeffrey Li, Josh Gardner, Doug Kang +10

cs.CY2018

Student Success Prediction in MOOCs

Josh Gardner, Christopher Brooks

eess.AS2025

Data-Centric Lessons To Improve Speech-Language Pretraining

Vishaal Udandarao, Zhiyun Lu, Xuankai Chang +6

cs.LG2024

Benchmarking Distribution Shift in Tabular Data with TableShift

Josh Gardner, Zoran Popovic, Ludwig Schmidt

cs.LG2025

DataComp-LM: In search of the next generation of training sets for language models

Jeffrey Li, Alex Fang, Georgios Smyrnis +56

cs.CY2020

Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data

Josh Gardner, Jawad Mroueh, Natalia Jenuwine +4

cs.CY2017

Driving with Data: Modeling and Forecasting Vehicle Fleet Maintenance in Detroit

Josh Gardner, Danai Koutra, Jawad Mroueh +4