Kuchnik, Michael

5 publications

ICLR 2026 How Text Quality Interventions Reshape Neural Scaling Laws for LLMs: Empirical Study Newsha Ardalani, Feiyang Kang, Michael Kuchnik, Mostafa Elhoushi, Shubhabrata Sengupta, Shang-Wen Li, Carole-Jean Wu

ICLR 2026 Quagmires in SFT-RL Post-Training: When High SFT Scores Mislead and What to Use Instead Feiyang Kang, Michael Kuchnik, Karthik Padthe, Marin Vlastelica, Ruoxi Jia, Carole-Jean Wu, Newsha Ardalani

NeurIPS 2025 AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-Bench Edan Toledo, Karen Hambardzumyan, Martin Josifoski, Rishi Hazra, Nicolas Baldwin, Alexis Audran-Reiss, Michael Kuchnik, Despoina Magka, Minqi Jiang, Alisia Maria Lupidi, Andrei Lupu, Roberta Raileanu, Tatiana Shavrina, Kelvin Niu, Jean-Christophe Gagnon-Audet, Michael Shvartsman, Shagun Sodhani, Alexander H Miller, Abhishek Charnalia, Derek Dunfield, Carole-Jean Wu, Pontus Stenetorp, Nicola Cancedda, Jakob Nicolaus Foerster, Yoram Bachrach

NeurIPS 2024 Croissant: A Metadata Format for ML-Ready Datasets Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Luca Foschini, Pieter Gijsbers, Joan Giner-Miguelez, Sujata Goswami, Nitisha Jain, Michalis Karamousadakis, Satyapriya Krishna, Michael Kuchnik, Sylvain Lesage, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Hamidah Oderinwale, Pierre Ruyssen, Tim Santos, Rajat Shinde, Elena Simperl, Arjun Suresh, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Susheel Varma, Jos van der Velde, Steffen Vogler, Carole-Jean Wu, Luyao Zhang

ICLR 2019 Efficient Augmentation via Data Subsampling Michael Kuchnik, Virginia Smith