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2020 – today
- 2026
[i13]Rylan Schaeffer, Joshua Kazdan, Baber Abbasi, Ken Ziyu Liu, Brando Miranda, Ahmed Ahmed, Abhay Puri, Niloofar Mireshghallah, Sanmi Koyejo:
Quantifying the Effect of Test Set Contamination on Generative Evaluations. CoRR abs/2601.04301 (2026)- 2025
- [c4]Youssef Allouah, Joshua Kazdan, Rachid Guerraoui, Sanmi Koyejo:
The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning. ICLR 2025 - [c3]Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Frederick Vu, Stefano Ermon:
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion. ICLR 2025 - [c2]Joshua Kazdan, Rylan Schaeffer, Apratim Dey, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo:
Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World. ICML 2025 - [c1]Rylan Schaeffer, Joshua Kazdan, John Hughes, Jordan Juravsky, Sara Price, Aengus Lynch, Erik Jones, Robert Kirk, Azalia Mirhoseini, Sanmi Koyejo:
How Do Large Language Monkeys Get Their Power (Laws)? ICML 2025 - [i12]Belinda Mo, Kyssen Yu, Joshua Kazdan, Proud Mpala, Lisa Yu, Chris Cundy, Charilaos I. Kanatsoulis, Sanmi Koyejo:
KGGen: Extracting Knowledge Graphs from Plain Text with Language Models. CoRR abs/2502.09956 (2025) - [i11]Rylan Schaeffer, Joshua Kazdan, John Hughes, Jordan Juravsky, Sara Price, Aengus Lynch, Erik Jones, Robert Kirk, Azalia Mirhoseini, Sanmi Koyejo:
How Do Large Language Monkeys Get Their Power (Laws)? CoRR abs/2502.17578 (2025) - [i10]Joshua Kazdan, Lisa Yu, Rylan Schaeffer, Chris Cundy, Sanmi Koyejo, Dvijotham Krishnamurthy:
No, of course I can! Refusal Mechanisms Can Be Exploited Using Harmless Fine-Tuning Data. CoRR abs/2502.19537 (2025) - [i9]Rylan Schaeffer, Joshua Kazdan, Alvan Caleb Arulandu, Sanmi Koyejo:
Position: Model Collapse Does Not Mean What You Think. CoRR abs/2503.03150 (2025) - [i8]Syrine Belakaria, Joshua Kazdan, Charles Marx, Chris Cundy, Willie Neiswanger, Sanmi Koyejo, Barbara E. Engelhardt, Stefano Ermon:
Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF. CoRR abs/2503.22137 (2025) - [i7]Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch:
Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models. CoRR abs/2506.13681 (2025) - [i6]Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch, Brando Miranda, Matthias Gerstgrasser, Susan Zhang, Andreas Haupt, Isha Gupta, Elyas Obbad, Jesse Dodge, Jessica Zosa Forde, Koustuv Sinha, Francesco Orabona, Sanmi Koyejo, David L. Donoho:
Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track. CoRR abs/2506.19882 (2025) - [i5]Isha Gupta, Rylan Schaeffer, Joshua Kazdan, Ken Ziyu Liu, Sanmi Koyejo:
Understanding Adversarial Transfer: Why Representation-Space Attacks Fail Where Data-Space Attacks Succeed. CoRR abs/2510.01494 (2025) - [i4]Joshua Kazdan, Rylan Schaeffer, Youssef Allouah, Colin Sullivan, Kyssen Yu, Noam Levi, Sanmi Koyejo:
Efficient Prediction of Pass@k Scaling in Large Language Models. CoRR abs/2510.05197 (2025) - 2024
- [i3]Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Stefano Ermon:
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion. CoRR abs/2409.07025 (2024) - [i2]Joshua Kazdan, Rylan Schaeffer, Apratim Dey, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo:
Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World. CoRR abs/2410.16713 (2024) - [i1]Youssef Allouah
, Joshua Kazdan, Rachid Guerraoui, Sanmi Koyejo:
The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning. CoRR abs/2412.09119 (2024) - 2021
- [j1]Angèle M. Foley, Joshua Kazdan, Larissa Kröll, Sofía Martínez Alberga, Oleksii Melnyk, Alexander Tenenbaum:
Spiders and their Kin: An Investigation of Stanley's Chromatic Symmetric Function for Spiders and Related Graphs. Graphs Comb. 37(1): 87-110 (2021)
Coauthor Index
aka: Sanmi Koyejo
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