Joshua Kazdan

According to our database, Joshua Kazdan authored at least 18 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2026

Consensus is Not Verification: Why Crowd Wisdom Strategies Fail for LLM Truthfulness.

Yegor Denisov-Blanch, Joshua Kazdan, Jessica Chudnovsky, Rylan Schaeffer, Sheng Guan, Soji Adeshina, Sanmi Koyejo

CoRR, March, 2026

Scale Dependent Data Duplication.

Joshua Kazdan, Noam Levi, Rylan Schaeffer, Jessica Chudnovsky, Abhay Puri, Bo He, Mehmet Donmez, Sanmi Koyejo, David L. Donoho

CoRR, March, 2026

Quantifying the Effect of Test Set Contamination on Generative Evaluations.

Rylan Schaeffer, Joshua Kazdan, Baber Abbasi, Ken Ziyu Liu, Brando Miranda, Ahmed Ahmed, Abhay Puri, Niloofar Mireshghallah, Sanmi Koyejo

CoRR, January, 2026

2025

Efficient Prediction of Pass@k Scaling in Large Language Models.

Joshua Kazdan, Rylan Schaeffer, Youssef Allouah, Colin Sullivan, Kyssen Yu, Noam Levi, Sanmi Koyejo

CoRR, October, 2025

Understanding Adversarial Transfer: Why Representation-Space Attacks Fail Where Data-Space Attacks Succeed.

Isha Gupta, Rylan Schaeffer, Joshua Kazdan, Ken Ziyu Liu, Sanmi Koyejo

CoRR, October, 2025

Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track.

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

CoRR, June, 2025

Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models.

Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch

CoRR, June, 2025

Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF.

Syrine Belakaria, Joshua Kazdan, Charles Marx, Chris Cundy, Willie Neiswanger, Sanmi Koyejo, Barbara E. Engelhardt, Stefano Ermon

CoRR, March, 2025

Position: Model Collapse Does Not Mean What You Think.

Rylan Schaeffer, Joshua Kazdan, Alvan Caleb Arulandu, Sanmi Koyejo

CoRR, March, 2025

No, of course I can! Refusal Mechanisms Can Be Exploited Using Harmless Fine-Tuning Data.

Joshua Kazdan, Lisa Yu, Rylan Schaeffer, Chris Cundy, Sanmi Koyejo, Dvijotham Krishnamurthy

CoRR, February, 2025

KGGen: Extracting Knowledge Graphs from Plain Text with Language Models.

Belinda Mo, Kyssen Yu, Joshua Kazdan, Proud Mpala, Lisa Yu, Chris Cundy, Charilaos I. Kanatsoulis, Sanmi Koyejo

CoRR, February, 2025

Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track.

Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch, Brando Miranda, Matthias Gerstgrasser, Susan Zhang, Andreas Haupt, Isha Gupta, Elyas Obbad, Jesse Dodge, Jessica Zosa Forde, Francesco Orabona, Sanmi Koyejo, David L. Donoho

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

How Do Large Language Monkeys Get Their Power (Laws)?

Rylan Schaeffer, Joshua Kazdan, John Hughes, Jordan Juravsky, Sara Price, Aengus Lynch, Erik Jones, Robert Kirk, Azalia Mirhoseini, Sanmi Koyejo

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World.

Joshua Kazdan, Rylan Schaeffer, Apratim Dey, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo

Proceedings of the Forty-second International Conference on Machine Learning, 2025

CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion.

Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Frederick Vu, Stefano Ermon

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning.

Youssef Allouah, Joshua Kazdan, Rachid Guerraoui, Sanmi Koyejo

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion.

Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Stefano Ermon

CoRR, 2024

2021

Spiders and their Kin: An Investigation of Stanley's Chromatic Symmetric Function for Spiders and Related Graphs.

Angèle M. Foley, Joshua Kazdan, Larissa Kröll, Sofía Martínez Alberga, Oleksii Melnyk, Alexander Tenenbaum

Graphs Comb., 2021