Eliciting Black-Box Representations from LLMs through Self-Queries
Dylan Sam, Marc Finzi, and J. Zico Kolter
Under Review
Finetuning CLIP to Reason about Pairwise Differences
Dylan Sam, Devin Willmott, Joao D. Semedo, and J. Zico Kolter
Under Review
[pdf, code]
Understanding Prompt Engineering Does Not Require Rethinking Generalization
Victor Akinawade, Yiding Jiang, Dylan Sam, and J. Zico Kolter
International Conference on Learning Representations (ICLR), 2024
ICML Sampling and Optimization in Discrete Spaces, 2023 (Outstanding Paper)
[pdf]
Auditing Fairness under Unobserved Confounders
Yewon Byun, Dylan Sam, Michael Oberst, Zachary C. Lipton, and Bryan Wilder.
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
[pdf, code]
Bayesian Neural Networks with Domain Knowledge Priors
Dylan Sam*, Rattana Pukdee*, Daniel P. Jeong, Yewon Byun, and J. Zico Kolter
ICML Knowledge and Logical Reasoning Workshop, 2023 (Oral)
Under Review
[pdf, code]
Computing Low-Entropy Couplings for Large-Support Distributions
Samuel Sokota, Dylan Sam, Christian Schroeder de Witt, Spencer Compton, Jakob Nicolaus Foerster, and J. Zico Kolter
Conference on Uncertainty in Artificial Intelligence (UAI), 2024
[pdf, code]
Learning with Explanation Constraints
Dylan Sam*, Rattana Pukdee*, J. Zico Kolter, Maria-Florina Balcan, and Pradeep Ravikumar
Neural Information Processing Systems (NeurIPS), 2023
[pdf]
Label Propagation with Weak Supervision
Dylan Sam*, Rattana Pukdee*, Maria-Florina Balcan, and Pradeep Ravikumar
International Conference on Learning Representations (ICLR), 2023
[pdf,
code]
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
Dylan Sam and J. Zico Kolter
AAAI Conference on Artificial Intelligence, 2023
[pdf,
code]
Improving self-supervised representation learning via sequential adversarial masking
Dylan Sam, Min Bai, Tristan McKinney, and Li Erran Li
NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice, 2022
[pdf]
Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees
Alessio Mazzetto*, Cyrus Cousins*, Dylan Sam, Stephen H Bach, and Eli Upfal
International Conference on Machine Learning (ICML), 2021
[pdf,
code]
Semi-Supervised Aggregation of Dependent Weak Supervision Sources with Performance Guarantees
Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, and Stephen H Bach
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
[pdf,
code]
Learning from Dependent Weak Supervision Sources
Dylan Sam
Undergraduate Honors Thesis, 2021
[pdf]
Automated Data Accountability for the Mars Science Laboratory
Ryan Alimo, Dylan Sam, Dounia Lakhmiri, Brian Kahovec, and Dariush Divsalar
IEEE Aerospace Conference, 2021
[pdf,
code]
Hierarchical Clustering Analysis of Spectral Fingerprints for Cheminformatics
Dylan Sam and Brenda M Rubenstein
NeurIPS Machine Learning for Molecules Workshop, 2020
[pdf]