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Micah Goldblum

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

46

Venues

8

Active years

2020–2025

Best venue rank

A*

Where they publish

Papers

46 indexed papers, newest first.

YearVenueTitleAuthors
2025ICLRAdaptive Retention & Correction: Test-Time Training for Continual Learning.Haoran Chen, Micah Goldblum, Zuxuan Wu, Yu-Gang Jiang
2025ICLRStyle Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarking.Benjamin Feuer, Micah Goldblum, Teresa Datta, Sanjana Nambiar, Raz Besaleli, Samuel Dooley, Max Cembalest, John P. Dickerson
2025ICLRLiveBench: A Challenging, Contamination-Limited LLM Benchmark.Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha V. Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum
2025ICMLHidden No More: Attacking and Defending Private Third-Party LLM Inference.Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum, Arka Pal
2025NAACLLLM-Generated Passphrases That Are Secure and Easy to Remember.Jie S. Li, Jonas Geiping, Micah Goldblum, Aniruddha Saha, Tom Goldstein
2024ECCVInvestigating Style Similarity in Diffusion Models.Gowthami Somepalli, Anubhav Gupta, Kamal Gupta, Shramay Palta, Micah Goldblum, Jonas Geiping, Abhinav Shrivastava, Tom Goldstein
2024ICASSPIdentifying Attack-Specific Signatures in Adversarial Examples.Hossein Souri, Pirazh Khorramshahi, Chun Pong Lau, Micah Goldblum, Rama Chellappa
2024ICLRUniversal Guidance for Diffusion Models.Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024ICLRNEFTune: Noisy Embeddings Improve Instruction Finetuning.Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024ICLROn the Reliability of Watermarks for Large Language Models.John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
2024ICMLPosition: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning.Micah Goldblum, Marc Anton Finzi, Keefer Rowan, Andrew Gordon Wilson
2024ICMLSpotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text.Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024ICMLNon-Vacuous Generalization Bounds for Large Language Models.Sanae Lotfi, Marc Anton Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum, Andrew Gordon Wilson
2024ICMLCompute Better Spent: Replacing Dense Layers with Structured Matrices.Shikai Qiu, Andres Potapczynski, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson
2023AIESA Deep Dive into Dataset Imbalance and Bias in Face Identification.Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein
2023CVPRUniversal Guidance for Diffusion Models.Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023CVPRDiffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models.Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023ICASSPSTYX: Adaptive Poisoning Attacks Against Byzantine-Robust Defenses in Federated Learning.Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023ICLRLoss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent.Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023ICLRPanning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation.Hong-Min Chu, Jonas Geiping, Liam H. Fowl, Micah Goldblum, Tom Goldstein
2023ICLRDecepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models.Liam H. Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein
2023ICLRHow Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization.Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson
2023ICLRThe Lie Derivative for Measuring Learned Equivariance.Nate Gruver, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson
2023ICLRTransfer Learning with Deep Tabular Models.Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum
2023ICLRSeeing in Words: Learning to Classify through Language Bottlenecks.Khalid Saifullah, Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023ICLRCanary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries.Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023ICLRExploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness.Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang
2022AAAITowards Transferable Adversarial Attacks on Vision Transformers.Zhipeng Wei, Jingjing Chen, Micah Goldblum, Zuxuan Wu, Tom Goldstein, Yu-Gang Jiang
2022CVPRPoisons that are learned faster are more effective.Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
2022CVPRCan Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective.Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
2022ICLRRobbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models.Liam H. Fowl, Jonas Geiping, Wojciech Czaja, Micah Goldblum, Tom Goldstein
2022ICLRStochastic Training is Not Necessary for Generalization.Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein
2022ICLRThe Close Relationship Between Contrastive Learning and Meta-Learning.Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein
2022ICLRThe Uncanny Similarity of Recurrence and Depth.Avi Schwarzschild, Arjun Gupta, Amin Ghiasi, Micah Goldblum, Tom Goldstein
2022ICMLPlug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations.Amin Ghiasi, Hamid Kazemi, Steven Reich, Chen Zhu, Micah Goldblum, Tom Goldstein
2022ICMLBayesian Model Selection, the Marginal Likelihood, and Generalization.Sanae Lotfi, Pavel Izmailov, Gregory W. Benton, Micah Goldblum, Andrew Gordon Wilson
2022ICMLFishing for User Data in Large-Batch Federated Learning via Gradient Magnification.Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein
2021ICASSPStrong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff.Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
2021ICLRLowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition.Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P. Dickerson, Gavin Taylor, Tom Goldstein
2021ICLRThe Intrinsic Dimension of Images and Its Impact on Learning.Phillip Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
2021ICMLData Augmentation for Meta-Learning.Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein
2021ICMLJust How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks.Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P. Dickerson, Tom Goldstein
2020AAAIAdversarially Robust Distillation.Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein
2020ICASSPWitchcraft: Efficient PGD Attacks with Random Step Size.Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
2020ICLRTruth or backpropaganda? An empirical investigation of deep learning theory.Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein
2020ICMLUnraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks.Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein