b'Tom Goldstein'

research

∙ 09/01/2023

Baseline Defenses for Adversarial Attacks Against Aligned Language Models

As Large Language Models quickly become ubiquitous, it becomes critical ...

0 Neel Jain, et al. ∙

research

∙ 06/29/2023

Seeing in Words: Learning to Classify through Language Bottlenecks

Neural networks for computer vision extract uninterpretable features des...

0 Khalid Saifullah, et al. ∙

research

∙ 06/28/2023

On the Exploitability of Instruction Tuning

Instruction tuning is an effective technique to align large language mod...

0 Manli Shu, et al. ∙

research

∙ 06/23/2023

Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

With the rise of Large Language Models (LLMs) and their ubiquitous deplo...

1 Neel Jain, et al. ∙

research

∙ 06/07/2023

On the Reliability of Watermarks for Large Language Models

As LLMs become commonplace, machine-generated text has the potential to ...

5 John Kirchenbauer, et al. ∙

research

∙ 06/05/2023

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models

Large language models (LLMs) are instruction followers, but it can be ch...

0 Lichang Chen, et al. ∙

research

∙ 05/31/2023

Understanding and Mitigating Copying in Diffusion Models

Images generated by diffusion models like Stable Diffusion are increasin...

0 Gowthami Somepalli, et al. ∙

research

∙ 05/31/2023

Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust

Watermarking the outputs of generative models is a crucial technique for...

0 Yuxin Wen, et al. ∙

research

∙ 05/30/2023

What Can We Learn from Unlearnable Datasets?

In an era of widespread web scraping, unlearnable dataset methods have t...

0 Pedro Sandoval Segura, et al. ∙

research

∙ 04/24/2023

A Cookbook of Self-Supervised Learning

Self-supervised learning, dubbed the dark matter of intelligence, is a p...

0 Randall Balestriero, et al. ∙

research

∙ 04/05/2023

JPEG Compressed Images Can Bypass Protections Against AI Editing

Recently developed text-to-image diffusion models make it easy to edit o...

0 Pedro Sandoval Segura, et al. ∙

research

∙ 02/28/2023

Neural Auctions Compromise Bidder Information

Single-shot auctions are commonly used as a means to sell goods, for exa...

0 Alex Stein, et al. ∙

research

∙ 02/14/2023

Universal Guidance for Diffusion Models

Typical diffusion models are trained to accept a particular form of cond...

0 Arpit Bansal, et al. ∙

research

∙ 02/07/2023

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

The strength of modern generative models lies in their ability to be con...

12 Yuxin Wen, et al. ∙

research

∙ 02/06/2023

Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness

The robustness of a deep classifier can be characterized by its margins:...

1 Yuancheng Xu, et al. ∙

research

∙ 01/24/2023

A Watermark for Large Language Models

Potential harms of large language models can be mitigated by watermarkin...

3 John Kirchenbauer, et al. ∙

research

∙ 12/28/2022

Cramming: Training a Language Model on a Single GPU in One Day

Recent trends in language modeling have focused on increasing performanc...

0 Jonas Geiping, et al. ∙

research

∙ 12/13/2022

What do Vision Transformers Learn? A Visual Exploration

Vision transformers (ViTs) are quickly becoming the de-facto architectur...

0 Amin Ghiasi, et al. ∙

research

∙ 12/07/2022

Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models

Cutting-edge diffusion models produce images with high quality and custo...

0 Gowthami Somepalli, et al. ∙

research

∙ 11/29/2022

Robustness Disparities in Face Detection

Facial analysis systems have been deployed by large companies and critiq...

0 Samuel Dooley, et al. ∙

research

∙ 10/23/2022

K-SAM: Sharpness-Aware Minimization at the Speed of SGD

Sharpness-Aware Minimization (SAM) has recently emerged as a robust tech...

0 Renkun Ni, et al. ∙

research

∙ 10/19/2022

Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries

As industrial applications are increasingly automated by machine learnin...

0 Yuxin Wen, et al. ∙

research

∙ 10/17/2022

Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning

Federated learning is particularly susceptible to model poisoning and ba...

6 Yuxin Wen, et al. ∙

research

∙ 10/12/2022

How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization

Despite the clear performance benefits of data augmentations, little is ...

0 Jonas Geiping, et al. ∙

research

∙ 09/15/2022

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

Pre-trained vision-language models (e.g., CLIP) have shown promising zer...

29 Manli Shu, et al. ∙

research

∙ 08/19/2022

Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise

Standard diffusion models involve an image transform – adding Gaussian n...

12 Arpit Bansal, et al. ∙

research

∙ 07/16/2022

Certified Neural Network Watermarks with Randomized Smoothing

Watermarking is a commonly used strategy to protect creators' rights to ...

2 Arpit Bansal, et al. ∙

research

∙ 06/16/2022

A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features

Graph Neural Networks (GNNs) with numerical node features and graph stru...

0 Jiuhai Chen, et al. ∙

research

∙ 06/08/2022

Autoregressive Perturbations for Data Poisoning

The prevalence of data scraping from social media as a means to obtain d...

0 Pedro Sandoval Segura, et al. ∙

research

∙ 04/19/2022

Poisons that are learned faster are more effective

Imperceptible poisoning attacks on entire datasets have recently been to...

9 Pedro Sandoval Segura, et al. ∙

research

∙ 03/15/2022

A Deep Dive into Dataset Imbalance and Bias in Face Identification

As the deployment of automated face recognition (FR) systems proliferate...

13 Valeriia Cherepanova, et al. ∙

research

∙ 03/15/2022

Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective

We discuss methods for visualizing neural network decision boundaries an...

0 Gowthami Somepalli, et al. ∙

research

∙ 02/11/2022

End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking

Machine learning systems perform well on pattern matching tasks, but the...

4 Arpit Bansal, et al. ∙

research

∙ 02/01/2022

Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Federated learning (FL) has rapidly risen in popularity due to its promi...

0 Yuxin Wen, et al. ∙

research

∙ 01/31/2022

Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations

Existing techniques for model inversion typically rely on hard-to-tune r...

0 Amin Ghiasi, et al. ∙

research

∙ 01/29/2022

Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models

A central tenet of Federated learning (FL), which trains models without ...

0 Liam Fowl, et al. ∙

research

∙ 01/28/2022

Certifying Model Accuracy under Distribution Shifts

Certified robustness in machine learning has primarily focused on advers...

0 Aounon Kumar, et al. ∙

research

∙ 01/25/2022

Are Commercial Face Detection Models as Biased as Academic Models?

As facial recognition systems are deployed more widely, scholars and act...

6 Samuel Dooley, et al. ∙

research

∙ 01/03/2022

Execute Order 66: Targeted Data Poisoning for Reinforcement Learning

Data poisoning for reinforcement learning has historically focused on ge...

0 Harrison Foley, et al. ∙

research

∙ 11/25/2021

Active Learning at the ImageNet Scale

Active learning (AL) algorithms aim to identify an optimal subset of dat...

0 Zeyad Ali Sami Emam, et al. ∙

research

∙ 10/29/2021

Joint Channel Estimation and Data Detection in Cell-Free Massive MU-MIMO Systems

We propose a joint channel estimation and data detection (JED) algorithm...

0 Haochuan Song, et al. ∙

research

∙ 10/27/2021

VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization

Most state-of-the-art Graph Neural Networks (GNNs) can be defined as a f...

31 Mucong Ding, et al. ∙

research

∙ 10/26/2021

A Frequency Perspective of Adversarial Robustness

Adversarial examples pose a unique challenge for deep learning systems. ...

0 Shishira R Maiya, et al. ∙

research

∙ 10/26/2021

Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features

For supervised learning with tabular data, decision tree ensembles produ...

4 Jiuhai Chen, et al. ∙

research

∙ 10/25/2021

Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models

Federated learning has quickly gained popularity with its promises of in...

0 Liam Fowl, et al. ∙

research

∙ 10/15/2021

Comparing Human and Machine Bias in Face Recognition

Much recent research has uncovered and discussed serious concerns of bia...

17 Samuel Dooley, et al. ∙

research

∙ 09/29/2021

Stochastic Training is Not Necessary for Generalization

It is widely believed that the implicit regularization of stochastic gra...

0 Jonas Geiping, et al. ∙

research

∙ 09/09/2021

Towards Transferable Adversarial Attacks on Vision Transformers

Vision transformers (ViTs) have demonstrated impressive performance on a...

0 Zhipeng Wei, et al. ∙

research

∙ 08/27/2021

Robustness Disparities in Commercial Face Detection

Facial detection and analysis systems have been deployed by large compan...

9 Samuel Dooley, et al. ∙

research

∙ 08/13/2021

Datasets for Studying Generalization from Easy to Hard Examples

We describe new datasets for studying generalization from easy to hard e...

0 Avi Schwarzschild, et al. ∙

Tom Goldstein

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