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09/01/2023
Baseline Defenses for Adversarial Attacks Against Aligned Language Models
As Large Language Models quickly become ubiquitous, it becomes critical ...
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06/29/2023
Seeing in Words: Learning to Classify through Language Bottlenecks
Neural networks for computer vision extract uninterpretable features des...
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06/28/2023
On the Exploitability of Instruction Tuning
Instruction tuning is an effective technique to align large language mod...
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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...
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06/07/2023
On the Reliability of Watermarks for Large Language Models
As LLMs become commonplace, machine-generated text has the potential to ...
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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...
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05/31/2023
Understanding and Mitigating Copying in Diffusion Models
Images generated by diffusion models like Stable Diffusion are increasin...
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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...
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05/30/2023
What Can We Learn from Unlearnable Datasets?
In an era of widespread web scraping, unlearnable dataset methods have t...
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04/24/2023
A Cookbook of Self-Supervised Learning
Self-supervised learning, dubbed the dark matter of intelligence, is a p...
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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...
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02/28/2023
Neural Auctions Compromise Bidder Information
Single-shot auctions are commonly used as a means to sell goods, for exa...
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02/14/2023
Universal Guidance for Diffusion Models
Typical diffusion models are trained to accept a particular form of cond...
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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...
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02/06/2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness
The robustness of a deep classifier can be characterized by its margins:...
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01/24/2023
A Watermark for Large Language Models
Potential harms of large language models can be mitigated by watermarkin...
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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...
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12/13/2022
What do Vision Transformers Learn? A Visual Exploration
Vision transformers (ViTs) are quickly becoming the de-facto architectur...
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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...
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11/29/2022
Robustness Disparities in Face Detection
Facial analysis systems have been deployed by large companies and critiq...
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10/23/2022
K-SAM: Sharpness-Aware Minimization at the Speed of SGD
Sharpness-Aware Minimization (SAM) has recently emerged as a robust tech...
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10/19/2022
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
As industrial applications are increasingly automated by machine learnin...
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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...
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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 ...
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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...
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08/19/2022
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
Standard diffusion models involve an image transform – adding Gaussian n...
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07/16/2022
Certified Neural Network Watermarks with Randomized Smoothing
Watermarking is a commonly used strategy to protect creators' rights to ...
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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...
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06/08/2022
Autoregressive Perturbations for Data Poisoning
The prevalence of data scraping from social media as a means to obtain d...
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04/19/2022
Poisons that are learned faster are more effective
Imperceptible poisoning attacks on entire datasets have recently been to...
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03/15/2022
A Deep Dive into Dataset Imbalance and Bias in Face Identification
As the deployment of automated face recognition (FR) systems proliferate...
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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...
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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...
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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...
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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...
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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 ...
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01/28/2022
Certifying Model Accuracy under Distribution Shifts
Certified robustness in machine learning has primarily focused on advers...
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01/25/2022
Are Commercial Face Detection Models as Biased as Academic Models?
As facial recognition systems are deployed more widely, scholars and act...
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01/03/2022
Execute Order 66: Targeted Data Poisoning for Reinforcement Learning
Data poisoning for reinforcement learning has historically focused on ge...
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11/25/2021
Active Learning at the ImageNet Scale
Active learning (AL) algorithms aim to identify an optimal subset of dat...
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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...
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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...
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10/26/2021
A Frequency Perspective of Adversarial Robustness
Adversarial examples pose a unique challenge for deep learning systems. ...
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10/26/2021
Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features
For supervised learning with tabular data, decision tree ensembles produ...
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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...
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10/15/2021
Comparing Human and Machine Bias in Face Recognition
Much recent research has uncovered and discussed serious concerns of bia...
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09/29/2021
Stochastic Training is Not Necessary for Generalization
It is widely believed that the implicit regularization of stochastic gra...
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09/09/2021
Towards Transferable Adversarial Attacks on Vision Transformers
Vision transformers (ViTs) have demonstrated impressive performance on a...
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08/27/2021
Robustness Disparities in Commercial Face Detection
Facial detection and analysis systems have been deployed by large compan...
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08/13/2021