research
∙
09/01/2023
Baseline Defenses for Adversarial Attacks Against Aligned Language Models
As Large Language Models quickly become ubiquitous, it becomes critical ...
share
research
∙
06/29/2023
Seeing in Words: Learning to Classify through Language Bottlenecks
Neural networks for computer vision extract uninterpretable features des...
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...
research
∙
06/07/2023
On the Reliability of Watermarks for Large Language Models
As LLMs become commonplace, machine-generated text has the potential to ...
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...
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...
research
∙
01/24/2023
A Watermark for Large Language Models
Potential harms of large language models can be mitigated by watermarkin...
research
∙
10/19/2022
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
As industrial applications are increasingly automated by machine learnin...
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...
research
∙
05/05/2022
Surface Reconstruction from Point Clouds: A Survey and a Benchmark
Reconstruction of a continuous surface of two-dimensional manifold from ...
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...
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 ...
research
∙
09/27/2021
Machine Learning based Medical Image Deepfake Detection: A Comparative Study
Deep generative networks in recent years have reinforced the need for ca...
research
∙
12/14/2020
Sign-Agnostic Implicit Learning of Surface Self-Similarities for Shape Modeling and Reconstruction from Raw Point Clouds
Shape modeling and reconstruction from raw point clouds of objects stand...
research
∙
12/14/2020
Deep Optimized Priors for 3D Shape Modeling and Reconstruction
Many learning-based approaches have difficulty scaling to unseen data, a...
research
∙
11/15/2020
Towards Understanding the Regularization of Adversarial Robustness on Neural Networks
The problem of adversarial examples has shown that modern Neural Network...
research
∙
12/24/2019
Geometry-aware Generation of Adversarial and Cooperative Point Clouds
Recent studies show that machine learning models are vulnerable to adver...
research
∙
05/15/2019
