b'Dawn Song'

research

∙ 08/11/2022

Going Incognito in the Metaverse

Virtual reality (VR) telepresence applications and the so-called "metave...

Vivek Nair, et al. ∙

research

∙ 08/10/2022

Multi-Factor Key Derivation Function (MFKDF)

We present the first general construction of a Multi-Factor Key Derivati...

Vivek Nair, et al. ∙

research

∙ 07/26/2022

Exploring the Unprecedented Privacy Risks of the Metaverse

Thirty study participants playtested an innocent-looking "escape room" g...

Vivek Nair, et al. ∙

research

∙ 07/21/2022

UniFed: A Benchmark for Federated Learning Frameworks

Federated Learning (FL) has become a practical and popular paradigm in m...

Xiaoyuan Liu, et al. ∙

research

∙ 07/19/2022

Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond

We consider vertical logistic regression (VLR) trained with mini-batch g...

Yuzheng Hu, et al. ∙

research

∙ 06/30/2022

Forecasting Future World Events with Neural Networks

Forecasting future world events is a challenging but valuable task. Fore...

Andy Zou, et al. ∙

research

∙ 05/24/2022

Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees

We propose Byzantine-robust federated learning protocols with nearly opt...

Banghua Zhu, et al. ∙

research

∙ 05/21/2022

DeepStruct: Pretraining of Language Models for Structure Prediction

We introduce a method for improving the structural understanding abiliti...

Chenguang Wang, et al. ∙

research

∙ 05/14/2022

The Sky Above The Clouds

Technology ecosystems often undergo significant transformations as they ...

Sarah Chasins, et al. ∙

research

∙ 01/19/2022

Shades of Finality and Layer 2 Scaling

Blockchains combine a distributed append-only log with a virtual machine...

Bennet Yee, et al. ∙

research

∙ 12/10/2021

Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models

Deep learning (DL) models, especially those large-scale and high-perform...

Jialuo Chen, et al. ∙

research

∙ 12/09/2021

PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures

In real-world applications of machine learning, reliable and safe system...

Dan Hendrycks, et al. ∙

research

∙ 11/05/2021

Grounded Graph Decoding Improves Compositional Generalization in Question Answering

Question answering models struggle to generalize to novel compositions o...

Yu Gai, et al. ∙

research

∙ 10/25/2021

What Would Jiminy Cricket Do? Towards Agents That Behave Morally

When making everyday decisions, people are guided by their conscience, a...

Dan Hendrycks, et al. ∙

research

∙ 09/23/2021

Zero-Shot Information Extraction as a Unified Text-to-Triple Translation

We cast a suite of information extraction tasks into a text-to-triple tr...

Chenguang Wang, et al. ∙

research

∙ 09/11/2021

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

Deep neural networks (DNNs) are vulnerable to adversarial noises, which ...

Shiyu Tang, et al. ∙

research

∙ 06/29/2021

Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages

Program synthesis from input-output examples has been a long-standing ch...

Xinyun Chen, et al. ∙

research

∙ 05/30/2021

FED-χ^2: Privacy Preserving Federated Correlation Test

In this paper, we propose the first secure federated χ^2-test protocol F...

Lun Wang, et al. ∙

research

∙ 05/26/2021

Differentially Private Frequency Moments Estimation with Polylogarithmic Space

We prove that 𝔽_p sketch, a well-celebrated streaming algorithm for freq...

Lun Wang, et al. ∙

research

∙ 05/20/2021

Measuring Coding Challenge Competence With APPS

While programming is one of the most broadly applicable skills in modern...

Dan Hendrycks, et al. ∙

research

∙ 05/02/2021

BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning

Recent research has confirmed the feasibility of backdoor attacks in dee...

Lun Wang, et al. ∙

research

∙ 03/30/2021

Model-Contrastive Federated Learning

Federated learning enables multiple parties to collaboratively train a m...

Qinbin Li, et al. ∙

research

∙ 03/05/2021

Measuring Mathematical Problem Solving With the MATH Dataset

Many intellectual endeavors require mathematical problem solving, but th...

Dan Hendrycks, et al. ∙

research

∙ 03/02/2021

DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing

Deep learning techniques have achieved remarkable performance in wide-ra...

Wenxiao Wang, et al. ∙

research

∙ 01/19/2021

A System for Automated Open-Source Threat Intelligence Gathering and Management

To remain aware of the fast-evolving cyber threat landscape, open-source...

Peng Gao, et al. ∙

research

∙ 01/17/2021

A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence

Log-based cyber threat hunting has emerged as an important solution to c...

Peng Gao, et al. ∙

research

∙ 12/18/2020

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

As machine learning systems grow in scale, so do their training data req...

Micah Goldblum, et al. ∙

research

∙ 12/14/2020

Extracting Training Data from Large Language Models

It has become common to publish large (billion parameter) language model...

Nicholas Carlini, et al. ∙

research

∙ 12/09/2020

PrivFramework: A System for Configurable and Automated Privacy Policy Compliance

Today's massive scale of data collection coupled with recent surges of c...

Usmann Khan, et al. ∙

research

∙ 12/03/2020

Towards Defending Multiple Adversarial Perturbations via Gated Batch Normalization

There is now extensive evidence demonstrating that deep neural networks ...

Aishan Liu, et al. ∙

research

∙ 11/19/2020

Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams

Adversarial examples are a widely studied phenomenon in machine learning...

Chawin Sitawarin, et al. ∙

research

∙ 10/26/2020

Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence

Log-based cyber threat hunting has emerged as an important solution to c...

Peng Gao, et al. ∙

research

∙ 10/22/2020

Language Models are Open Knowledge Graphs

This paper shows how to construct knowledge graphs (KGs) from pre-traine...

Chenguang Wang, et al. ∙

research

∙ 10/02/2020

F2ED-Learning: Good Fences Make Good Neighbors

In this paper, we present F2ED-Learning, the first federated learning pr...

Lun Wang, et al. ∙

research

∙ 10/02/2020

Model-Agnostic Round-Optimal Federated Learning via Knowledge Transfer

Federated learning enables multiple parties to collaboratively learn a m...

Qinbin Li, et al. ∙

research

∙ 09/14/2020

A Principled Approach to Data Valuation for Federated Learning

Federated learning (FL) is a popular technique to train machine learning...

Tianhao Wang, et al. ∙

research

∙ 09/07/2020

Measuring Massive Multitask Language Understanding

We propose a new test to measure a text model's multitask accuracy. The ...

Dan Hendrycks, et al. ∙

research

∙ 08/15/2020

Compositional Generalization via Neural-Symbolic Stack Machines

Despite achieving tremendous success, existing deep learning models have...

Xinyun Chen, et al. ∙

research

∙ 08/05/2020

Aligning AI With Shared Human Values

We show how to assess a language model's knowledge of basic concepts of ...

Dan Hendrycks, et al. ∙

research

∙ 07/16/2020

Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis

The use of deep learning techniques has achieved significant progress fo...

Kavi Gupta, et al. ∙

research

∙ 07/05/2020

BeeTrace: A Unified Platform for Secure Contact Tracing that Breaks Data Silos

Contact tracing is an important method to control the spread of an infec...

Xiaoyuan Liu, et al. ∙

research

∙ 06/29/2020

The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization

We introduce three new robustness benchmarks consisting of naturally occ...

Dan Hendrycks, et al. ∙

research

∙ 06/15/2020

Towards practical differentially private causal graph discovery

Causal graph discovery refers to the process of discovering causal relat...

Lun Wang, et al. ∙

research

∙ 04/30/2020

Imitation Attacks and Defenses for Black-box Machine Translation Systems

We consider an adversary looking to steal or attack a black-box machine ...

Eric Wallace, et al. ∙

research

∙ 04/28/2020

Epione: Lightweight Contact Tracing with Strong Privacy

Contact tracing is an essential tool in containing infectious diseases s...

Ni Trieu, et al. ∙

research

∙ 04/13/2020

Pretrained Transformers Improve Out-of-Distribution Robustness

Although pretrained Transformers such as BERT achieve high accuracy on i...

Dan Hendrycks, et al. ∙

research

∙ 03/16/2020

Anomalous Instance Detection in Deep Learning: A Survey

Deep Learning (DL) is vulnerable to out-of-distribution and adversarial ...

Saikiran Bulusu, et al. ∙

research

∙ 01/15/2020

Proceedings of the AAAI-20 Workshop on Intelligent Process Automation (IPA-20)

This is the Proceedings of the AAAI-20 Workshop on Intelligent Process A...

Dell Zhang, et al. ∙

research

∙ 12/29/2019

Hierarchical Variational Imitation Learning of Control Programs

Autonomous agents can learn by imitating teacher demonstrations of the i...

Roy Fox, et al. ∙

research

∙ 12/27/2019

Synthetic Datasets for Neural Program Synthesis

The goal of program synthesis is to automatically generate programs in a...

Richard Shin, et al. ∙

Dawn Song

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