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08/28/2023
Identifying and Mitigating the Security Risks of Generative AI
Every major technical invention resurfaces the dual-use dilemma – the ne...
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06/20/2023
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
Generative Pre-trained Transformer (GPT) models have exhibited exciting ...
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05/23/2023
Towards Automated Security Analysis of Smart Contracts based on Execution Property Graph
Identifying and mitigating vulnerabilities in smart contracts is crucial...
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12/20/2022
ThreatKG: A Threat Knowledge Graph for Automated Open-Source Cyber Threat Intelligence Gathering and Management
Despite the increased adoption of open-source cyber threat intelligence ...
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12/10/2022
Specular: Towards Trust-minimized Blockchain Execution Scalability with EVM-native Fraud Proofs
An optimistic rollup (ORU) enables refereed delegation of computation fr...
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08/11/2022
Going Incognito in the Metaverse
Virtual reality (VR) telepresence applications and the so-called "metave...
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07/21/2022
UniFed: A Benchmark for Federated Learning Frameworks
Federated Learning (FL) has become a practical and popular paradigm in m...
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05/14/2022
The Sky Above The Clouds
Technology ecosystems often undergo significant transformations as they ...
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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...
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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...
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03/05/2021
Measuring Mathematical Problem Solving With the MATH Dataset
Many intellectual endeavors require mathematical problem solving, but th...
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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...
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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...
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12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
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11/17/2019
REFIT: a Unified Watermark Removal Framework for Deep Learning Systems with Limited Data
Deep neural networks (DNNs) have achieved tremendous success in various ...
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07/23/2019
Keystone: A Framework for Architecting TEEs
Trusted execution environments (TEEs) are becoming a requirement across ...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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09/20/2018
Chorus: Differential Privacy via Query Rewriting
We present Chorus, a system with a novel architecture for providing diff...
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07/20/2018
Physical Adversarial Examples for Object Detectors
Deep neural networks (DNNs) are vulnerable to adversarial examples-malic...
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06/02/2018
GamePad: A Learning Environment for Theorem Proving
In this paper, we introduce a system called GamePad that can be used to ...
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02/22/2018
The Secret Sharer: Measuring Unintended Neural Network Memorization & Extracting Secrets
Machine learning models based on neural networks and deep learning are b...
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12/15/2017
Gradients explode - Deep Networks are shallow - ResNet explained
Whereas it is believed that techniques such as Adam, batch normalization...
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09/25/2017
