Cook-Levin: The Ugly Underbelly is Good for Us
Theory
Boosting Fuzzer Efficiency: An Information Theoretic Perspective
In this paper, we take the fundamental perspective of fuzzing as a learning process.
Technical Perspective: What’s All the Fuss about Fuzzing?
"Boosting Fuzzer Efficiency: An Information Theoretic Perspective," by Marcel Böhme, Valentin J.M. Manès, and Sang Kil Cha, presents a novel twist to fuzzing that is shown to increase the central metric of the number of bugs found.
Generative AI as a New Innovation Platform
Generating and Exploiting Automated Reasoning Proof Certificates
Historic Algorithms Help Unlock Shortest-Path Problem Breakthrough
The Smallness of Large Language Models
Dilemma of the Artificial Intelligence Regulatory Landscape
Research for Practice: OS Scheduling
A Year Embedded in the Crypto-NFT Space
Model Counting Meets Distinct Elements
In this work, we seek to investigate whether bridging the seeming communication gap between two different domains of computer science may pave the way to richer fundamental insights.
Technical Perspective: Tapping the Link between Algorithmic Model Counting and Streaming
"Model Counting Meets Distinct Elements," by A. Pavan et al., gives a surprising connection between model counting and streaming, providing a generic transformation of data stream algorithms for F0 estimation to algorithms for model counting.
Machine Learning: The Road to Artificial Intelligence?
Computer-Assisted Proofs Take on Fluid Flow
For a More Transparent Governance of Open Source
SI and Binary Prefixes: Clearing the Confusion
The Principles of Data-Centric AI
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