Talking about Large Language Models
It is a serious mistake to apply to AI systems the same intuitions that we deploy in our dealings with each other.
Research and Advances
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Energy and Emissions of Machine Learning on Smartphones vs. the Cloud
An extensive study from Google finds machine-learning training in the cloud can significantly reduce carbon footprints.
Inherent Limitations of AI Fairness
AI fairness should not be considered a panacea: It may have the potential to make society more fair than ever, but it needs critical thought and outside help to make it…
Nonverbal Communication through Expressive Objects
In this work, we work closely with an AAC user to understand how motion through a physical expressive object can support their communication.
The User as a Key Ingredient in AAC Design
"Nonverbal Communication through Expressive Objects," by Stephanie Valencia et al., describes the design of a physical object to support communication and focuses on the…
Shortcut Learning of Large Language Models in Natural Language Understanding
Shortcuts often hinder the robustness of large language models.
On Specifying for Trustworthiness
As autonomous systems increasingly become part of our lives, it is crucial to foster trust between humans and these systems, to ensure positive outcomes and mitigate…
What Should We Do when Our Ideas of Fairness Conflict?
Standards for fair decision making could help us develop algorithms that comport with our consensus views; however, algorithmic fairness has its limits.
10 Things Software Developers Should Learn about Learning
Understanding how human memory and learning works, the differences between beginners and experts, and practical steps developers can take to improve their learning,…
Understanding and handling interference across multiple active cameras.
Theoretical Analysis of Edit Distance Algorithms
To what extent have the techniques for theoretical analysis of edit distance algorithms achieved their goals?
Data Analytics Anywhere and Everywhere
Mobile, ubiquitous, and immersive computing appear poised to transform visualization, data science, and data-driven decision making.
Maximum Flow Through a Network: A Storied Problem and a Groundbreaking Solution
“Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow,” by Li Chen et al., comes within striking distance of answering the question: “Does maximum…
Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow
We present an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with m edges and polynomially bounded integral demands, costs, and…
Informatics Higher Education in Europe: A Data Portal and Case Study
A discussion on the need for coordinated, governed, data-driven computing education initiatives of the future.
Scrambled Features for Breakfast: Concepts of Agile Language Development
Describing a framework to support simpler development of languages best suited to express the problems and solutions of each particular domain.
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…
Technical Perspective: A Rare Glimpse of Tracking Fake Reviews
"Leveraging Social Media to Buy Fake Reviews," by Sherry He et al., represents a breakthrough in our empirical understanding of fake reviews on Amazon.
"Locating Everyday Objects Using NFC Textiles," by Jingxian Wang et al., describes the potential of Near-Field Communication for advanced home automation.
Low-code has the potential to empower more people to automate tasks by creating computer programs.
Show It or Tell It? Text, Visualization, and Their Combination
When communicating information, language should be considered as co-equal with visualization.
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