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To extract value from evergrowing volumes of data, coming from a number of different sources, and to drive decision making, organizations frequently resort to the composition of data processing workflows, since they are expressive,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-12-13 Sérgio Esteves , Helena Galhardas , Luís Veiga

This paper is about the possible negative impact of excessive collaboration on the performance of top employees. With the rise of participatory culture and developments in communications technology, management practices require greater…

Applications · Statistics 2020-04-29 Anna Velyka , Marco Guerzoni

LLMs are increasingly deployed in autonomous laboratories, under the assumption that their domain priors and reasoning over iterative feedback let them converge on good designs in fewer iterations than feedback-only baselines. Current…

Machine Learning · Computer Science 2026-05-18 Marilyn Zhang , Tianfeng Chen , Fabián Barzuna , Ankita Rathod , Mark E. Whiting

Job rotation is a managerial practice to be applied in the organizational environment to reduce job monotony, boredom, and exhaustion resulting from job simplification, specialization, and repetition. Previous studies have identified and…

Differential replication through copying refers to the process of replicating the decision behavior of a machine learning model using another model that possesses enhanced features and attributes. This process is relevant when external…

Machine Learning · Computer Science 2023-02-08 Nahuel Statuto , Irene Unceta , Jordi Nin , Oriol Pujol

Generative AI brings novel and impressive abilities to help people in everyday tasks. There are many AI workflows that solve real and complex problems by chaining AI outputs together with human interaction. Although there is an undeniable…

Human-Computer Interaction · Computer Science 2024-06-03 Tao Long , Katy Ilonka Gero , Lydia B. Chilton

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization. Synthesis of a new material is typically followed by a set of characterization methods aiming to provide feedback for optimization or…

Expertise is often built by learning from examples. This process, known as schema induction, helps us identify patterns from examples. Despite its importance, schema induction remains a challenging cognitive task. Recent advances in…

Human-Computer Interaction · Computer Science 2025-02-24 Sitong Wang , Lydia B. Chilton

Optimal design is a critical yet challenging task within many applications. This challenge arises from the need for extensive trial and error, often done through simulations or running field experiments. Fortunately, sequential optimal…

Machine Learning · Computer Science 2025-03-25 Xubo Yue , Raed Al Kontar , Albert S. Berahas , Yang Liu , Blake N. Johnson

Human computation refers to the outsourcing of computation tasks to human workers. It offers a new direction for solving a variety of problems and calls for innovative ways of managing human computation processes. The majority of human…

Human-Computer Interaction · Computer Science 2012-04-17 Lu Xiao

Background: Multitasking is usual in software development. It is the ability to stop working on a task, switch to another, and return eventually to the first one, as needed or as scheduled. Multitasking, however, comes at a cognitive cost:…

Software Engineering · Computer Science 2020-06-24 Karina Kohl , Bogdan Vasilescu , Rafael Prikladnicki

Scientific progress depends on the continual generation of innovative re-search ideas. However, the rapid growth of scientific literature has greatly increased the cost of knowledge filtering, making it harder for researchers to identify…

Computation and Language · Computer Science 2026-04-23 Shuai Chen , Chengzhi Zhang

Context: Test-driven development (TDD) is an agile software development approach that has been widely claimed to improve software quality. However, the extent to which TDD improves quality appears to be largely dependent upon the…

Development of machine learning (ML) workflows is a tedious process of iterative experimentation: developers repeatedly make changes to workflows until the desired accuracy is attained. We describe our vision for a "human-in-the-loop" ML…

Databases · Computer Science 2018-04-18 Doris Xin , Litian Ma , Jialin Liu , Stephen Macke , Shuchen Song , Aditya Parameswaran

Budgetary constraints force organizations to pursue only a subset of possible innovation projects. Identifying which subset is most promising is an error-prone exercise, and involving multiple decision makers may be prudent. This raises the…

Theoretical Economics · Economics 2025-10-21 Lucas Böttcher , Ronald Klingebiel

Generative AI is quickly becoming an integral part of people's everyday workflows. Early evidence has shown that while generative AI can increase individual-level productivity, it does so at the cost of collective diversity, potentially…

Human-Computer Interaction · Computer Science 2026-04-07 Nathanael Jo , Manish Raghavan

In continual learning, understanding the properties of task sequences and their relationships to model performance is important for developing advanced algorithms with better accuracy. However, efforts in this direction remain…

Machine Learning · Computer Science 2025-02-11 Thinh Nguyen , Cuong N. Nguyen , Quang Pham , Binh T. Nguyen , Savitha Ramasamy , Xiaoli Li , Cuong V. Nguyen

Human-AI collaboration increasingly drives decision-making across industries, from medical diagnosis to content moderation. While AI systems promise efficiency gains by providing automated suggestions for human review, these workflows can…

Human-Computer Interaction · Computer Science 2025-09-11 Jacob Beck , Stephanie Eckman , Christoph Kern , Frauke Kreuter

Executing workflows on volunteer computing resources where individual tasks may be forced to relinquish their resource for the resource's primary use leads to unpredictability and often significantly increases execution time. Task…

Performance · Computer Science 2022-09-28 Andrew Stephen McGough , Matthew Forshaw

Background: Test-driven development (TDD) is a technique that repeats short coding cycles interleaved with testing. The developer first writes a unit test for the desired functionality, followed by the necessary production code, and…

Software Engineering · Computer Science 2016-11-21 Davide Fucci , Hakan Erdogmus , Burak Turhan , Markku Oivo , Natalia Juristo