专题：Mobile Crowdsensing and Crowdsourcing

This cluster of papers focuses on the use of crowdsourcing platforms, particularly Amazon's Mechanical Turk, for research and data collection purposes. It explores topics such as data quality, incentive mechanisms, mobile sensing, truth discovery, and the application of crowdsourcing in behavioral research and participatory sensing.
最新文献
AI Resource Allocation: On the Contribution of Distributive and Procedural Fairness

article Full Text OpenAlex

Agency in Human-AI Collaboration for Image Generation and Creative Writing: Preliminary Insights from Think-Aloud Protocols

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Source Anonymity for Private Random Walk Decentralized Learning

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More than One Step at a Time: Designing Procedural Feedback for Non-visual Makeup Routines

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Check Now, Can You See It?: Exploring Voice and Video-Capable Language Models for Identifying and Spatially Locating Items of Interest for Blind and Low-Vision Travelers

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From Cluttered to Clear: Improving the Web Accessibility Design for Screen Reader Users in E-commerce With Generative AI

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Truthful reverse auction-based incentive mechanisms for task offloading in mobile edge computing

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Differentially Private Distributed Mean Estimation with Constrained User Correlations

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From User Surveys to Telemetry-Driven AI Agents: Exploring the Potential of Personalized Productivity Solutions

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Optimized Device Selection and Resource Management Framework for Federated Learning

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近5年高被引文献
Response rates of online surveys in published research: A meta-analysis

article Full Text OpenAlex 1045 FWCI499.58154731

Data quality in online human-subjects research: Comparisons between MTurk, Prolific, CloudResearch, Qualtrics, and SONA

article Full Text OpenAlex 1022 FWCI259.52997385

Transfer Learning in Deep Reinforcement Learning: A Survey

article Full Text OpenAlex 590 FWCI146.11333173

Bias and Debias in Recommender System: A Survey and Future Directions

article Full Text OpenAlex 562 FWCI192.27550195

SplitFed: When Federated Learning Meets Split Learning

article Full Text OpenAlex 541 FWCI60.18818037

Model Pruning Enables Efficient Federated Learning on Edge Devices

article Full Text OpenAlex 466 FWCI82.82290098

Federated learning review: Fundamentals, enabling technologies, and future applications

article Full Text OpenAlex 454 FWCI87.91367031

AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts

article Full Text OpenAlex 375 FWCI101.61755281

Heterogeneous Federated Learning: State-of-the-art and Research Challenges

review Full Text OpenAlex 368 FWCI94.00298265

Differential Privacy for Deep and Federated Learning: A Survey

article Full Text OpenAlex 333 FWCI64.6136107