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Found 8 papers, 1 papers with code
Navigating Privacy and Copyright Challenges Across the Data Lifecycle of Generative AI
The advent of Generative AI has marked a significant milestone in artificial intelligence, demonstrating remarkable capabilities in generating realistic images, texts, and data patterns.
Test-takers have a say: understanding the implications of the use of AI in language tests
To the best of our knowledge, this is the first empirical study aimed at identifying the implications of AI adoption in language tests from a test-taker perspective.
Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions
In this paper, we explore these challenges and provide our insights on how to implement technical solutions for the RTBF, including the use of differential privacy, machine unlearning, model editing, and prompt engineering.
Blockchain-Empowered Trustworthy Data Sharing: Fundamentals, Applications, and Challenges
Second, we focus on the convergence of blockchain and data sharing to give a clear picture of this landscape and propose a reference architecture for blockchain-based data sharing.
Keen2Act: Activity Recommendation in Online Social Collaborative Platforms
The Act step then recommends to the user which activities to perform on the identified set of items.
PatchNet: A Tool for Deep Patch Classification
This work proposes PatchNet, an automated tool based on hierarchical deep learning for classifying patches by extracting features from commit messages and code changes.
Network-Clustered Multi-Modal Bug Localization
To help the developers debug, numerous information retrieval (IR)-based and spectrum-based bug localization techniques have been devised.
