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Found 7 papers, 0 papers with code
HumSum: A Personalized Lecture Summarization Tool for Humanities Students Using LLMs
Generative AI systems aim to create customizable content for their users, with a subsequent surge in demand for adaptable tools that can create personalized experiences.
Aligning Uncertainty: Leveraging LLMs to Analyze Uncertainty Transfer in Text Summarization
The method capitalizes on a small amount of expert annotations and on the capabilities of Large language models (LLMs) to evaluate how the uncertainty of the source text aligns with the uncertainty expressions in the summary.
Experts-in-the-Loop: Establishing an Effective Workflow in Crafting Privacy Q&A
Privacy policies play a vital role in safeguarding user privacy as legal jurisdictions worldwide emphasize the need for transparent data processing.
EduQuick: A Dataset Toward Evaluating Summarization of Informal Educational Content for Social Media
This study explores the capacity of large language models (LLMs) to efficiently generate summaries of informal educational content tailored for platforms like TikTok.
Let’s Write Privacy: Survey and Experiment Design on Textual Privacy in Conversation
This research article emphasizes the significance of privacy in textual conversational data, specifically in the context of interactions between virtual assistants and users.
GiCCS: A German in-Context Conversational Similarity Benchmark
We argue for the need of benchmarks specifically created using conversational data in order to evaluate conversational LMs in the STS task.
PATE: A Corpus of Temporal Expressions for the In-car Voice Assistant Domain
The recognition and automatic annotation of temporal expressions (e. g. {``}Add an event for tomorrow evening at eight to my calendar{''}) is a key module for AI voice assistants, in order to allow them to interact with apps (for example, a calendar app).
