Search Results for author:
Found 5 papers, 1 papers with code
Not So Fast, Classifier – Accuracy and Entropy Reduction in Incremental Intent Classification
We release inCLINC, a dataset of partial and full utterances with human annotations of plausible intent labels for different portions of each utterance, as an upper (human) baseline for incremental intent classification.
New Domain, Major Effort? How Much Data is Necessary to Adapt a Temporal Tagger to the Voice Assistant Domain
Reliable tagging of Temporal Expressions (TEs, e. g., Book a table at L’Osteria for Sunday evening) is a central requirement for Voice Assistants (VAs).
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.
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.
