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20152025
most citedYou Are What You Write: Preserving Privacy in the Era of Large Language Models

8 citations · 9 across the 7 of their papers we have counts for

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cs.CL2025

LLMs as Span Annotators: A Comparative Study of LLMs and Humans

Zdeněk Kasner, Vilém Zouhar, Patrícia Schmidtová +7

Span annotation - annotating specific text features at the span level - can be used to evaluate texts where single-score metrics fail to provide actionable feedback. Until recently…

cs.CL2024

Automatic Metrics in Natural Language Generation: A Survey of Current Evaluation Practices

Patrícia Schmidtová, Saad Mahamood, Simone Balloccu +6

Automatic metrics are extensively used to evaluate natural language processing systems. However, there has been increasing focus on how they are used and reported by practitioners…

cs.CL2023

Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP

Anya Belz, Craig Thomson, Ehud Reiter +39

We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/le…

cs.CL20228 cited

You Are What You Write: Preserving Privacy in the Era of Large Language Models

Richard Plant, Valerio Giuffrida, Dimitra Gkatzia

Large scale adoption of large language models has introduced a new era of convenient knowledge transfer for a slew of natural language processing tasks. However, these models also…

cs.CL2022

Task2Dial: A Novel Task and Dataset for Commonsense enhanced Task-based Dialogue Grounded in Documents

Carl Strathearn, Dimitra Gkatzia

This paper proposes a novel task on commonsense-enhanced task-based dialogue grounded in documents and describes the Task2Dial dataset, a novel dataset of document-grounded task-ba…

cs.CL2021

CAPE: Context-Aware Private Embeddings for Private Language Learning

Richard Plant, Dimitra Gkatzia, Valerio Giuffrida

Deep learning-based language models have achieved state-of-the-art results in a number of applications including sentiment analysis, topic labelling, intent classification and othe…