Events

NLTP Content Meetings – September 16 – Dimensions of Semantic Change: Applying the SIBling Framework to Mental Health Concepts by Naomi Baes
We’re pleased to welcome Naomi Baes from the University of Melbourne to our NLTP Content Meeting on September 16, where they will give a talk on Dimensions of Semantic Change: Applying the SIBling Framework to Mental Health Concepts. The meeting link is available on request. See details below. Title: Dimensions of Semantic Change: Applying the SIBling…
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NLTP Content Meetings – September 9 – Lexical Semantic Change Detection for Ancient Greek by Silvia Stopponi
We’re opening this academic year’s content meetings on September 9 with a talk by Silvia Stopponi, PhD candidate at the Center for Language and Cognition, University of Groningen, on Lexical Semantic Change Detection for Ancient Greek. See the details below. Title: Lexical semantic change detection for Ancient Greek: dataset creation and evaluation of a word-embedding-based…
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6th NLTP Content Meeting Session
🌐 Discussion Topic: Assessing the Reliability of Annotations in the Context of LLM Predictions and Explanations This event focused on evaluating the reliability of human annotations in NLP tasks and exploring whether Generative AI (GenAI) models can serve as viable alternatives. The research examined demographic influences on labeling decisions and tested explainable AI (XAI) techniques…
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Upcoming NLTP Content Meeting Session
🌐 Event Details: Paper Presentation Location: Sjoerd Groenmangebouw, B.109 Discussion Topic: Assessing the Reliability of Annotations in the Context of LLMs Predictions and Explanations 🔍Overview of the Meeting: A presentation will be given on “Assessing the Reliability of Annotations in the Context of LLM Predictions and Explanations” as part of the Applied Data Science grant…
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5th NLTP Content Meeting Session
🌐 Discussion Topic: A Comparison of Correspondence Analysis with PMI-Based Word Embedding Methods 🔍 Overview of the Presentation This session explored the integration of Correspondence Analysis (CA) with popular PMI-based word embedding techniques like GloVe and Word2Vec. The research presented a novel link between CA and PMI, demonstrating how square-root and root-root transformations can significantly…
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