Our EACL 2024 paper promotes a strict definition of entity salience by presenting GUMsley, a 12-genre challenge dataset for entity salience evaluation and shows how salient entities added to summarization models are beneficial for deriving higher-quality summaries with fewer hallucinated entities
Current members
PhD Student in Computational Linguistics, Language Modeling, Language Acquisition, Learner Corpus Research, NLP
PhD Student in Computational Linguistics, Corpus Linguistics, Natural Language Processing
PhD Student in Computational Linguistics, Discourse Processing, Pragmatics, Linguistic Annotation
PhD Student in Computational Linguistics, Coreference Resolution, LLM Evaluation, Linguistic Annotation
Alumni
MS in Computational Linguistics (2019), Junior Computational Linguist at Army Research Laboratory
PhD in Computational Linguistics (2023), Post-Doc at Munich AI & NLP (MaiNLP, LMU Munich)
PhD in Computational Linguistics (2017), Senior Computational Linguist at BlackBoiler LLC