Papers by Paul Landes
RoBERTa Low Resource Fine Tuning for Sentiment Analysis in Albanian (2024.lrec-main)
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| Challenge: | Recent advances in the education domain have provided new opportunities for solving interesting, but difficult problems. |
| Approach: | They propose to use EduSenti to fine-tune language models for assigning sentiment to reviews of educators' performance annotated for sentiment, emotion and educational topic. |
| Outcome: | The proposed model is compared with an Albanian masked language trained model from the last XLM-RoBERTa checkpoint and shows that it is a good fit for the proposed model. |
A New Public Corpus for Clinical Section Identification: MedSecId (2022.coling-1)
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| Challenge: | a study aims to segment sections of clinical medical domain documentation . section identification is a process by which sections are demarcated and labeled . |
| Approach: | They use a set of 2,002 fully annotated medical notes from the MIMIC-III to segment sections in clinical medical domain documentation. |
| Outcome: | The proposed model shows that medical concepts are related across sections using principal component analysis. |
CALAMR: Component ALignment for Abstract Meaning Representation (2024.lrec-main)
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| Challenge: | Abstract meaning representation (AMR) graphs represent semantic structure in a syntactic independent way. |
| Approach: | They propose a method for graph alignment that can support summarization and evaluation. |
| Outcome: | The proposed method produces graphs that explain what is summarized through their alignments, which can be used to train graph based summarization learners. |