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The subtle human values we acquire through life experiences govern our thoughts and gets reflected in our speech. It plays an integral part in capturing the essence of our individuality and making it imperative to identify such values in computational systems that mimic human actions. Computational argumentation is a field that deals with the argumentation capabilities of humans and can benefit from identifying such values. Motivated by that, we present an ensemble approach for detecting human values from argument text. Our ensemble comprises three models: (i) An entailment-based model for determining the human values based on their descriptions, (ii) A Roberta-based classifier that predicts the set of human values from an argument. (iii) A Roberta-based classifier to predict a reduced set of human values from an argument. We experiment with different ways of combining the models and report our results. Furthermore, our best combination achieves an overall F1 score of 0.48 on the main test set.
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Observations from an expedition to Costa Rican peatlands.
Notes from the field In July and August of 2023, we visited Costa Rica to examine some of the country’s peatlands. The purpose of our trip was to collect peat samples from a variety of wetland habitats from the coast to the highlands for future analysis. We summarize our observations in this short essay. Editorial review only
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- Award ID(s):
- 2142177
- PAR ID:
- 10506697
- Publisher / Repository:
- Society of Wetland Scientists
- Date Published:
- Journal Name:
- The Society of Wetland Scientists bulletin
- Volume:
- 42
- Issue:
- 1
- ISSN:
- 1943-6254
- Page Range / eLocation ID:
- 145-149
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
