Exploiting Image Generality for Lexical Entailment Detection
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Douwe Kiela, Laura Rimell, Ivan Vulić, Stephen Clark. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). 2015.
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The same embeddings achieved a state-of-the-art accuracy of 0.86 on WBLESS, which evaluates non-graded lexical entailment.
“The same embeddings also achieved a state-of-the-art accuracy of 0 . 86 on WBLESS [33, 14], which evaluates non-graded lexical entailment.”
From Poincaré Embeddings for Learning Hierarchical Representations (2017) · cites this paper as [14]
Table 2 (Results) reports WBLESS accuracy of 0.75 for image dispersion and 0.74 for centroid distance, not 0.86. The Results say dispersion matches the best-performing supervised method; the paper does support describing WBLESS as a non-graded entailment-detection evaluation. (LLM, conf=0.90)
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- Authors
- Kiela, D., Rimell, L., Vulić, I., & Clark, S.
- Affiliations
- University of Cambridge (GB)
- KU Leuven (BE)
- Venue
- Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
- Published
- 2015
- Pages
- 119-124
- OpenAlex
- W2251109971
- Cited by
- 55
- References
- 36
- Citations by year
- 2024: 3 · 2023: 1 · 2022: 3 · 2021: 3 · 2020: 8 · 2019: 11 · 2018: 6 · 2017: 13 · 2016: 7
- FWCI
- 4.88
- Type
- conference paper
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Lirias (acceptedVersion, other-oa)
- Funders
- KU Leuven
- Engineering and Physical Sciences Research Council (EP/I037512/1)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Keywords
- visual grounding, natural language understanding
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