Papers with CN

3 papers
Do Vision-Language Models Understand Compound Nouns? (2024.naacl-short)

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Challenge: Open-vocabulary vision-language models (CLIP) are emerging as a promising new paradigm for text-to-image retrieval.
Approach: They propose a benchmark to evaluate the effectiveness of open-vocabulary vision-language models (CLIP) for text-to-image retrieval using contrastive loss.
Outcome: The proposed framework improves CN understanding of CLIP by 8.25% on Compun.
CONAN-MT-SP: A Spanish Corpus for Counternarrative Using GPT Models (2024.lrec-main)

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Challenge: a new study evaluates the performance of GPT-based models to generate CNs for hate speech in Spanish . a growing number of social interactions through digital platforms have led to inappropriate behavior .
Approach: They propose to use GPT-based models to generate CNs for Hate Speech in Spanish . they use the DeepL API to automatically translate the HS segment into Spanish based on the original CN pairs translated into spanish .
Outcome: The proposed models outperform human models in most instances, the authors say . the results will be made available to the research community .
Towards the Inference of Semantic Relations in Complex Nominals: a Pilot Study (L18-1)

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Challenge: Complex nominals (CNs) show similar external forms but encode different semantic relations because of noun packing.
Approach: They propose to use paraphrases to convey conceptual content of english two-term CNs in the domain of environmental science to disambiguate the semantic relation between constituents of CN.
Outcome: The proposed method disambiguates the semantic relation between constituents of the CN and infers the semantic relations in these multi-word terms.

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