Papers by Arkadiy Saakyan
I Spy a Metaphor: Large Language Models and Diffusion Models Co-Create Visual Metaphors (2023.findings-acl)
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Tuhin Chakrabarty, Arkadiy Saakyan, Olivia Winn, Artemis Panagopoulou, Yue Yang, Marianna Apidianaki, Smaranda Muresan
| Challenge: | Visual metaphors are powerful rhetorical devices used to communicate creative ideas through images. |
| Approach: | They propose to generate visual metaphors from linguistic metaphors by using large language models and Diffusion models. |
| Outcome: | The proposed task requires the ability to model implicit meaning and compositionality. |
Don’t Go Far Off: An Empirical Study on Neural Poetry Translation (2021.emnlp-main)
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| Challenge: | despite improvements in machine translation quality, automatic poetry translation remains a challenging problem . et al., a study of automatic poetry translators shows that multilingual fine-tuning on poetic data outperforms bilingual fine-timing on non-poetic text . |
| Approach: | They propose to use poetic parallel corpora for 6 languages to study poetry translation . they find that multilingual fine-tuning on poetic data outperforms bilingual fine-uning . |
| Outcome: | The proposed model outperforms bilingual and multilingual models on poetic data . the proposed model is based on a parallel dataset of poetry translations for several languages . |
COVID-Fact: Fact Extraction and Verification of Real-World Claims on COVID-19 Pandemic (2021.acl-long)
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| Challenge: | a new method for fact-checking is needed to detect disinformation on the web . a dataset COVID-Fact contains 4,086 claims concerning the COVId-19 pandemic . |
| Approach: | They propose a FEVER-like dataset COVID-Fact of 4,086 claims concerning the COVId-19 pandemic . they automatically detect true claims and their source articles and generate counter-claims using automatic methods . |
| Outcome: | The proposed method reduces the cost of building domain-specific datasets for detecting misinformation . the proposed dataset contains 4,086 claims concerning the COVID-19 pandemic . |
NormDial: A Comparable Bilingual Synthetic Dialog Dataset for Modeling Social Norm Adherence and Violation (2023.emnlp-main)
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| Challenge: | Social norms fundamentally shape interpersonal communication. |
| Approach: | They propose a human-in-the-loop pipeline to synthesize a bilingual dyadic dialogue dataset with turn-by-turn annotations of social norms for Chinese and American cultures. |
| Outcome: | The proposed dataset is high-quality through human evaluation and compares with existing models. |
Sociocultural Norm Similarities and Differences via Situational Alignment and Explainable Textual Entailment (2023.emnlp-main)
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| Challenge: | Current research on developing computational models of social norms has focused on American society. |
| Approach: | They propose to leverage a Chinese Q&A platform and a socialchiemistry dataset as proxies for contrasting cultural axes and align social situations cross-culturally. |
| Outcome: | The proposed model can reason across cultures using a Chinese Q&A platform and the existing socialChemistry dataset. |
Understanding Figurative Meaning through Explainable Visual Entailment (2025.naacl-long)
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| Challenge: | Existing models for visual entailment and visual question-answering have limited ability to understand figurative meaning in images and captions. |
| Approach: | They propose a task framing the figurative meaning understanding problem as an explainable visual entailment task where the model has to predict whether the image entitles a caption and justify the predicted label with a textual explanation. |
| Outcome: | The proposed dataset contains 6,027 image, caption, label, explanation instances covering five diverse figurative phenomena. |
FLUTE: Figurative Language Understanding through Textual Explanations (2022.emnlp-main)
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| Challenge: | Figurative language understanding is a recognizing textual entailment task, but lacks data for figurative language. |
| Approach: | They propose to use a dataset to analyze figurative NLI instances with explanations to improve models' performance. |
| Outcome: | The proposed dataset can scale up models even for figurative language using human annotations. |
Learning to Follow Object-Centric Image Editing Instructions Faithfully (2023.findings-emnlp)
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| Challenge: | avrahami et al., 2022b,a): natural language instructions are often underspecified, requiring models to uncover their implicit meaning. |
| Approach: | They propose to use paired data to model the implicit meaning of instructions . they also propose to ground the model to localize where the edit has to be performed . |
| Outcome: | The proposed model performs better than state-of-the-art baselines on paired data, showing improvements in quality and faithfulness. |