Papers by Jihie Kim
Culture-TRIP: Culturally-Aware Text-to-Image Generation with Iterative Prompt Refinement (2025.naacl-long)
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| Challenge: | Existing text-to-image models fail to produce appropriate images for cultural concepts or objects not well known or underrepresented in western cultures, such as 'hangari' (a Korean utensil). |
| Approach: | They propose a method which iteratively refines the prompt to improve the alignment between the generated images and underrepresented cultural nouns in text-to-image models. |
| Outcome: | The proposed approach improves the alignment between the generated images and cultural nouns in text-to-image models. |
NormGenesis: Multicultural Dialogue Generation via Exemplar-Guided Social Norm Modeling and Violation Recovery (2025.emnlp-main)
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| Challenge: | Social norms govern culturally appropriate behavior in communication, enabling dialogue systems to produce coherent and socially acceptable outputs. |
| Approach: | They propose a framework for generating and annotating socially grounded dialogues in Chinese, English, and Korean. |
| Outcome: | The proposed framework outperforms existing frameworks in refinement quality, dialogue naturalness, and generalization performance. |
VisDoT : Enhancing Visual Reasoning through Human-Like Interpretation Grounding and Decomposition of Thought (2026.findings-eacl)
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| Challenge: | Lack of perceptual grounding limits vision-language models' ability to interpret visual data . prior work on visualized data understanding focused on adapting VLMs to instruction tuning and chain-of-thought supervision . |
| Approach: | They propose a framework that enhances visual reasoning through human-like interpretation grounding. |
| Outcome: | The proposed framework improves on ChartQA and ChartQAPro benchmarks by +11.2%. |
MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller (D18-1)
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| Challenge: | Existing approaches to machine reading comprehension are limited in understanding, up to a few paragraphs, failing to comprehend lengthy documents. |
| Approach: | They propose a deep neural network architecture to handle a long-range dependency in RC tasks. |
| Outcome: | The proposed method outperforms existing methods especially for lengthy documents. |
On-Device Neural Language Model Based Word Prediction (C18-2)
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| Challenge: | Currently, on-device keyboards have limited memory and response time for word prediction . a proposed on-device neural language model based word prediction method is available for mobile devices . |
| Approach: | They propose an on-device neural language model based word prediction method that optimizes run-time memory and provides a real-time prediction environment. |
| Outcome: | The proposed model outperforms existing methods for word prediction in keystroke savings and word prediction rate and has been commercialized. |