Papers by Jihun Yi

2 papers
Interactive Text-to-Image Retrieval with Large Language Models: A Plug-and-Play Approach (2024.acl-long)

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Challenge: primarily addressed in text-to-image retrieval task using dialogue-form context query . conventionally, text-based retrieval methods rely on initial text descriptions .
Approach: They propose a plug-based retrieval method that uses large language models as questioners to generate non-redundant questions about the attributes of the target image.
Outcome: The proposed method performs better than zero-shot and fine-tuned baselines in benchmarks.
Interpretation of NLP models through input marginalization (2020.emnlp-main)

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Challenge: Existing methods to interpret NLP predictions replace each token with a predefined value, resulting in misleading interpretations.
Approach: They propose to marginalize each token out of the training data distribution to demystify the "black box" property of deep neural networks for natural language processing.
Outcome: The proposed method marginalizes each token out of the training data distribution.

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