Papers by Siwon Kim

2 papers
GrounDial: Human-norm Grounded Safe Dialog Response Generation (2024.findings-eacl)

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Challenge: Recent conversational AI systems generate unsafe responses agreeing to offensive user input or including toxic content.
Approach: They propose a method where response safety is achieved by grounding responses to commonsense social rules without fine-tuning.
Outcome: The proposed approach is quantitatively and qualitatively safer even without additional data or tuning.
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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