Papers by Minwoo Kang

3 papers
Puzzled by Puzzles: When Vision-Language Models Can’t Take a Hint (2025.emnlp-main)

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Challenge: rebus puzzles encode language through imagery, spatial arrangement, and symbolic substitution.
Approach: They construct a benchmark of rebus puzzles in english language to test their ability to interpret and solve them.
Outcome: The proposed model performs well on a set of english-language rebus puzzles.
Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions (2025.acl-long)

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Challenge: Prior studies have failed to accurately predict distribution of survey responses from human subjects.
Approach: They propose to fine-tune large language models to predict human response distributions by leveraging unique structural characteristics of survey data.
Outcome: The proposed model can capture group-specific variability in public opinions, generalizing to unseen subpopulations, survey waves and question topics, and different survey families.
Virtual Personas for Language Models via an Anthology of Backstories (2024.emnlp-main)

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Challenge: Large language models (LLMs) are trained from vast repositories of text authored by millions of distinct authors, reflecting an enormous diversity of human traits.
Approach: They propose a method for conditioning LLMs to particular virtual personas by harnessing open-ended life narratives, which they refer to as backstories, and demonstrate that it improves consistency and reliability of experimental outcomes.
Outcome: The proposed method improves consistency and reliability of experimental outcomes while ensuring better representation of diverse sub-populations.

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