Papers by Gene Louis Kim
BanStereoSet: A Dataset to Measure Stereotypical Social Biases in LLMs for Bangla (2025.findings-acl)
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| Challenge: | ***BanStereoSet*** is a dataset designed to evaluate stereotypical social biases in multilingual LLMs for the Bangla language. |
| Approach: | They propose to localize the content from StereoSet, IndiBias, and kamruzzaman-etal's datasets to capture biases prevalent within the Bangla language. |
| Outcome: | The proposed dataset consists of 1,194 sentences spanning 9 categories of bias: race, profession, gender, ageism, beauty, beauty in profession, region, caste, and religion. |
Exploring Changes in Nation Perception with Nationality-Assigned Personas in LLMs (2025.emnlp-main)
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| Challenge: | Using personas, LLMs are custom-made to meet specific user needs. |
| Approach: | They assign 193 different nationality personas to five LLMs and examine how evaluations of different nations change when LLM users are assigned specific nationality persons. |
| Outcome: | The nationality personas of five LLMs are assigned to different nations and their evaluations change. |
Event Detection with a Context-Aware Encoder and LoRA for Improved Performance on Long-Tailed Classes (2026.findings-eacl)
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| Challenge: | Decoder-only models dominate the event detection literature, but their unidirectional attention mechanism has been a roadblock in getting strong performance on embedding. |
| Approach: | They propose to use Macro-F1 as a more representative measure of a model’s ability across the long-tail of event types to improve their models' performance. |
| Outcome: | The proposed model improves on the decoder-only models, showing that low-rank Adaptation can be an effective tool to enhance LLMs’ performance on long-tailed event classes. |
The Impact of Name Age Perception on Job Recommendations in LLMs (2025.findings-acl)
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| Challenge: | Existing studies have examined implicit age-related name bias in LLMs . older-sounding names are favored for senior roles, while younger-sounders are linked to youth-dominant jobs . |
| Approach: | They analyze six LLMs and 117 American names categorized by perceived age across 30 occupations . older-sounding names are favored for senior roles, while younger-sounders are linked to youth-dominant jobs . |
| Outcome: | The proposed model based on six LLMs and 117 American names shows that older-sounding names are favored for senior roles, while younger-sounders are linked to youth-dominant jobs. |