Papers by Kwesi Adu Cobbina
My LLM might Mimic AAE - But When Should It? (2025.naacl-long)
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| Challenge: | a study examines the representation of African American English in large language models . a survey of black americans and annotation of LLM outputs shows that Black Americans prefer to use AAE in formal settings . |
| Approach: | They examine Black Americans' perceptions of how effective AI tools are at producing authentic African American English in large language models. |
| Outcome: | The results show that Black Americans prefer to use LLMs in formal settings over informal ones . the results show they prefer to produce AAE in less formal settings . |
Where to show Demos in Your Prompt: A Positional Bias of In-Context Learning (2025.emnlp-main)
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| Challenge: | In-context learning (ICL) is a critical emerging capability of large language models (LLMs), enabling few-shot learning during inference by including a few demonstrations in the prompt. |
| Approach: | They propose to use positional bias to study ICL's performance for the first time by examining the positional variation in demos, system prompt, and user message in LLM input. |
| Outcome: | The proposed model can predict accuracy and accuracy when demos are placed at different positions in the input prompt and in the user message. |