Papers by Hiba Ahsan

2 papers
Multi-Modal Image Captioning for the Visually Impaired (2021.naacl-srw)

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Challenge: Current captioning models for blind people do not use textual data present in the image when generating captions.
Approach: They propose to use text detected in the image as an input feature in captions . they also use a pointer-generator network to copy detected text to the caption .
Outcome: The proposed system outperforms existing models on the VizWiz dataset, showing a 35% and 16.2% performance improvement.
Elucidating Mechanisms of Demographic Bias in LLMs for Healthcare (2025.findings-emnlp)

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Challenge: a recent study has shown that LLMs encode social biases and manifest in clinical tasks.
Approach: They use mechanistic interpretability to uncover biases within LLMs . they find gender information is highly localized in MLP layers .
Outcome: The proposed method can reveal biases and representations within LLMs in healthcare.

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