Papers by Ananya Malik

2 papers
Are LLMs Empathetic to All? Investigating the Influence of Multi-Demographic Personas on a Model’s Empathy (2025.findings-emnlp)

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Challenge: Large Language Models’ ability to converse naturally is empowered by their ability to empathetically understand and respond to their users.
Approach: They propose a framework to investigate how LLMs’ cognitive and affective empathy vary across user personas defined by intersecting demographic attributes.
Outcome: The proposed framework examines 315 unique personas from age, culture, and gender across four LLMs.
Who Speaks Matters: Analysing the Influence of the Speaker’s Linguistic Identity on Hate Classification (2025.findings-emnlp)

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Challenge: Large Language Models are known to be brittle and biased against marginalised communities and dialects.
Approach: They investigate the robustness of hate speech classification using LLMs when explicit and implicit markers of the speaker’s ethnicity are injected into the input.
Outcome: The proposed model is robust when explicit and implicit markers of speaker's ethnicity are injected into the input.

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