Papers by Aishwarya Verma
SAFARI: A Community-Engaged Approach and Dataset of Stereotype Resources in the Sub-Saharan African Context (2026.eacl-short)
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Aishwarya Verma, Laud Ammah, Olivia Nercy Ndlovu Lucas, Andrew Zaldivar, Vinodkumar Prabhakaran, Sunipa Dev
| Challenge: | Existing data collection approaches to generative AI are inadequate to assess its safety and utility. |
| Approach: | They propose a multilingual stereotype resource that uses socioculturally-situated, community-engaged methods to assess the region’s linguistic diversity and traditional orality. |
| Outcome: | The proposed method covers four sub-Saharan African countries that are severely underrepresented in NLP resources: Ghana, Kenya, Nigeria, and South Africa. |
Scaling Cultural Resources for Improving Generative Models (2026.findings-eacl)
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Hayk Stepanyan, Aishwarya Verma, Andrew Zaldivar, Rutledge Chin Feman, Erin MacMurray van Liemt, Charu Kalia, Vinodkumar Prabhakaran, Sunipa Dev
| Challenge: | generative models have been known to have reduced performance in different global cultural contexts and languages. |
| Approach: | They construct a pipeline to collect and contribute culturally salient, multilingual data . they argue such data can assess the state of the global applicability of generative AI models . |
| Outcome: | The proposed pipeline can assess the state of the global applicability of our models and improve upon cross-cultural gaps. |