Papers by Shriya Ramakrishnan

1 papers
Multilingual Retrieval Augmented Generation for Culturally-Sensitive Tasks: A Benchmark for Cross-lingual Robustness (2025.findings-acl)

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Challenge: Existing approaches to retrieval-augmented generated (RAG) can be useful in multilingual settings, but they also introduce biases in the retrieved documents.
Approach: They propose a dataset of territorial disputes paired with retrieved Wikipedia documents in 49 languages to evaluate cross-lingual robustness.
Outcome: The proposed paradigm helps mitigate hallucinations of large language models (LLMs).

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