Papers by Arif Ahmad
ETHICA-MT: Introducing a Framework and Dataset for Studying Ethical Orientations in LLM-based Machine Translation (2026.findings-acl)
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| Challenge: | Existing models for translation have not been systematically examined for their default ethical tendencies or their ability to employ and prioritize specified ethical approaches in conflicted translation situations. |
| Approach: | They propose a framework for examining ethical reasoning and implementation in large language models (LLMs) that systematically examines default ethical tendencies and their ability to employ and prioritize specified ethical approaches in conflicted translation situations. |
| Outcome: | The proposed framework examines the ethical reasoning and implementation of large language models in translation tasks. |
IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context (2024.naacl-long)
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Nihar Sahoo, Pranamya Kulkarni, Arif Ahmad, Tanu Goyal, Narjis Asad, Aparna Garimella, Pushpak Bhattacharyya
| Challenge: | Existing benchmark datasets focus on English language and the Western context, leaving a void for a reliable dataset that encapsulates India’s unique socio-cultural nuances. |
| Approach: | They propose to use CrowS-Pairs to create a benchmark dataset that captures and evaluates social biases in Large Language Models (LLMs). |
| Outcome: | The proposed dataset is available in English and Hindi and leverages LLMs ChatGPT and InstructGPT to augment the existing dataset with diverse societal biases and stereotypes prevalent in India. |