Papers by Arif A. Ahmad
Looks can be Deceptive: Distinguishing Repetition Disfluency from Reduplication (2025.coling-main)
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| Challenge: | Existing research indicates that disfluencies can constitute up to 5.9% of words in spontaneous speech, with repetitions accounting for over half of these disfluency. |
| Approach: | They propose to use a dataset to analyze reduplication and repetition in speech using computational linguistics to evaluate transformer-based models. |
| Outcome: | The proposed models achieve macro F1 scores of up to 85.62% in Hindi, 83.95% in Telugu, and 84.82% in Marathi for reduplication-repetition classification. |
Addressing Bias and Hallucination in Large Language Models (2024.lrec-tutorials)
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Nihar Ranjan Sahoo, Ashita Saxena, Kishan Maharaj, Arif A. Ahmad, Abhijit Mishra, Pushpak Bhattacharyya
| Challenge: | This tutorial provides a comprehensive overview of two critical aspects of Large Language Models: bias and hallucination. |
| Approach: | This tutorial provides an overview of two critical aspects of Large Language Models: bias and hallucination. |
| Outcome: | This tutorial delves into the complex dimensions of Large Language Models (LLMs) it outlines ethical considerations pertinent to their development and discusses hallucination, a prevalent issue in generative AI systems such as LLMs. |