Papers by Reddybathuni Venkat
UnityAI Guard: Pioneering Toxicity Detection Across Low-Resource Indian Languages (2025.emnlp-demos)
Copied to clipboard
Himanshu Beniwal, Reddybathuni Venkat, Rohit Kumar, Birudugadda Srivibhav, Daksh Jain, Pavan Deekshith Doddi, Eshwar Dhande, Adithya Ananth, null Kuldeep, Mayank Singh
| Challenge: | Existing systems target high-resource languages, but UnityAI-Guard addresses this gap by developing state-of-the-art models for binary toxicity classification targeting low-resourced Indian languages. |
| Approach: | They propose a framework for binary toxicity classification targeting low-resource Indian languages. |
| Outcome: | The proposed framework achieves an impressive average F1-score of 84.23% across seven languages, leveraging a dataset of 567k training instances and 30k manually verified test instances. |