Papers by Hrishikesh Terdalkar
A Novel Multi-Task Learning Approach for Context-Sensitive Compound Type Identification in Sanskrit (2022.coling-1)
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Jivnesh Sandhan, Ashish Gupta, Hrishikesh Terdalkar, Tushar Sandhan, Suvendu Samanta, Laxmidhar Behera, Pawan Goyal
| Challenge: | Previously, compounding is a problem of identifying semantic relations between components of a word. |
| Approach: | They propose a multi-task learning architecture which incorporates contextual information and enriches syntactic information using morphological tagging and dependency parsing as auxiliary tasks. |
| Outcome: | The proposed architecture shows 6.1 points accuracy and 7.7 points (F1-score) absolute gain in English and Marathi languages. |
A Case Study of Cross-Lingual Zero-Shot Generalization for Classical Languages in LLMs (2025.findings-acl)
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V.S.D.S.Mahesh Akavarapu, Hrishikesh Terdalkar, Pramit Bhattacharyya, Shubhangi Agarwal, Dr. Vishakha Deulgaonkar, Chaitali Dangarikar, Pralay Manna, Arnab Bhattacharya
| Challenge: | Large Language Models (LLMs) have demonstrated remarkable generalization capabilities across diverse tasks and languages. |
| Approach: | They focus on named entity recognition and machine translation into English to examine factors affecting cross-lingual zero-shot generalization. |
| Outcome: | The proposed models perform better than fine-tuned baselines on out-of-domain data, but smaller models struggle with niche or abstract entity types. |