Papers by Tushar Pranav
DiaSynth: Synthetic Dialogue Generation Framework for Low Resource Dialogue Applications (2025.findings-naacl)
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| Challenge: | Existing research is limited by general or niche datasets that lack sufficient scale for training dialogue systems. |
| Approach: | They propose a synthetic dialogue generation framework that uses Large Language Models and Chain of Thought reasoning to generate dynamic, domain-specific dialogues with simulated personas and diverse conversational features. |
| Outcome: | The proposed framework outperforms existing frameworks on dialogue summarization and quality increases as the size of the LLM increases from 3B to 8B. |