Divyaksh Shukla — accepted AI-conference papers

2025

CoMuMDR: Code-mixed Multi-modal Multi-domain corpus for Discourse paRsing in conversations

Divyaksh Shukla, Ritesh Baviskar, Dwijesh Gohil, Aniket Tiwari, Atul Shree, Ashutosh Modi

ACL 2025finding

Discourse parsing is an important task useful for NLU applications such as summarization, machine comprehension, and emotion recognition. The current discourse parsing datasets based on conversations consists of written English dialogues restricted to a single domain. In this resource paper, we intr…

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2024

Towards Robust Evaluation of Unlearning in LLMs via Data Transformations

Abhinav Joshi, Shaswati Saha, Divyaksh Shukla, Sriram Vema, Harsh Jhamtani, Manas Gaur +1

EMNLP 2024finding

Large Language Models (LLMs) have shown to be a great success in a wide range of applications ranging from regular NLP-based use cases to AI agents. LLMs have been trained on a vast corpus of texts from various sources; despite the best efforts during the data pre-processing stage while training the…

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