Manav Nitin Kapadnis — accepted AI-conference papers

2024

Evaluating the Effectiveness of Large Language Models in Establishing Conversational Grounding

Biswesh Mohapatra, Manav Nitin Kapadnis, Laurent Romary, Justine Cassell

EMNLP 2024main

Conversational grounding, vital for building dependable dialog systems, involves ensuring a mutual understanding of shared information. Despite its importance, there has been limited research on this aspect of conversation in recent years, especially after the advent of Large Language Models (LLMs).…

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2023

$\textbf{\emph{CLMSM}}$: A Multi-Task Learning Framework for Pre-training on Procedural Text

Abhilash Nandy, Manav Nitin Kapadnis, Pawan Goyal, Niloy Ganguly

EMNLP 2023long findings

In this paper, we propose ***CLMSM***, a domain-specific, continual pre-training framework, that learns from a large set of procedural recipes. ***CLMSM*** uses a Multi-Task Learning Framework to optimize two objectives - a) Contrastive Learning using hard triplets to learn fine-grained differences…

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