3 papers
cs.CL2025
Enhancing Dialogue Systems with Discourse-Level Understanding Using Deep Canonical Correlation Analysis
Akanksha Mehndiratta, Krishna Asawa
The evolution of conversational agents has been driven by the need for more contextually aware systems that can effectively manage dialogue over extended interactions. To address t…
cs.CL2025
A Multi-view Discourse Framework for Integrating Semantic and Syntactic Features in Dialog Agents
Akanksha Mehndiratta, Krishna Asawa
Multiturn dialogue models aim to generate human-like responses by leveraging conversational context, consisting of utterances from previous exchanges. Existing methods often neglec…
cs.CL2024
Discovering Elementary Discourse Units in Textual Data Using Canonical Correlation Analysis
Akanksha Mehndiratta, Krishna Asawa
Canonical Correlation Analysis (CCA) has been exploited immensely for learning latent representations in various fields. This study takes a step further by demonstrating the potent…