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Cue-bot: A Conversational Agent for Assistive Technology
Intelligent conversational assistants have become an integral part of our lives for performing simple tasks.
Context or No Context? A preliminary exploration of human-in-the-loop approach for Incremental Temporal Summarization in meetings
By compressing the previous contexts by ~70%, we achieve better ROUGE scores over our baseline models.
Learning from Red Teaming: Gender Bias Provocation and Mitigation in Large Language Models
Recently, researchers have made considerable improvements in dialogue systems with the progress of large language models (LLMs) such as ChatGPT and GPT-4.
Position Matters! Empirical Study of Order Effect in Knowledge-grounded Dialogue
With the power of large pretrained language models, various research works have integrated knowledge into dialogue systems.
Controllable Response Generation for Assistive Use-cases
We build models that can suggest relevant cues in the dialog response context which is used to control response generation and can speed up communication.
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