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cs.CL2024
Practical token pruning for foundation models in few-shot conversational virtual assistant systems
Haode Qi, Cheng Qian, Jian Ni +6
In an enterprise Virtual Assistant (VA) system, intent classification is the crucial component that determines how a user input is handled based on what the user wants. The VA syst…
cs.CL2024
An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants
G P Shrivatsa Bhargav, Sumit Neelam, Udit Sharma +10
We present an approach to build Large Language Model (LLM) based slot-filling system to perform Dialogue State Tracking in conversational assistants serving across a wide variety o…
cs.CL2023★ 1 cited
Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants
Cheng Qian, Haode Qi, Gengyu Wang +2
Out of Scope (OOS) detection in Conversational AI solutions enables a chatbot to handle a conversation gracefully when it is unable to make sense of the end-user query. Accurately…