3 papers
cs.CL2025
PyTOD: Programmable Task-Oriented Dialogue with Execution Feedback
Alexandru Coca, Bo-Hsiang Tseng, Pete Boothroyd +8
Programmable task-oriented dialogue (TOD) agents enable language models to follow structured dialogue policies, but their effectiveness hinges on accurate state tracking. We presen…
cs.CL2025
ASPERA: A Simulated Environment to Evaluate Planning for Complex Action Execution
Alexandru Coca, Mark Gaynor, Zhenxing Zhang +6
This work evaluates the potential of large language models (LLMs) to power digital assistants capable of complex action execution. These assistants rely on pre-trained programming…
cs.CL2024
LUCID: LLM-Generated Utterances for Complex and Interesting Dialogues
Joe Stacey, Jianpeng Cheng, John Torr +5
Spurred by recent advances in Large Language Models (LLMs), virtual assistants are poised to take a leap forward in terms of their dialogue capabilities. Yet a major bottleneck to…