Search Results for author: Brendan King

Found 3 papers, 2 papers with code

The Power of the Noisy Channel: Unsupervised End-to-End Task-Oriented Dialogue with LLMs

1 code implementation23 Apr 2024 Brendan King, Jeffrey Flanigan

Training task-oriented dialogue systems typically requires turn-level annotations for interacting with their APIs: e. g. a dialogue state and the system actions taken at each step.

Task-Oriented Dialogue Systems

Diverse Retrieval-Augmented In-Context Learning for Dialogue State Tracking

1 code implementation4 Jul 2023 Brendan King, Jeffrey Flanigan

There has been significant interest in zero and few-shot learning for dialogue state tracking (DST) due to the high cost of collecting and annotating task-oriented dialogues.

Dialogue State Tracking Few-Shot Learning +2

Dependency Dialogue Acts -- Annotation Scheme and Case Study

no code implementations25 Feb 2023 Jon Z. Cai, Brendan King, Margaret Perkoff, Shiran Dudy, Jie Cao, Marie Grace, Natalia Wojarnik, Ananya Ganesh, James H. Martin, Martha Palmer, Marilyn Walker, Jeffrey Flanigan

DDA combines and adapts features from existing dialogue annotation frameworks, and emphasizes the multi-relational response structure of dialogues in addition to the dialogue acts and rhetorical relations.

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