1 citations · 1 across the 4 of their papers we have counts for
5 papers
Confidence Reasoning Graphs: Structured Confidence Estimation for LLM Agents
Brendan King, Farima Fatahi Bayat, Jean-Flavien Bussotti +2
When using an LLM agent in a consequential domain, making an informed decision about whether to trust its output or intervene requires calibrated confidence in the agent's success.…
Dialogue SWE-Bench: A Benchmark for Dialogue-Driven Coding Agents
Brendan King, Jeffrey Flanigan
AI coding agents have rapidly transformed software engineering, powering widely used interactive coding assistants. Despite their interactive real-world use, existing benchmarks ev…
Unsupervised End-to-End Task-Oriented Dialogue with LLMs: The Power of the Noisy Channel
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.…
Diverse Retrieval-Augmented In-Context Learning for Dialogue State Tracking
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. Recen…
Dependency Dialogue Acts -- Annotation Scheme and Case Study
Jon Z. Cai, Brendan King, Margaret Perkoff +9
In this paper, we introduce Dependency Dialogue Acts (DDA), a novel framework for capturing the structure of speaker-intentions in multi-party dialogues. DDA combines and adapts fe…