3 papers
cs.CL2026
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…
cs.CL2024
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.…
cs.CL2023
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…