Luke Yoffe — accepted AI-conference papers

2025

DebUnc: Improving Large Language Model Agent Communication With Uncertainty Metrics

Luke Yoffe, Alfonso Amayuelas, William Yang Wang

EMNLP 2025

Multi-agent debates have been introduced to improve the accuracy of Large Language Models (LLMs) by having multiple agents discuss solutions to a problem over several rounds of debate. However, models often generate incorrect yet confident-sounding responses, which can mislead the others. This issue

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2022

FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue

Alon Albalak, Yi-Lin Tuan, Pegah Jandaghi, Connor Pryor, Luke Yoffe, Deepak Ramachandran +3

EMNLP 2022main

Task transfer, transferring knowledge contained in related tasks, holds the promise of reducing the quantity of labeled data required to fine-tune language models. Dialogue understanding encompasses many diverse tasks, yet task transfer has not been thoroughly studied in conversational AI. This work…

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