6 citations · 8 across the 5 of their papers we have counts for
5 papers
Sparse Rewards Can Self-Train Dialogue Agents
Barrett Martin Lattimer, Varun Gangal, Ryan McDonald +1
Recent advancements in state-of-the-art (SOTA) Large Language Model (LLM) agents, especially in multi-turn dialogue tasks, have been primarily driven by supervised fine-tuning and…
Enhancing Hallucination Detection through Perturbation-Based Synthetic Data Generation in System Responses
Dongxu Zhang, Varun Gangal, Barrett Martin Lattimer +1
Detecting hallucinations in large language model (LLM) outputs is pivotal, yet traditional fine-tuning for this classification task is impeded by the expensive and quickly outdated…
Fast and Accurate Factual Inconsistency Detection Over Long Documents
Barrett Martin Lattimer, Patrick Chen, Xinyuan Zhang +1
Generative AI models exhibit remarkable potential; however, hallucinations across various tasks present a significant challenge, particularly for longer inputs that current approac…
Human Inspired Progressive Alignment and Comparative Learning for Grounded Word Acquisition
Yuwei Bao, Barrett Martin Lattimer, Joyce Chai
Human language acquisition is an efficient, supervised, and continual process. In this work, we took inspiration from how human babies acquire their first language, and developed a…
Creating Compact Regions of Social Determinants of Health
Barrett Lattimer, Alan Lattimer
Regionalization is the act of breaking a dataset into contiguous homogeneous regions that are heterogeneous from each other. Many different algorithms exist for performing regional…