3 papers
cs.CL2025
Biases in Large Language Model-Elicited Text: A Case Study in Natural Language Inference
Grace Proebsting, Adam Poliak
We test whether NLP datasets created with Large Language Models (LLMs) contain annotation artifacts and social biases like NLP datasets elicited from crowd-source workers. We recre…
cs.AI2024
Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks
Adam Fourney, Gagan Bansal, Hussein Mozannar +17
Modern AI agents, driven by advances in large foundation models, promise to enhance our productivity and transform our lives by augmenting our knowledge and capabilities. To achiev…
cs.CL2024
Hypothesis-only Biases in Large Language Model-Elicited Natural Language Inference
Grace Proebsting, Adam Poliak
We test whether replacing crowdsource workers with LLMs to write Natural Language Inference (NLI) hypotheses similarly results in annotation artifacts. We recreate a portion of the…