Blase Ur — accepted AI-conference papers

2025

Implicit Values Embedded in How Humans and LLMs Complete Subjective Everyday Tasks

Arjun Arunasalam, Madison Pickering, Z. Berkay Celik, Blase Ur

EMNLP 2025

Large language models (LLMs) can underpin AI assistants that help users with everyday tasks, such as by making recommendations or performing basic computation. Despite AI assistants’ promise, little is known about the implicit values these assistants display while completing subjective everyday task

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2022

Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data

Jamar Sullivan Jr., Will Brackenbury, Andrew McNutt, Kevin Bryson, Kwam Byll, Yuxin Chen +3

NAACL 2022long

In the context of data labeling, NLP researchers are increasingly interested in having humans select rationales, a subset of input tokens relevant to the chosen label. We conducted a 332-participant online user study to understand how humans select rationales, especially how different instructions a…

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