131 citations · 319 across the 29 of their papers we have counts for
6 papers · 2 filters
Belief in the Machine: Investigating Epistemological Blind Spots of Language Models
Mirac Suzgun, Tayfun Gur, Federico Bianchi +4
As language models (LMs) become integral to fields like healthcare, law, and journalism, their ability to differentiate between fact, belief, and knowledge is essential for reliabl…
Data Checklist: On Unit-Testing Datasets with Usable Information
Heidi C. Zhang, Shabnam Behzad, Kawin Ethayarajh +1
Model checklists (Ribeiro et al., 2020) have emerged as a useful tool for understanding the behavior of LLMs, analogous to unit-testing in software engineering. However, despite da…
Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance
Kaitlyn Zhou, Jena D. Hwang, Xiang Ren +3
The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models. However, current evaluations of these abilities rely on simple cali…
NLP Systems That Can't Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helps
Kristina Gligoric, Myra Cheng, Lucia Zheng +2
The use of words to convey speaker's intent is traditionally distinguished from the `mention' of words for quoting what someone said, or pointing out properties of a word. Here we…
Dialect prejudice predicts AI decisions about people's character, employability, and criminality
Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky +1
Hundreds of millions of people now interact with language models, with uses ranging from serving as a writing aid to informing hiring decisions. Yet these language models are known…
AnthroScore: A Computational Linguistic Measure of Anthropomorphism
Myra Cheng, Kristina Gligoric, Tiziano Piccardi +1
Anthropomorphism, or the attribution of human-like characteristics to non-human entities, has shaped conversations about the impacts and possibilities of technology. We present Ant…