8 papers
Stress Testing Factual Consistency Metrics for Long-Document Summarization
Zain Muhammad Mujahid, Dustin Wright, Isabelle Augenstein
Evaluating the factual consistency of abstractive text summarization remains a significant challenge, particularly for long documents, where conventional metrics struggle with inpu…
Epistemic Diversity and Knowledge Collapse in Large Language Models
Dustin Wright, Sarah Masud, Jared Moore +5
Large language models (LLMs) tend to generate homogenous texts, which may impact the diversity of knowledge generated across different outputs. Given their potential to replace exi…
Unstructured Evidence Attribution for Long Context Query Focused Summarization
Dustin Wright, Zain Muhammad Mujahid, Lu Wang +2
Large language models (LLMs) are capable of generating coherent summaries from very long contexts given a user query, and extracting and citing evidence spans helps improve the tru…
Revealing Fine-Grained Values and Opinions in Large Language Models
Dustin Wright, Arnav Arora, Nadav Borenstein +3
Uncovering latent values and opinions embedded in large language models (LLMs) can help identify biases and mitigate potential harm. Recently, this has been approached by prompting…
Modeling Public Perceptions of Science in Media
Jiaxin Pei, Dustin Wright, Isabelle Augenstein +1
Effectively engaging the public with science is vital for fostering trust and understanding in our scientific community. Yet, with an ever-growing volume of information, science co…
Machine Understanding of Scientific Language
Dustin Wright
Scientific information expresses human understanding of nature. This knowledge is largely disseminated in different forms of text, including scientific papers, news articles, and d…