Six papers by CopeNLU authors have been accepted for presentation at ACL 2026, on topics including fact-checking and uncertainty, evaluation protocols for retrieval, factual consistency in long-document summarization, context utilisation in language models, and gender bias in LLM-generated persuasive text.
CUB: Benchmarking Context Utilisation Techniques for Language Models. Lovisa Hagström, Youna Kim, Haeun Yu, Sang-goo Lee, Richard Johansson, Hyunsoo Cho, Isabelle Augenstein.
Explaining Sources of Uncertainty in Automated Fact-Checking. Jingyi Sun, Greta Warren, Irina Shklovski, Isabelle Augenstein.
Reliable Evaluation Protocol for Low-Precision Retrieval. Kisu Yang, Yoonna Jang, Hwanseok Jang, Kenneth Choi, Isabelle Augenstein, Heuiseok Lim.
Stress Testing Factual Consistency Metrics for Long-Document Summarization. Zain Muhammad Mujahid, Dustin Wright, Isabelle Augenstein.
Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns. Amalie Brogaard Pauli, Maria Barrett, Max Müller-Eberstein, Isabelle Augenstein, Ira Assent.
Evaluation Framework for Highlight Explanations of Context Utilisation in Language Models. Jingyi Sun, Pepa Atanasova, Sagnik Ray Choudhury, Sekh Mainul Islam, Isabelle Augenstein.