Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it? - Tobias Norlund; Lovisa Hagström; Richard Johansson (BlackboxNLP@EMNLP, 2021)

Knowledge Distillation for Swedish NER models: A Search for Performance and Efficiency. - Lovisa Hagström; Richard Johansson (NoDaLiDa, 2021)

What do Models Learn From Training on More Than Text? Measuring Visual Commonsense Knowledge. - Lovisa Hagström; Richard Johansson (ACL (student), 2022)

How to Adapt Pre-trained Vision-and-Language Models to a Text-only Input? - Lovisa Hagström; Richard Johansson (COLING, 2022)

The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models. - Lovisa Hagström; Denitsa Saynova; Tobias Norlund; Moa Johansson; Richard Johansson (EMNLP, 2023)

A Reality Check on Context Utilisation for Retrieval-Augmented Generation. - Lovisa Hagström; Sara Vera Marjanovic; Haeun Yu; Arnav Arora; Christina Lioma; Maria Maistro; Pepa Atanasova; Isabelle Augenstein (ACL (1), 2025)

Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion. - Denitsa Saynova; Lovisa Hagström; Moa Johansson; Richard Johansson; Marco Kuhlmann (ACL (Findings), 2025)

Language Model Re-rankers are Steered by Lexical Similarities. - Lovisa Hagström; Ercong Nie; Ruben Halifa; Helmut Schmid; Richard Johansson; Alexander Junge (CoRR, 2025)

CUB: Benchmarking Context Utilisation Techniques for Language Models. - Lovisa Hagström; Youna Kim; Haeun Yu; Sang-goo Lee; Richard Johansson; Hyunsoo Cho; Isabelle Augenstein (CoRR, 2025)