2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2023
The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models
Lovisa Hagström, Denitsa Saynova, Tobias Norlund +2
Large Language Models (LLMs) make natural interfaces to factual knowledge, but their usefulness is limited by their tendency to deliver inconsistent answers to semantically equival…
cs.CL2022★ 2 cited
How to Adapt Pre-trained Vision-and-Language Models to a Text-only Input?
Lovisa Hagström, Richard Johansson
Current language models have been criticised for learning language from text alone without connection between words and their meaning. Consequently, multimodal training has been pr…
cs.CL2021
Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it?
Tobias Norlund, Lovisa Hagström, Richard Johansson
Large language models are known to suffer from the hallucination problem in that they are prone to output statements that are false or inconsistent, indicating a lack of knowledge.…