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Tobias Norlund
Tobias Norlund
Chalmers University of Technology
Verified email at norlund.se - Homepage
Title
Cited by
Cited by
Year
Exploring communicative AI: Reflections from a Swedish newsroom
A Stenbom, M Wiggberg, T Norlund
Digital Journalism 11 (9), 1622-1640, 2023
172023
Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it?
T Norlund, L Hagström, R Johansson
arXiv preprint arXiv:2109.11321, 2021
162021
Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models
E Doostmohammadi, T Norlund, M Kuhlmann, R Johansson
arXiv preprint arXiv:2305.16243, 2023
42023
Building a Swedish open-domain conversational language model
T Norlund, A Stenbom
arXiv preprint arXiv:2104.05277, 2021
42021
The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models
L Hagström, D Saynova, T Norlund, M Johansson, R Johansson
arXiv preprint arXiv:2311.01307, 2023
32023
On the generalization ability of retrieval-enhanced transformers
T Norlund, E Doostmohammadi, R Johansson, M Kuhlmann
arXiv preprint arXiv:2302.12128, 2023
32023
Cross-modal transfer between vision and language for protest detection
R Raj, K Andreasson, T Norlund, R Johansson, A Lagerberg
Proceedings of the 5th Workshop on Challenges and Applications of Automated …, 2022
12022
Parameterized context windows in Random Indexing
T Norlund, D Nilsson, M Sahlgren
Proceedings of the 1st Workshop on Representation Learning for NLP, 166-173, 2016
12016
Improving Language Models Using Augmentation and Multi-Modality
T Norlund
PQDT-Global, 2023
2023
Can We Use Small Models to Investigate Multimodal Fusion Methods?
L Hagström, T Norlund, R Johansson
Proceedings of the 2022 CLASP Conference on (Dis) embodiment, 45-50, 2022
2022
Proceedings of the 1st Workshop on Representation Learning for NLP
P Blunsom, K Cho, SB Cohen, E Grefenstette, KM Hermann, L Rimell, ...
Proceedings of the 1st Workshop on Representation Learning for NLP, 2016
2016
The Use of Distributional Semantics in Text Classification Models: Comparative performance analysis of popular word embeddings
T Norlund
2016
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