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pro vyhledávání: '"Norlund, Tobias"'
Autor:
Norlund, Tobias, Isbister, Tim, Gyllensten, Amaru Cuba, Santos, Paul Dos, Petrelli, Danila, Ekgren, Ariel, Sahlgren, Magnus
This paper presents the hitherto largest pretraining dataset for the Scandinavian languages: the Scandinavian WEb (SWEb), comprising over one trillion tokens. The paper details the collection and processing pipeline, and introduces a novel model-base
Externí odkaz:
http://arxiv.org/abs/2410.04456
The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models
Large Language Models (LLMs) make natural interfaces to factual knowledge, but their usefulness is limited by their tendency to deliver inconsistent answers to semantically equivalent questions. For example, a model might predict both "Anne Redpath p
Externí odkaz:
http://arxiv.org/abs/2311.01307
Augmenting language models with a retrieval mechanism has been shown to significantly improve their performance while keeping the number of parameters low. Retrieval-augmented models commonly rely on a semantic retrieval mechanism based on the simila
Externí odkaz:
http://arxiv.org/abs/2305.16243
Recent work on the Retrieval-Enhanced Transformer (RETRO) model has shown that off-loading memory from trainable weights to a retrieval database can significantly improve language modeling and match the performance of non-retrieval models that are an
Externí odkaz:
http://arxiv.org/abs/2302.12128
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. A proposed solution to this is to provide the model with additional d
Externí odkaz:
http://arxiv.org/abs/2109.11321
Autor:
Norlund, Tobias, Stenbom, Agnes
We present on-going work of evaluating the, to our knowledge, first large generative language model trained to converse in Swedish, using data from the online discussion forum Flashback. We conduct a human evaluation pilot study that indicates the mo
Externí odkaz:
http://arxiv.org/abs/2104.05277
Akademický článek
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Autor:
Norlund, Tobias, Marklund, Johan
En efterfrågan efter mer informativa revisionsberättelser har över tid växt fram, vilketledde till att The International Auditing and Assurance Standards Board (IAASB) år 2015introducerade ISA 701: “Communicating Key Audit Matters in the Indep
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-210597
Autor:
Norlund, Tobias
In the field of Natural Language Processing, supervised machine learning is commonly used to solve classification tasks such as sentiment analysis and text categorization. The classical way of representing the text has been to use the well known Bag-
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-127991
Autor:
Peña-Fernández, Simón1 simon.pena@ehu.eus, Meso-Ayerdi, Koldobika1 koldo.meso@ehu.eus, Larrondo-Ureta, Ainara1 ainara.larrondo@ehu.eus, Díaz-Noci, Javier2 javier.diaz@upf.edu
Publikováno v:
El Profesional de la Información. 2023, Vol. 32 Issue 2, p1-15. 15p.
