Sökning: id:"swepub:oai:DiVA.org:ltu-103097" >
Bipol :
Bipol : Multi-axes Evaluation of Bias with Explainability in BenchmarkDatasets
-
- Adewumi, Tosin, 1978- (författare)
- Luleå tekniska universitet,EISLAB
-
- Södergren, Isabella (författare)
- Luleå tekniska universitet,Digitala tjänster och system
-
- Alkhaled, Lama (författare)
- Luleå tekniska universitet,EISLAB
-
visa fler...
-
- Sabry, Sana Sabah (författare)
- Luleå tekniska universitet,EISLAB
-
- Liwicki, Foteini (författare)
- Luleå tekniska universitet,EISLAB
-
- Liwicki, Marcus (författare)
- Luleå tekniska universitet,EISLAB
-
visa färre...
-
(creator_code:org_t)
- Incoma Ltd. 2023
- 2023
- Engelska.
-
Ingår i: Proceedings of Recent Advances in Natural Language Processing. - : Incoma Ltd.. ; , s. 1-10
- Relaterad länk:
-
https://doi.org/10.2...
-
visa fler...
-
https://urn.kb.se/re...
-
https://doi.org/10.2...
-
visa färre...
Abstract
Ämnesord
Stäng
- We investigate five English NLP benchmark datasets (on the superGLUE leaderboard) and two Swedish datasets for bias, along multiple axes. The datasets are the following: Boolean Question (Boolq), CommitmentBank (CB), Winograd Schema Challenge (WSC), Winogender diagnostic (AXg), Recognising Textual Entailment (RTE), Swedish CB, and SWEDN. Bias can be harmful and it is known to be common in data, which ML models learn from. In order to mitigate bias in data, it is crucial to be able to estimate it objectively. We use bipol, a novel multi-axes bias metric with explainability, to estimate and explain how much bias exists in these datasets. Multilingual, multi-axes bias evaluation is not very common. Hence, we also contribute a new, large Swedish bias-labeled dataset (of 2 million samples), translated from the English version and train the SotA mT5 model on it. In addition, we contribute new multi-axes lexica for bias detection in Swedish. We make the codes, model, and new dataset publicly available.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
Nyckelord
- Maskininlärning
- Machine Learning
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)