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Our work on quality estimation of non-English Wikipedia articles is on arXiv! 🎉 arxiv.org/abs/2411.05527v1
In collaboration with @akulmizev, Wessel Poelman, @EstherPloeger, @mmbollmann, @johannesbjerva, Jiaming Luo, @heather_nlp, and @mdlhx at @lagom_nlp✨
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We evaluate the downstream impact of quality filtering on Wikipedia by training tiny monolingual pretrained models for each Wikipedia to find that data quality pruning is an effective means for resource-efficient training without hurting performance, especially for LRLs.
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Our work on quality estimation for non-English Wikipedia articles is finally out in the wild 👀. It spread before we had the chance to publicise it haha, but watch out for our upcoming thread on this next week!
"How Good is Your Wikipedia?" a critical analysis of the Wikipedia content quality beyond English, revealing widespread issues such as a high percentage of one-line articles and duplicate articles.
(Tatariya et al, 2024)
arxiv.org/pdf/2411.05527
I am happy to present our latest work at EMNLP 2024 on the interpretability of pixel-based language models! 🎉
@vgaraujov @ThomasBauwens_ @mdlhx
Pixology: Probing the Linguistic and Visual Capabilities of Pixel-based Language Models
arxiv.org/abs/2410.12011
#NLProc
Additionally, we examine variants of PIXEL trained with different text rendering strategies, discovering that introducing certain orthographic constraints at the input level can facilitate earlier learning of surface-level features.
Kushal Tatariya retweeted
Leuven goes to Leiden in 10 days! We'll be presenting two posters about data quality of non-English Wikipedias and about typologically informed language sampling 👀 see you there!
10 days until #CLIN34! The 34th edition of Computational Linguistics in the Netherlands, held at @UniLeiden this year.
We present the program on clin34.leidenuniv.nl/
Registration is still possible!
Kushal Tatariya retweeted
The camera ready version is now up!
arxiv.org/abs/2310.19567
We hope to present this at ACL next year.
To summarize our contributions:
1. The first ever benchmark for Creole NLP
2. 8 NLP tasks and 28 Creoles
3. Human generated/checked data
Hopefully this is used as a starting point for future work on Creoles.
CreoleVal has been accepted to TACL! Hearty congratulations to all authors, especially @heather_nlp who grinded hard to get this work complete! Updated manuscript to go up soon.
This marks my 4th paper on Creoles!
Kushal Tatariya retweeted
✨Sociolinguistically Informed Interpretability: A Case Study on Hinglish Emotion Classification
Paper: aclanthology.org/2024.sigtyp…
Talk: youtube.com/watch?v=8MTQTSUq…
#SIGTYP2024 #SIGTYP #EACL2024
Kushal Tatariya retweeted
These two papers are being presented today @#EACL2024 @sig_typ ! @EstherPloeger will present at 11h40 and @KushalTatariya at 15h20!
My paper on 'Sociolinguistically Informed Interpretability: A Case Study on Hinglish Emotion Classification' is now on arXiv!🎉
Watch out for it at SIGTYP @ EACL 2024! #NLProc
@mdlhx @heather_nlp @johannesbjerva
arxiv.org/abs/2402.03137
We use LIME and token-level language ID to examine the effect of language on emotion prediction across 3 PLMs finetuned on a Hinglish emotion classification dataset.











