MarkusSagen/Master-Thesis-Multilingual-Longformer
Master thesis with code investigating methods for incorporating long-context reasoning in low-resource languages, without the need to pre-train from scratch. We investigated if multilingual models could inherit these properties by making it an Efficient Transformer (s.a. the Longformer architecture).
Jupyter NotebookMIT
Stargazers
- 40647045S
- 42cosmos
- 4332001876
- amansinha09Nancy, France
- andreasvcGroningen
- azsh1725Saint Petersburg
- baoivyHo Chi Minh University of Technology - VNUHCM
- barana91
- carlrynCopenhagen
- chen-yuxuanFreie Universität Berlin
- dennis9707
- dennlingerCohere
- gabrielcatalin191200
- icesonata
- jw0831Republic of Korea
- KDercksenWorld Brain Scholar
- khandnshrimp
- llkkk194
- lraithel@DFKI-NLP
- MarkusSagen@demaai
- michael81045NTNU
- mosh98Tietoevry
- mralexdmitriy
- mukeshmithrakumar@mintage
- NtaylorOXUniversity of Oxford
- paudan@Intellerts
- subhasisjAlef Education
- UnheatedMindverse AI
- vdeeplearn
- VinACE
- Wi1y-project
- yetianshThe University of Hong Kong