Betswish

Ph.D. candidate at University of Groningen

University of GroningenGroningen, Netherlands

Pinned Repositories

Betswish.github.io
Personal Homepage
Language:SCSS00
Cross-Lingual-Consistency
Easy-to-use framework for evaluating cross-lingual consistency of factual knowledge (Supported LLaMA, BLOOM, mT5, RoBERTa, etc.) Paper here: https://aclanthology.org/2023.emnlp-main.658/
Language:Python21 2 21
genbench_cbt
The official Genbench Collaborative Benchmarking Task repository.
Language:Python00
ik-nlp-tutorials
Lab tutorials for the MSc NLP course at the University of Groningen 🐮
Language:Jupyter Notebook00
inseq
Interpretability for sequence generation models 🐛 🔍
Language:Python00
MIRAGE
Easy-to-use MIRAGE code for faithful answer attribution in RAG applications. Paper: https://arxiv.org/abs/2406.13663
Language:Python16 2 21
MIRAGE-reproduce
Code for reproducing all experimental results in our MIRAGE paper: https://arxiv.org/abs/2406.13663
Language:Python10
ik-nlp-tutorials
Lab tutorials for the MSc NLP course at the University of Groningen 🐮
Language:Jupyter Notebook20 3 319
inseq
Interpretability for sequence generation models 🐛 🔍
Language:Python378 10 8836
acad-homepage.github.io
AcadHomepage: A Modern and Responsive Academic Personal Homepage
Language:SCSS1.5k 3 362.9k

Betswish/Cross-Lingual-Consistency
Easy-to-use framework for evaluating cross-lingual consistency of factual knowledge (Supported LLaMA, BLOOM, mT5, RoBERTa, etc.) Paper here: https://aclanthology.org/2023.emnlp-main.658/
Language:Python21 2 21
Betswish/MIRAGE
Easy-to-use MIRAGE code for faithful answer attribution in RAG applications. Paper: https://arxiv.org/abs/2406.13663
Language:Python16 2 21
Betswish/MIRAGE-reproduce
Code for reproducing all experimental results in our MIRAGE paper: https://arxiv.org/abs/2406.13663
Language:Python10
Betswish/Betswish.github.io
Personal Homepage
Language:SCSS00
Betswish/genbench_cbt
The official Genbench Collaborative Benchmarking Task repository.
Language:Python00
Betswish/ik-nlp-tutorials
Lab tutorials for the MSc NLP course at the University of Groningen 🐮
Language:Jupyter Notebook00
Betswish/inseq
Interpretability for sequence generation models 🐛 🔍
Language:Python00