My Ph.D. supervisor Prof. Pascale Fung @pascalefung is hiring Ph.D. students for fall 2024. Please feel free to send her emails ([email protected]) if youโre interested!๐
Our KILM paper was accepted at ACL 2023! In this paper with @Tea_XuYan, @hdevamanyu, Di Jin, @AishwaryaPadma4, Yang Liu, and @dilekhakkanitur we show how atomic pieces of knowledge could be injected into a pre-trained language model. https://t.co/PBzz8v33dc @AmazonScience
I'm very happy to announce that NusaCrowd, a crowdsourcing collaboration for centralizing Indonesian corpora, is accepted in #ACL2023 Findings: https://t.co/Y8ppKcQLpc
It is a BIG momentum for IndoNLP to push datasets to be open & publicly accessible ๐ฎ๐ฉ๐ฎ๐ฉ๐ฎ๐ฉ
#IndoNLP#NLProc
๐จ We are excited to have our NusaCrowd paper accepted in #acl2023 Findings. It is the first collaborative initiative to collect Indonesian corpus ๐ฎ๐ฉ
It is a BIG momentum for IndoNLP to push datasets to be open & publicly accessible.
https://t.co/en9E0C2Hye #NLProc@aclmeeting
https://t.co/nuzWZIkRlr
FFS what is LLaMA-adapter? Just looks like prefix tuning with a learnable weight for the prefix part of self-attention. I wish people would stop pretending like they invented new things.
๐จ Exciting news! We are delighted to announce NusaCrowd, a new open-source initiative to collect and unite Indonesian NLP resources! ๐ฎ๐ฉ๐ฎ๐ฉ๐ฎ๐ฉ
Through NusaCrowd, we have gathered 137 datasets and 117 standardized data loaders covering text, audio, and image modalities๐ช๐พโจ๐๐
Large language models (LLMs) often make mistakes that are difficult to correct.
We study the problem of quickly editing these models:
Paper: https://t.co/iJCrvbcga3
Code: https://t.co/8zMmIl9WdI
w/ @_eric_mitchell_, C. Lin, @ABosselut, @chrmanning
thread ๐งต๐
We just released the IndoNLU benchmark Github repository at https://t.co/Hzac4Gf04q โญ๏ธโจThe largest benchmark for Indonesian NLP so far. You can find our open-source datasets, pre-trained models, and the starter code! #nlproc#aacl#acl#nlp#indonlp#indonlu#indobenchmark (1/n)
After a day waiting... happy to announce that our meta-learning ASR paper "Learning Fast Adaptation on Cross-Accented Speech Recognition" is accepted by Interspeech 2020. We propose a benchmark for zero-shot & few-shot settings #interspeech
Preprint https://t.co/tr6yQkcPzy