Publications (6)
Hierarchical Document Encoder for Parallel Corpus Mining
Mandy Guo, Yinfei Yang, Keith Stevens +5
We explore using multilingual document embeddings for nearest neighbor mining of parallel data. Three document-level representations are investigated: (i) document embeddings gener…
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu, Mike Schuster, Zhifeng Chen +28
Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based tr…
OpenAssistant Conversations -- Democratizing Large Language Model Alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte +15
Aligning large language models (LLMs) with human preferences has proven to drastically improve usability and has driven rapid adoption as demonstrated by ChatGPT. Alignment techniq…
NusaCrowd: Open Source Initiative for Indonesian NLP Resources
Samuel Cahyawijaya, Holy Lovenia, Alham Fikri Aji +44
We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Thro…
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings
Mandy Guo, Qinlan Shen, Yinfei Yang +8
This paper presents an effective approach for parallel corpus mining using bilingual sentence embeddings. Our embedding models are trained to produce similar representations exclus…
Self-rationalization improves LLM as a fine-grained judge
Prapti Trivedi, Aditya Gulati, Oliver Molenschot +7
LLM-as-a-judge models have been used for evaluating both human and AI generated content, specifically by providing scores and rationales. Rationales, in addition to increasing tran…