Search Results for author:
Found 15 papers, 7 papers with code
BERT Goes Brrr: A Venture Towards the Lesser Error in Classifying Medical Self-Reporters on Twitter
This paper describes our team’s submission for the Social Media Mining for Health (SMM4H) 2021 shared task.
Investigating Text Shortening Strategy in BERT: Truncation vs Summarization
In this study, we investigate the performance of document truncation and summarization in text classification tasks.
Simple Hack for Transformers against Heavy Long-Text Classification on a Time- and Memory-Limited GPU Service
Using the best hack found, we then compare 512, 256, and 128 tokens length.
COPAL-ID: Indonesian Language Reasoning with Local Culture and Nuances
Unlike the previous Indonesian COPA dataset (XCOPA-ID), COPAL-ID incorporates Indonesian local and cultural nuances, and therefore, provides a more natural portrayal of day-to-day causal reasoning within the Indonesian cultural sphere.
On "Scientific Debt" in NLP: A Case for More Rigour in Language Model Pre-Training Research
This evidence-based position paper critiques current research practices within the language model pre-training literature.
NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages
In this work, we focus on developing resources for languages in Indonesia.
ParaCotta: Synthetic Multilingual Paraphrase Corpora from the Most Diverse Translation Sample Pair
We release our synthetic parallel paraphrase corpus across 17 languages: Arabic, Catalan, Czech, German, English, Spanish, Estonian, French, Hindi, Indonesian, Italian, Dutch, Romanian, Russian, Swedish, Vietnamese, and Chinese.
Nix-TTS: Lightweight and End-to-End Text-to-Speech via Module-wise Distillation
We present Nix-TTS, a lightweight TTS achieved via knowledge distillation to a high-quality yet large-sized, non-autoregressive, and end-to-end (vocoder-free) TTS teacher model.
One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia
NLP research is impeded by a lack of resources and awareness of the challenges presented by underrepresented languages and dialects.
Which Student is Best? A Comprehensive Knowledge Distillation Exam for Task-Specific BERT Models
We perform knowledge distillation (KD) benchmark from task-specific BERT-base teacher models to various student models: BiLSTM, CNN, BERT-Tiny, BERT-Mini, and BERT-Small.
Synthetic Source Language Augmentation for Colloquial Neural Machine Translation
Neural machine translation (NMT) is typically domain-dependent and style-dependent, and it requires lots of training data.
Costs to Consider in Adopting NLP for Your Business
Recent advances in Natural Language Processing (NLP) have largely pushed deep transformer-based models as the go-to state-of-the-art technique without much regard to the production and utilization cost.
Semi-Supervised Low-Resource Style Transfer of Indonesian Informal to Formal Language with Iterative Forward-Translation
In this work, we address a style-transfer from informal to formal Indonesian as a low-resource machine translation problem.
Benchmarking Multidomain English-Indonesian Machine Translation
In the context of Machine Translation (MT) from-and-to English, Bahasa Indonesia has been considered a low-resource language, and therefore applying Neural Machine Translation (NMT) which typically requires large training dataset proves to be problematic.
