15 citations · 28 across the 7 of their papers we have counts for
7 papers
Gradual Fine-Tuning with Graph Routing for Multi-Source Unsupervised Domain Adaptation
Yao Ma, Samuel Louvan, Zhunxuan Wang
Multi-source unsupervised domain adaptation aims to leverage labeled data from multiple source domains for training a machine learning model to generalize well on a target domain w…
IndoNLI: A Natural Language Inference Dataset for Indonesian
Rahmad Mahendra, Alham Fikri Aji, Samuel Louvan +2
We present IndoNLI, the first human-elicited NLI dataset for Indonesian. We adapt the data collection protocol for MNLI and collect nearly 18K sentence pairs annotated by crowd wor…
Recent Neural Methods on Slot Filling and Intent Classification for Task-Oriented Dialogue Systems: A Survey
Samuel Louvan, Bernardo Magnini
In recent years, fostered by deep learning technologies and by the high demand for conversational AI, various approaches have been proposed that address the capacity to elicit and…
Simple is Better! Lightweight Data Augmentation for Low Resource Slot Filling and Intent Classification
Samuel Louvan, Bernardo Magnini
Neural-based models have achieved outstanding performance on slot filling and intent classification, when fairly large in-domain training data are available. However, as new domain…
IndoSum: A New Benchmark Dataset for Indonesian Text Summarization
Kemal Kurniawan, Samuel Louvan
Automatic text summarization is generally considered as a challenging task in the NLP community. One of the challenges is the publicly available and large dataset that is relativel…
Multi-Task Active Learning for Neural Semantic Role Labeling on Low Resource Conversational Corpus
Fariz Ikhwantri, Samuel Louvan, Kemal Kurniawan +4
Most Semantic Role Labeling (SRL) approaches are supervised methods which require a significant amount of annotated corpus, and the annotation requires linguistic expertise. In thi…