most citedSimple is Better! Lightweight Data Augmentation for Low Resource Slot Filling and Intent Classification

11 citations · 12 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL20201 cited

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…

cs.CL202011 cited

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…

cs.CL2018

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…

cs.CL2018

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…

cs.CL2018

Empirical Evaluation of Character-Based Model on Neural Named-Entity Recognition in Indonesian Conversational Texts

Kemal Kurniawan, Samuel Louvan

Despite the long history of named-entity recognition (NER) task in the natural language processing community, previous work rarely studied the task on conversational texts. Such te…