activity
20182023
most citedSurvey of Hallucination in Natural Language Generation

4.5k citations · 5.5k across the 41 of their papers we have counts for

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Showing 2019Show all

14 papers · 1 filter

cs.CL2019★ 14 cited

Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systems

Zihan Liu, Genta Indra Winata, Zhaojiang Lin +2

Recently, data-driven task-oriented dialogue systems have achieved promising performance in English. However, developing dialogue systems that support low-resource languages remain…

cs.CL2019

Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables

Zihan Liu, Jamin Shin, Yan Xu +4

Despite the surging demands for multilingual task-oriented dialog systems (e.g., Alexa, Google Home), there has been less research done in multilingual or cross-lingual scenarios.…

cs.CL2019★ 1 cited

Lightweight and Efficient End-to-End Speech Recognition Using Low-Rank Transformer

Genta Indra Winata, Samuel Cahyawijaya, Zhaojiang Lin +2

Highly performing deep neural networks come at the cost of computational complexity that limits their practicality for deployment on portable devices. We propose the low-rank trans…

cs.CL2019

Code-Switched Language Models Using Neural Based Synthetic Data from Parallel Sentences

Genta Indra Winata, Andrea Madotto, Chien-Sheng Wu +1

Training code-switched language models is difficult due to lack of data and complexity in the grammatical structure. Linguistic constraint theories have been used for decades to ge…

cs.CL2019

Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition

Genta Indra Winata, Zhaojiang Lin, Jamin Shin +2

In countries that speak multiple main languages, mixing up different languages within a conversation is commonly called code-switching. Previous works addressing this challenge mai…

cs.CL2019

Clickbait? Sensational Headline Generation with Auto-tuned Reinforcement Learning

Peng Xu, Chien-Sheng Wu, Andrea Madotto +1

Sensational headlines are headlines that capture people's attention and generate reader interest. Conventional abstractive headline generation methods, unlike human writers, do not…