565 citations · 1.3k across the 96 of their papers we have counts for
15 papers · 1 filter
ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation
Holy Lovenia, Samuel Cahyawijaya, Genta Indra Winata +11
Code-switching is a speech phenomenon occurring when a speaker switches language during a conversation. Despite the spontaneous nature of code-switching in conversational spoken la…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Few-Shot Bot: Prompt-Based Learning for Dialogue Systems
Andrea Madotto, Zhaojiang Lin, Genta Indra Winata +1
Learning to converse using only a few examples is a great challenge in conversational AI. The current best conversational models, which are either good chit-chatters (e.g., Blender…
Greenformer: Factorization Toolkit for Efficient Deep Neural Networks
Samuel Cahyawijaya, Genta Indra Winata, Holy Lovenia +4
While the recent advances in deep neural networks (DNN) bring remarkable success, the computational cost also increases considerably. In this paper, we introduce Greenformer, a too…
Language Models are Few-shot Multilingual Learners
Genta Indra Winata, Andrea Madotto, Zhaojiang Lin +3
General-purpose language models have demonstrated impressive capabilities, performing on par with state-of-the-art approaches on a range of downstream natural language processing (…
CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue System
Etsuko Ishii, Yan Xu, Genta Indra Winata +5
Information-seeking dialogue systems, including knowledge identification and response generation, aim to respond to users with fluent, coherent, and informative responses based on…
X2Parser: Cross-Lingual and Cross-Domain Framework for Task-Oriented Compositional Semantic Parsing
Zihan Liu, Genta Indra Winata, Peng Xu +1
Task-oriented compositional semantic parsing (TCSP) handles complex nested user queries and serves as an essential component of virtual assistants. Current TCSP models rely on nume…
BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling
Zhaojiang Lin, Andrea Madotto, Genta Indra Winata +5
Task-oriented dialogue (ToD) benchmarks provide an important avenue to measure progress and develop better conversational agents. However, existing datasets for end-to-end ToD mode…
ERICA: An Empathetic Android Companion for Covid-19 Quarantine
Etsuko Ishii, Genta Indra Winata, Samuel Cahyawijaya +3
Over the past year, research in various domains, including Natural Language Processing (NLP), has been accelerated to fight against the COVID-19 pandemic, yet such research has jus…
Nora: The Well-Being Coach
Genta Indra Winata, Holy Lovenia, Etsuko Ishii +3
The current pandemic has forced people globally to remain in isolation and practice social distancing, which creates the need for a system to combat the resulting loneliness and ne…
Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translation
Zihan Liu, Genta Indra Winata, Pascale Fung
The data scarcity in low-resource languages has become a bottleneck to building robust neural machine translation systems. Fine-tuning a multilingual pre-trained model (e.g., mBART…
Retrieval-Free Knowledge-Grounded Dialogue Response Generation with Adapters
Yan Xu, Etsuko Ishii, Samuel Cahyawijaya +5
To diversify and enrich generated dialogue responses, knowledge-grounded dialogue has been investigated in recent years. The existing methods tackle the knowledge grounding challen…
Multilingual Transfer Learning for Code-Switched Language and Speech Neural Modeling
Genta Indra Winata
In this thesis, we address the data scarcity and limitations of linguistic theory by proposing language-agnostic multi-task training methods. First, we introduce a meta-learning-ba…
IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation
Samuel Cahyawijaya, Genta Indra Winata, Bryan Wilie +9
Natural language generation (NLG) benchmarks provide an important avenue to measure progress and develop better NLG systems. Unfortunately, the lack of publicly available NLG bench…
Are Multilingual Models Effective in Code-Switching?
Genta Indra Winata, Samuel Cahyawijaya, Zihan Liu +3
Multilingual language models have shown decent performance in multilingual and cross-lingual natural language understanding tasks. However, the power of these multilingual models i…