4.5k citations · 6k across the 67 of their papers we have counts for
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IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Genta Indra Winata +2
Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the code-mixing phenomenon in Indonesian is limited, despite many languages being frequently mixe…
NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languages
Samuel Cahyawijaya, Holy Lovenia, Fajri Koto +15
Democratizing access to natural language processing (NLP) technology is crucial, especially for underrepresented and extremely low-resource languages. Previous research has focused…
Improving Query-Focused Meeting Summarization with Query-Relevant Knowledge
Tiezheng Yu, Ziwei Ji, Pascale Fung
Query-Focused Meeting Summarization (QFMS) aims to generate a summary of a given meeting transcript conditioned upon a query. The main challenges for QFMS are the long input text l…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
NeuS: Neutral Multi-News Summarization for Mitigating Framing Bias
Nayeon Lee, Yejin Bang, Tiezheng Yu +2
Media news framing bias can increase political polarization and undermine civil society. The need for automatic mitigation methods is therefore growing. We propose a new task, a ne…
NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages
Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya +11
Natural language processing (NLP) has a significant impact on society via technologies such as machine translation and search engines. Despite its success, NLP technology is only w…
VScript: Controllable Script Generation with Visual Presentation
Ziwei Ji, Yan Xu, I-Tsun Cheng +6
In order to offer a customized script tool and inspire professional scriptwriters, we present VScript. It is a controllable pipeline that generates complete scripts, including dial…
Survey of Hallucination in Natural Language Generation
Ziwei Ji, Nayeon Lee, Rita Frieske +10
Natural Language Generation (NLG) has improved exponentially in recent years thanks to the development of sequence-to-sequence deep learning technologies such as Transformer-based…
CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognition
Wenliang Dai, Samuel Cahyawijaya, Tiezheng Yu +10
With the rise of deep learning and intelligent vehicle, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities. In-car…
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…
NER-BERT: A Pre-trained Model for Low-Resource Entity Tagging
Zihan Liu, Feijun Jiang, Yuxiang Hu +2
Named entity recognition (NER) models generally perform poorly when large training datasets are unavailable for low-resource domains. Recently, pre-training a large-scale language…
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…
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 (…
Zero-Shot Dialogue State Tracking via Cross-Task Transfer
Zhaojiang Lin, Bing Liu, Andrea Madotto +8
Zero-shot transfer learning for dialogue state tracking (DST) enables us to handle a variety of task-oriented dialogue domains without the expense of collecting in-domain data. In…
Assessing Political Prudence of Open-domain Chatbots
Yejin Bang, Nayeon Lee, Etsuko Ishii +2
Politically sensitive topics are still a challenge for open-domain chatbots. However, dealing with politically sensitive content in a responsible, non-partisan, and safe behavior w…
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…
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data
Wei-Jen Ko, Ahmed El-Kishky, Adithya Renduchintala +6
The scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages. Fortunately, some low-resource languages are lin…
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…
QAConv: Question Answering on Informative Conversations
Chien-Sheng Wu, Andrea Madotto, Wenhao Liu +2
This paper introduces QAConv, a new question answering (QA) dataset that uses conversations as a knowledge source. We focus on informative conversations, including business emails,…