activity
20192023
most citedFew-Shot Bot: Prompt-Based Learning for Dialogue Systems

45 citations · 332 across the 33 of their papers we have counts for

collaborators

62 papers

cs.CL20231 cited

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…

cs.CL20221 cited

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…

cs.CL202145 cited

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…

cs.LG20213 cited

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…

cs.CL2021

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 (…

cs.CL20212 cited

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…