565 citations · 1.1k across the 41 of their papers we have counts for
10 papers · 1 filter
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…
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…
Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking
Zhaojiang Lin, Bing Liu, Seungwhan Moon +7
Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented dialogue in unseen domains without the expense of collecting in-domain data. In this paper,…
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,…
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…
Dynamically Addressing Unseen Rumor via Continual Learning
Nayeon Lee, Andrea Madotto, Yejin Bang +1
Rumors are often associated with newly emerging events, thus, an ability to deal with unseen rumors is crucial for a rumor veracity classification model. Previous works address thi…
Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding
Nouha Dziri, Andrea Madotto, Osmar Zaiane +1
Dialogue systems powered by large pre-trained language models (LM) exhibit an innate ability to deliver fluent and natural-looking responses. Despite their impressive generation pe…
Mitigating Media Bias through Neutral Article Generation
Nayeon Lee, Yejin Bang, Andrea Madotto +1
Media bias can lead to increased political polarization, and thus, the need for automatic mitigation methods is growing. Existing mitigation work displays articles from multiple ne…
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…
Towards Few-Shot Fact-Checking via Perplexity
Nayeon Lee, Yejin Bang, Andrea Madotto +2
Few-shot learning has drawn researchers' attention to overcome the problem of data scarcity. Recently, large pre-trained language models have shown great performance in few-shot le…