55 citations · 188 across the 19 of their papers we have counts for
54 papers · 1 filter
Multi2WOZ: A Robust Multilingual Dataset and Conversational Pretraining for Task-Oriented Dialog
Chia-Chien Hung, Anne Lauscher, Ivan Vulić +2
Research on (multi-domain) task-oriented dialog (TOD) has predominantly focused on the English language, primarily due to the shortage of robust TOD datasets in other languages, pr…
NLU++: A Multi-Label, Slot-Rich, Generalisable Dataset for Natural Language Understanding in Task-Oriented Dialogue
Iñigo Casanueva, Ivan Vulić, Georgios P. Spithourakis +1
We present NLU++, a novel dataset for natural language understanding (NLU) in task-oriented dialogue (ToD) systems, with the aim to provide a much more challenging evaluation envir…
EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification
Georgios P. Spithourakis, Ivan Vulić, Michał Lis +2
Knowledge-based authentication is crucial for task-oriented spoken dialogue systems that offer personalised and privacy-focused services. Such systems should be able to enrol (E),…
Improved and Efficient Conversational Slot Labeling through Question Answering
Gabor Fuisz, Ivan Vulić, Samuel Gibbons +2
Transformer-based pretrained language models (PLMs) offer unmatched performance across the majority of natural language understanding (NLU) tasks, including a body of question answ…
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models
Ivan Vulić, Pei-Hao Su, Sam Coope +5
Transformer-based language models (LMs) pretrained on large text collections are proven to store a wealth of semantic knowledge. However, 1) they are not effective as sentence enco…
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models
Qianchu Liu, Fangyu Liu, Nigel Collier +2
Recent work indicated that pretrained language models (PLMs) such as BERT and RoBERTa can be transformed into effective sentence and word encoders even via simple self-supervised t…