Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking

28 September 2021

Papers citing "Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking"

6 / 6 papers shown

Title
MULTI3NLU++: A Multilingual, Multi-Intent, Multi-Domain Dataset for Natural Language Understanding in Task-Oriented Dialogue Nikita Moghe E. Razumovskaia Liane Guillou Ivan Vulić Anna Korhonen Alexandra Birch 37 13 0 20 Dec 2022
"Do you follow me?": A Survey of Recent Approaches in Dialogue State Tracking Léo Jacqmin L. Rojas-Barahona Benoit Favre 41 27 0 29 Jul 2022
Multi2WOZ: A Robust Multilingual Dataset and Conversational Pretraining for Task-Oriented Dialog Chia-Chien Hung Anne Lauscher Ivan Vulić Simone Paolo Ponzetto Goran Glavavs 25 34 0 20 May 2022
Improving In-Context Few-Shot Learning via Self-Supervised Training Mingda Chen Jingfei Du Ramakanth Pasunuru Todor Mihaylov Srini Iyer Ves Stoyanov Zornitsa Kozareva SSL AI4MH 29 63 0 03 May 2022
XQA-DST: Multi-Domain and Multi-Lingual Dialogue State Tracking Han Zhou Ignacio Iacobacci Pasquale Minervini 29 2 0 12 Apr 2022
Pre-trained Models for Natural Language Processing: A Survey Xipeng Qiu Tianxiang Sun Yige Xu Yunfan Shao Ning Dai Xuanjing Huang LM&MA VLM 243 1,450 0 18 Mar 2020