most citedTODSum: Task-Oriented Dialogue Summarization with State Tracking

7 citations · 12 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2022

Domain-Oriented Prefix-Tuning: Towards Efficient and Generalizable Fine-tuning for Zero-Shot Dialogue Summarization

Lulu Zhao, Fujia Zheng, Weihao Zeng +5

The most advanced abstractive dialogue summarizers lack generalization ability on new domains and the existing researches for domain adaptation in summarization generally rely on l…

cs.CL20221 cited

Co-VQA : Answering by Interactive Sub Question Sequence

Ruonan Wang, Yuxi Qian, Fangxiang Feng +2

Most existing approaches to Visual Question Answering (VQA) answer questions directly, however, people usually decompose a complex question into a sequence of simple sub questions…

cs.CL20217 cited

TODSum: Task-Oriented Dialogue Summarization with State Tracking

Lulu Zhao, Fujia Zheng, Keqing He +7

Previous dialogue summarization datasets mainly focus on open-domain chitchat dialogues, while summarization datasets for the broadly used task-oriented dialogue haven't been explo…

cs.CL20212 cited

Capturing Event Argument Interaction via A Bi-Directional Entity-Level Recurrent Decoder

Xiangyu Xi, Wei Ye, Shikun Zhang +3

Capturing interactions among event arguments is an essential step towards robust event argument extraction (EAE). However, existing efforts in this direction suffer from two limita…

cs.CL2021

Novel Slot Detection: A Benchmark for Discovering Unknown Slot Types in the Task-Oriented Dialogue System

Yanan Wu, Zhiyuan Zeng, Keqing He +4

Existing slot filling models can only recognize pre-defined in-domain slot types from a limited slot set. In the practical application, a reliable dialogue system should know what…

cs.CL20212 cited

Modeling Discriminative Representations for Out-of-Domain Detection with Supervised Contrastive Learning

Zhiyuan Zeng, Keqing He, Yuanmeng Yan +5

Detecting Out-of-Domain (OOD) or unknown intents from user queries is essential in a task-oriented dialog system. A key challenge of OOD detection is to learn discriminative semant…