7 citations · 16 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
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…
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…
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…
Converse, Focus and Guess -- Towards Multi-Document Driven Dialogue
Han Liu, Caixia Yuan, Xiaojie Wang +3
We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue. To benchmark pr…
Answer-Driven Visual State Estimator for Goal-Oriented Visual Dialogue
Zipeng Xu, Fangxiang Feng, Xiaojie Wang +3
A goal-oriented visual dialogue involves multi-turn interactions between two agents, Questioner and Oracle. During which, the answer given by Oracle is of great significance, as it…