activity
20172023
most citedGALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection

44 citations · 129 across the 14 of their papers we have counts for

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14 papers · 1 filter

cs.CL2023

Long-Tailed Question Answering in an Open World

Yi Dai, Hao Lang, Yinhe Zheng +2

Real-world data often have an open long-tailed distribution, and building a unified QA model supporting various tasks is vital for practical QA applications. However, it is non-tri…

cs.CL2023

Domain Incremental Lifelong Learning in an Open World

Yi Dai, Hao Lang, Yinhe Zheng +3

Lifelong learning (LL) is an important ability for NLP models to learn new tasks continuously. Architecture-based approaches are reported to be effective implementations for LL mod…

cs.CL2023★ 3 cited

SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents

Shuzheng Si, Wentao Ma, Haoyu Gao +7

Task-oriented dialogue (TOD) models have made significant progress in recent years. However, previous studies primarily focus on datasets written by annotators, which has resulted…

cs.CL2022

CGoDial: A Large-Scale Benchmark for Chinese Goal-oriented Dialog Evaluation

Yinpei Dai, Wanwei He, Bowen Li +5

Practical dialog systems need to deal with various knowledge sources, noisy user expressions, and the shortage of annotated data. To better solve the above problems, we propose CGo…

cs.CL2022★ 6 cited

SPACE-3: Unified Dialog Model Pre-training for Task-Oriented Dialog Understanding and Generation

Wanwei He, Yinpei Dai, Min Yang +4

Recently, pre-training methods have shown remarkable success in task-oriented dialog (TOD) systems. However, most existing pre-trained models for TOD focus on either dialog underst…

cs.CL2022★ 14 cited

SPACE-2: Tree-Structured Semi-Supervised Contrastive Pre-training for Task-Oriented Dialog Understanding

Wanwei He, Yinpei Dai, Binyuan Hui +6

Pre-training methods with contrastive learning objectives have shown remarkable success in dialog understanding tasks. However, current contrastive learning solely considers the se…

cs.CL2021★ 44 cited

GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection

Wanwei He, Yinpei Dai, Yinhe Zheng +9

Pre-trained models have proved to be powerful in enhancing task-oriented dialog systems. However, current pre-training methods mainly focus on enhancing dialog understanding and ge…

cs.CL2021★ 35 cited

Task-Oriented Dialogue System as Natural Language Generation

Weizhi Wang, Zhirui Zhang, Junliang Guo +3

In this paper, we propose to formulate the task-oriented dialogue system as the purely natural language generation task, so as to fully leverage the large-scale pre-trained models…

cs.CL2021★ 2 cited

Transferable Dialogue Systems and User Simulators

Bo-Hsiang Tseng, Yinpei Dai, Florian Kreyssig +1

One of the difficulties in training dialogue systems is the lack of training data. We explore the possibility of creating dialogue data through the interaction between a dialogue s…

cs.CL2021★ 4 cited

Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialog State Tracking

Yinpei Dai, Hangyu Li, Yongbin Li +4

Existing dialog state tracking (DST) models are trained with dialog data in a random order, neglecting rich structural information in a dataset. In this paper, we propose to use cu…

cs.CL2020★ 19 cited

A Survey on Dialog Management: Recent Advances and Challenges

Yinpei Dai, Huihua Yu, Yixuan Jiang +3

Dialog management (DM) is a crucial component in a task-oriented dialog system. Given the dialog history, DM predicts the dialog state and decides the next action that the dialog a…

cs.CL2018★ 2 cited

Elastic CRFs for Open-ontology Slot Filling

Yinpei Dai, Yichi Zhang, Hong Liu +3

Slot filling is a crucial component in task-oriented dialog systems that is used to parse (user) utterances into semantic concepts called slots. An ontology is defined by the colle…

cs.CL2018

Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural Therapy

Lina Rojas-Barahona, Bo-Hsiang Tseng, Yinpei Dai +5

In recent years, we have seen deep learning and distributed representations of words and sentences make impact on a number of natural language processing tasks, such as similarity,…

cs.CL2017

Tracking of enriched dialog states for flexible conversational information access

Yinpei Dai, Zhijian Ou, Dawei Ren +1

Dialog state tracking (DST) is a crucial component in a task-oriented dialog system for conversational information access. A common practice in current dialog systems is to define…