Search Results for author: Yinpei Dai

Found 10 papers, 4 papers with code

Task-Oriented Dialogue System as Natural Language Generation

1 code implementation31 Aug 2021 Weizhi Wang, Zhirui Zhang, Junliang Guo, Yinpei Dai, Boxing Chen, Weihua Luo

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 like GPT-2 and simplify complicated delexicalization prepossessing.

Text Generation Transfer Learning

Transferable Dialogue Systems and User Simulators

1 code implementation ACL 2021 Bo-Hsiang Tseng, Yinpei Dai, Florian Kreyssig, Bill Byrne

Our goal is to develop a modelling framework that can incorporate new dialogue scenarios through self-play between the two agents.

Domain Adaptation Transfer Learning

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

no code implementations1 Jun 2021 Yinpei Dai, Hangyu Li, Yongbin Li, Jian Sun, Fei Huang, Luo Si, Xiaodan Zhu

Existing dialog state tracking (DST) models are trained with dialog data in a random order, neglecting rich structural information in a dataset.

 Ranked #1 on Multi-domain Dialogue State Tracking on MULTIWOZ 2.1 (using extra training data)

Multi-domain Dialogue State Tracking

Elastic CRFs for Open-ontology Slot Filling

no code implementations4 Nov 2018 Yinpei Dai, Yichi Zhang, Zhijian Ou, Yanmeng Wang, Junlan Feng

Second, the one-hot encoding of slot labels ignores the semantic meanings and relations for slots, which are implicit in their natural language descriptions.

Slot Filling

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

1 code implementation WS 2018 Lina Rojas-Barahona, Bo-Hsiang Tseng, Yinpei Dai, Clare Mansfield, Osman Ramadan, Stefan Ultes, Michael Crawford, Milica Gasic

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, entailment and sentiment analysis.

Natural Language Processing Sentence Embeddings +2

Tracking of enriched dialog states for flexible conversational information access

no code implementations9 Nov 2017 Yinpei Dai, Zhijian Ou, Dawei Ren, Pengfei Yu

The above observations motivate us to enrich current representation of dialog states and collect a brand new dialog dataset about movies, based upon which we build a new DST, called enriched DST (EDST), for flexible accessing movie information.

Slot Filling

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