Open-Domain Dialog

32 papers with code • 1 benchmarks • 11 datasets

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Most implemented papers

Large-Scale Transfer Learning for Natural Language Generation

atselousov/transformer_chatbot_experiments ACL 2019

Large-scale pretrained language models define state of the art in natural language processing, achieving outstanding performance on a variety of tasks.

A Multi-Turn Emotionally Engaging Dialog Model

yuboxie/meed 15 Aug 2019

Open-domain dialog systems (also known as chatbots) have increasingly drawn attention in natural language processing.

Hierarchical Reinforcement Learning for Open-Domain Dialog

natashamjaques/neural_chat 17 Sep 2019

Open-domain dialog generation is a challenging problem; maximum likelihood training can lead to repetitive outputs, models have difficulty tracking long-term conversational goals, and training on standard movie or online datasets may lead to the generation of inappropriate, biased, or offensive text.

ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers

ClovaAI/ClovaCall 20 Apr 2020

Automatic speech recognition (ASR) via call is essential for various applications, including AI for contact center (AICC) services.

USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation

shikib/usr ACL 2020

The lack of meaningful automatic evaluation metrics for dialog has impeded open-domain dialog research.

Probing Neural Dialog Models for Conversational Understanding

AbdulSaleh/dialog-probing WS 2020

The predominant approach to open-domain dialog generation relies on end-to-end training of neural models on chat datasets.

ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation

microsoft/ProphetNet ACL 2021

ProphetNet is a pre-training based natural language generation method which shows powerful performance on English text summarization and question generation tasks.

CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation

chujiezheng/CoMAE Findings (ACL) 2021

However, existing methods for empathetic response generation usually either consider only one empathy factor or ignore the hierarchical relationships between different factors, leading to a weak ability of empathy modeling.