Open-Domain Dialog
32 papers with code • 1 benchmarks • 11 datasets
Benchmarks
These leaderboards are used to track progress in Open-Domain Dialog
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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Datasets
Reddit
KILT
MultiDoc2Dial
MMDialog
CPED
ProsocialDialog
DuLeMon
Latest papers
Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
Multiple different responses are often plausible for a given open domain dialog context.
HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations
Weixin-Liang/HERALD
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ACL 2021
Open-domain dialog systems have a user-centric goal: to provide humans with an engaging conversation experience.
CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation
chujiezheng/CoMAE
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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.
ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation
microsoft/ProphetNet
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ACL 2021
ProphetNet is a pre-training based natural language generation method which shows powerful performance on English text summarization and question generation tasks.
Hurdles to Progress in Long-form Question Answering
martiansideofthemoon/hurdles-longform-qa
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NAACL 2021
The task of long-form question answering (LFQA) involves retrieving documents relevant to a given question and using them to generate a paragraph-length answer.
Dialogue Response Ranking Training with Large-Scale Human Feedback Data
golsun/dialogrpt
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EMNLP 2020
Particularly, our ranker outperforms the conventional dialog perplexity baseline with a large margin on predicting Reddit feedback.
KILT: a Benchmark for Knowledge Intensive Language Tasks
We test both task-specific and general baselines, evaluating downstream performance in addition to the ability of the models to provide provenance.
Are Neural Open-Domain Dialog Systems Robust to Speech Recognition Errors in the Dialog History? An Empirical Study
Large end-to-end neural open-domain chatbots are becoming increasingly popular.
Unsupervised Evaluation of Interactive Dialog with DialoGPT
shikib/fed
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SIGDIAL (ACL) 2020
It is important to define meaningful and interpretable automatic evaluation metrics for open-domain dialog research.
Probing Neural Dialog Models for Conversational Understanding
AbdulSaleh/dialog-probing
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WS 2020
The predominant approach to open-domain dialog generation relies on end-to-end training of neural models on chat datasets.
