Open AccessProceedings Article
DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
Yanran Li,Hui Su,Xiaoyu Shen,Wenjie Li,Ziqiang Cao,Shuzi Niu +5 more
- Vol. 1, pp 986-995
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TLDR
This paper developed a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects, such as human-written and less noisy language, the dialogues in the dataset reflect our daily communication way and cover various topics about our daily life.Abstract:
We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the dataset reflect our daily communication way and cover various topics about our daily life. We also manually label the developed dataset with communication intention and emotion information. Then, we evaluate existing approaches on DailyDialog dataset and hope it benefit the research field of dialog systems. The dataset is available on http://yanran.li/dailydialogread more
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Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
TL;DR: This paper proposed a data filtering method for open-domain dialogues, which identifies untrustworthy samples from training data with a quality measure that linearly combines seven dialogue attributes, and then scores training samples with the quality measure, sort them in descending order, and filter out those at the bottom.
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Variational Dialogue Generation with Normalizing Flows
Tien-Ching Luo,Jen-Tzung Chien +1 more
TL;DR: In this article, an inverse autoregressive flow is proposed to transform isotropic Gaussian prior to a rich distribution to enhance the diversity of generated dialogue responses, and the proposed DF-VAE is significantly better than other methods in terms of different evaluation metrics.
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Jan Milan Deriu,Don Tuggener,Pius von Däniken,Jon Ander Campos,Álvaro Rodrigo,Thiziri Belkacem,Aitor Soroa,Eneko Agirre,Mark Cieliebak +8 more
TL;DR: A cost-efficient and robust evaluation framework that replaces human-bot conversations with conversations between bots, and incorporates a metric that measures which chatbot can uphold human-like behavior the longest, i.e., \emph{Survival Analysis}.
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GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection
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TL;DR: Li et al. as mentioned in this paper proposed a semi-supervised pre-trained dialog model that explicitly learns dialog policy from limited labeled dialogs and large-scale unlabeled dialog corpora.
References
More filters
Proceedings Article
Adam: A Method for Stochastic Optimization
Diederik P. Kingma,Jimmy Ba +1 more
TL;DR: This work introduces Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments, and provides a regret bound on the convergence rate that is comparable to the best known results under the online convex optimization framework.
Proceedings Article
Neural Machine Translation by Jointly Learning to Align and Translate
TL;DR: It is conjecture that the use of a fixed-length vector is a bottleneck in improving the performance of this basic encoder-decoder architecture, and it is proposed to extend this by allowing a model to automatically (soft-)search for parts of a source sentence that are relevant to predicting a target word, without having to form these parts as a hard segment explicitly.
Proceedings ArticleDOI
Effective Approaches to Attention-based Neural Machine Translation
TL;DR: A global approach which always attends to all source words and a local one that only looks at a subset of source words at a time are examined, demonstrating the effectiveness of both approaches on the WMT translation tasks between English and German in both directions.
Journal ArticleDOI
An argument for basic emotions
TL;DR: This work has shown that not only the intensity of an emotion but also its direction may vary greatly both in the amygdala and in the brain during the course of emotion regulation.
Proceedings ArticleDOI
On the Properties of Neural Machine Translation: Encoder--Decoder Approaches
Kyunghyun Cho,Bart van Merriënboer,Dzmitry Bahdanau,Yoshua Bengio,Yoshua Bengio,Yoshua Bengio +5 more
TL;DR: In this paper, a gated recursive convolutional neural network (GRNN) was proposed to learn a grammatical structure of a sentence automatically, which performed well on short sentences without unknown words, but its performance degrades rapidly as the length of the sentence and the number of unknown words increase.