Adversarial learning for neural dialogue generation
In this paper, drawing intuition from the Turing test, we propose using adversarial training for
open-domain dialogue generation: the system is trained to produce sequences that are …
open-domain dialogue generation: the system is trained to produce sequences that are …
Deep reinforcement learning for dialogue generation
Recent neural models of dialogue generation offer great promise for generating responses
for conversational agents, but tend to be shortsighted, predicting utterances one at a time …
for conversational agents, but tend to be shortsighted, predicting utterances one at a time …
Conversational ai: The science behind the alexa prize
Conversational agents are exploding in popularity. However, much work remains in the area
of social conversation as well as free-form conversation over a broad range of domains and …
of social conversation as well as free-form conversation over a broad range of domains and …
A survey of natural language generation techniques with a focus on dialogue systems-past, present and future directions
S Santhanam, S Shaikh - arXiv preprint arXiv:1906.00500, 2019 - arxiv.org
One of the hardest problems in the area of Natural Language Processing and Artificial
Intelligence is automatically generating language that is coherent and understandable to …
Intelligence is automatically generating language that is coherent and understandable to …
A simple, fast diverse decoding algorithm for neural generation
In this paper, we propose a simple, fast decoding algorithm that fosters diversity in neural
generation. The algorithm modifies the standard beam search algorithm by adding an inter …
generation. The algorithm modifies the standard beam search algorithm by adding an inter …
Training end-to-end dialogue systems with the ubuntu dialogue corpus
In this paper, we construct and train end-to-end neural network-based dialogue systems
usingan updated version of the recent Ubuntu Dialogue Corpus, a dataset containing almost …
usingan updated version of the recent Ubuntu Dialogue Corpus, a dataset containing almost …
The dialogue dodecathlon: Open-domain knowledge and image grounded conversational agents
We introduce dodecaDialogue: a set of 12 tasks that measures if a conversational agent can
communicate engagingly with personality and empathy, ask questions, answer questions by …
communicate engagingly with personality and empathy, ask questions, answer questions by …
Scientific information extraction with semi-supervised neural tagging
This paper addresses the problem of extracting keyphrases from scientific articles and
categorizing them as corresponding to a task, process, or material. We cast the problem as …
categorizing them as corresponding to a task, process, or material. We cast the problem as …
Coherent dialogue with attention-based language models
We model coherent conversation continuation via RNN-based dialogue models equipped
with a dynamic attention mechanism. Our attention-RNN language model dynamically …
with a dynamic attention mechanism. Our attention-RNN language model dynamically …
Self-supervised dialogue learning
The sequential order of utterances is often meaningful in coherent dialogues, and the order
changes of utterances could lead to low-quality and incoherent conversations. We consider …
changes of utterances could lead to low-quality and incoherent conversations. We consider …