Neural approaches to conversational AI
This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …
few years. We group conversational systems into three categories:(1) question answering …
Pomdp-based statistical spoken dialog systems: A review
Statistical dialog systems (SDSs) are motivated by the need for a data-driven framework that
reduces the cost of laboriously handcrafting complex dialog managers and that provides …
reduces the cost of laboriously handcrafting complex dialog managers and that provides …
A neural network approach to context-sensitive generation of conversational responses
We present a novel response generation system that can be trained end to end on large
quantities of unstructured Twitter conversations. A neural network architecture is used to …
quantities of unstructured Twitter conversations. A neural network architecture is used to …
A deep reinforcement learning chatbot
We present MILABOT: a deep reinforcement learning chatbot developed by the Montreal
Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize competition. MILABOT is …
Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize competition. MILABOT is …
A survey of available corpora for building data-driven dialogue systems
During the past decade, several areas of speech and language understanding have
witnessed substantial breakthroughs from the use of data-driven models. In the area of …
witnessed substantial breakthroughs from the use of data-driven models. In the area of …
Chai: A chatbot ai for task-oriented dialogue with offline reinforcement learning
Conventionally, generation of natural language for dialogue agents may be viewed as a
statistical learning problem: determine the patterns in human-provided data and generate …
statistical learning problem: determine the patterns in human-provided data and generate …
A sequence-to-sequence model for user simulation in spoken dialogue systems
User simulation is essential for generating enough data to train a statistical spoken dialogue
system. Previous models for user simulation suffer from several drawbacks, such as the …
system. Previous models for user simulation suffer from several drawbacks, such as the …
Continual learning for instruction following from realtime feedback
We propose and deploy an approach to continually train an instruction-following agent from
feedback provided by users during collaborative interactions. During interaction, human …
feedback provided by users during collaborative interactions. During interaction, human …
[图书][B] Reinforcement learning for adaptive dialogue systems: a data-driven methodology for dialogue management and natural language generation
The past decade has seen a revolution in the field of spoken dialogue systems. As in other
areas of Computer Science and Artificial Intelligence, data-driven methods are now being …
areas of Computer Science and Artificial Intelligence, data-driven methods are now being …
Report from the nsf future directions workshop on automatic evaluation of dialog: Research directions and challenges
This is a report on the NSF Future Directions Workshop on Automatic Evaluation of Dialog.
The workshop explored the current state of the art along with its limitations and suggested …
The workshop explored the current state of the art along with its limitations and suggested …