The Adapter-Bot: All-In-One Controllable Conversational Model

08/28/2020
by   Andrea Madotto, et al.
5

Considerable progress has been made towards conversational models that generate coherent and fluent responses by training large language models on large dialogue datasets. These models have little or no control of the generated responses and miss two important features: continuous dialogue skills integration and seamlessly leveraging diverse knowledge sources. In this paper, we propose the Adapter-Bot, a dialogue model that uses a fixed backbone conversational model such as DialGPT (Zhang et al., 2019) and triggers on-demand dialogue skills (e.g., emphatic response, weather information, movie recommendation) via different adapters (Houlsby et al., 2019). Each adapter can be trained independently, thus allowing a continual integration of skills without retraining the entire model. Depending on the skills, the model is able to process multiple knowledge types, such as text, tables, and graphs, in a seamless manner. The dialogue skills can be triggered automatically via a dialogue manager, or manually, thus allowing high-level control of the generated responses. At the current stage, we have implemented 12 response styles (e.g., positive, negative etc.), 8 goal-oriented skills (e.g. weather information, movie recommendation, etc.), and personalized and emphatic responses. We evaluate our model using automatic evaluation by comparing it with existing state-of-the-art conversational models, and we have released an interactive system at adapter.bot.ust.hk.

READ FULL TEXT

page 1

page 2

page 3

page 4

10/09/2020

Plug-and-Play Conversational Models

There has been considerable progress made towards conversational models ...
08/28/2019

DeepCopy: Grounded Response Generation with Hierarchical Pointer Networks

Recent advances in neural sequence-to-sequence models have led to promis...
01/20/2021

WeChat AI's Submission for DSTC9 Interactive Dialogue Evaluation Track

We participate in the DSTC9 Interactive Dialogue Evaluation Track (Gunas...
12/05/2020

Modeling and Utilizing User's Internal State in Movie Recommendation Dialogue

Intelligent dialogue systems are expected as a new interface between hum...
04/28/2017

Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models

Neural conversational models require substantial amounts of dialogue dat...
07/15/2021

Internet-Augmented Dialogue Generation

The largest store of continually updating knowledge on our planet can be...
01/07/2020

Attention over Parameters for Dialogue Systems

Dialogue systems require a great deal of different but complementary exp...

Code Repositories

adapterbot

The Adapter-Bot: All-In-One Controllable Conversational Model


view repo