Completed
Intro
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Neural Nets for NLP 2017 - Models of Dialog
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro
- 2 Types of Dialog
- 3 Two Paradigms
- 4 Generation-based Models (Ritter et al. 2011)
- 5 Neural Models for Dialog Response Generation
- 6 Hierarchical Encoder- decoder Model (Serban et al. 2016)
- 7 Dialog allows Much More Varied Responses
- 8 Diversity Promoting Objective for Conversation (Li et al. 2016)
- 9 Diversity is a Problem for Evaluation!
- 10 Using Multiple References with Human Evaluation Scores (Gallay et al. 2015)
- 11 Learning to Evaluate • Use context, true response, and actual response to learn a regressor that predicts goodness (Lowe et al. 2017) • Important similar to model, but has access to reference
- 12 Problem 3: Dialog Agents should have Personality
- 13 Personality Infused Dialog (Mairesse et al. 2007)
- 14 Persona-based Neural Dialog Model (Li et al. 2017)
- 15 Dialog Response Retrieval
- 16 Retrieval-based Chat (Lee et al. 2009)
- 17 Neural Response Retrieval (Nio et al. 2014)
- 18 Smart Reply for Email Retrieval (Kannan et al. 2016)
- 19 Traditional Task-completion Dialog Framework
- 20 NLU (for Slot Filling) w/ Neural Nets (Mesnil et al. 2015)
- 21 Dialog State Tracking
- 22 Language Generation from Dialog State w/ Neural Nets (Wen et al. 2015)
