5.2k citations · 10k across the 79 of their papers we have counts for
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Learning through Dialogue Interactions by Asking Questions
Jiwei Li, Alexander H. Miller, Sumit Chopra +2
A good dialogue agent should have the ability to interact with users by both responding to questions and by asking questions, and importantly to learn from both types of interactio…
Tracking the World State with Recurrent Entity Networks
Mikael Henaff, Jason Weston, Arthur Szlam +2
We introduce a new model, the Recurrent Entity Network (EntNet). It is equipped with a dynamic long-term memory which allows it to maintain and update a representation of the state…
Dialogue Learning With Human-In-The-Loop
Jiwei Li, Alexander H. Miller, Sumit Chopra +2
An important aspect of developing conversational agents is to give a bot the ability to improve through communicating with humans and to learn from the mistakes that it makes. Most…
Key-Value Memory Networks for Directly Reading Documents
Alexander Miller, Adam Fisch, Jesse Dodge +3
Directly reading documents and being able to answer questions from them is an unsolved challenge. To avoid its inherent difficulty, question answering (QA) has been directed toward…
Learning End-to-End Goal-Oriented Dialog
Antoine Bordes, Y-Lan Boureau, Jason Weston
Traditional dialog systems used in goal-oriented applications require a lot of domain-specific handcrafting, which hinders scaling up to new domains. End-to-end dialog systems, in…
Dialog-based Language Learning
Jason Weston
A long-term goal of machine learning research is to build an intelligent dialog agent. Most research in natural language understanding has focused on learning from fixed training s…