91 citations · 123 across the 24 of their papers we have counts for
5 papers · 1 filter
Quantized-Dialog Language Model for Goal-Oriented Conversational Systems
R. Chulaka Gunasekara, David Nahamoo, Lazaros C. Polymenakos +2
We propose a novel methodology to address dialog learning in the context of goal-oriented conversational systems. The key idea is to quantize the dialog space into clusters and cre…
A Large-Scale Corpus for Conversation Disentanglement
Jonathan K. Kummerfeld, Sai R. Gouravajhala, Joseph Peper +6
Disentangling conversations mixed together in a single stream of messages is a difficult task, made harder by the lack of large manually annotated datasets. We created a new datase…
Learning End-to-End Goal-Oriented Dialog with Multiple Answers
Janarthanan Rajendran, Jatin Ganhotra, Satinder Singh +1
In a dialog, there can be multiple valid next utterances at any point. The present end-to-end neural methods for dialog do not take this into account. They learn with the assumptio…
Knowledge-based end-to-end memory networks
Jatin Ganhotra, Lazaros Polymenakos
End-to-end dialog systems have become very popular because they hold the promise of learning directly from human to human dialog interaction. Retrieval and Generative methods have…
NE-Table: A Neural key-value table for Named Entities
Janarthanan Rajendran, Jatin Ganhotra, Xiaoxiao Guo +3
Many Natural Language Processing (NLP) tasks depend on using Named Entities (NEs) that are contained in texts and in external knowledge sources. While this is easy for humans, the…