research
∙
09/18/2023
SYNDICOM: Improving Conversational Commonsense with Error-Injection and Natural Language Feedback
Commonsense reasoning is a critical aspect of human communication. Despi...
share
research
∙
03/21/2023
cTBL: Augmenting Large Language Models for Conversational Tables
An open challenge in multimodal conversational AI requires augmenting la...
research
∙
02/15/2023
Commonsense Reasoning for Conversational AI: A Survey of the State of the Art
Large, transformer-based pretrained language models like BERT, GPT, and ...
research
∙
05/13/2022
Multimodal Conversational AI: A Survey of Datasets and Approaches
As humans, we experience the world with all our senses or modalities (so...
research
∙
03/30/2021
Grounding Open-Domain Instructions to Automate Web Support Tasks
Grounding natural language instructions on the web to perform previously...
research
∙
11/24/2020
Zero-Shot Visual Slot Filling as Question Answering
This paper presents a new approach to visual zero-shot slot filling. The...
research
∙
12/22/2019
end-to-end training of a large vocabulary end-to-end speech recognition system
In this paper, we present an end-to-end training framework for building ...
research
∙
03/26/2019
Efficient Incremental Learning for Mobile Object Detection
Object detection models shipped with camera-equipped mobile devices cann...
research
∙
03/19/2019
Class-incremental Learning via Deep Model Consolidation
Deep neural networks (DNNs) often suffer from "catastrophic forgetting" ...
research
∙
02/26/2019
Generative Visual Dialogue System via Adaptive Reasoning and Weighted Likelihood Estimation
The key challenge of generative Visual Dialogue (VD) systems is to respo...
research
∙
04/18/2018
Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems
In this work, we present a hybrid learning method for training task-orie...
research
∙
01/15/2018
Building a Conversational Agent Overnight with Dialogue Self-Play
We propose Machines Talking To Machines (M2M), a framework combining aut...
research
∙
12/29/2017
Scalable Multi-Domain Dialogue State Tracking
Dialogue state tracking (DST) is a key component of task-oriented dialog...
research
∙
12/22/2017
Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning
We present a framework combining hierarchical and multi-agent deep reinf...
research
∙
11/29/2017
End-to-End Optimization of Task-Oriented Dialogue Model with Deep Reinforcement Learning
In this paper, we present a neural network based task-oriented dialogue ...
research
∙
07/07/2017
Towards Zero-Shot Frame Semantic Parsing for Domain Scaling
State-of-the-art slot filling models for goal-oriented human/machine con...
research
∙
06/14/2017
Learning and Evaluating Musical Features with Deep Autoencoders
In this work we describe and evaluate methods to learn musical embedding...
research
∙
05/08/2017
Sequential Dialogue Context Modeling for Spoken Language Understanding
Spoken Language Understanding (SLU) is a key component of goal oriented ...
research
∙
12/12/2016
A Unit Selection Methodology for Music Generation Using Deep Neural Networks
Several methods exist for a computer to generate music based on data inc...
research
∙
06/25/2016
Leveraging Semantic Web Search and Browse Sessions for Multi-Turn Spoken Dialog Systems
Training statistical dialog models in spoken dialog systems (SDS) requir...
research
∙
04/01/2016
Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding
The goal of this paper is to use multi-task learning to efficiently scal...
research
∙
02/19/2016
Contextual LSTM (CLSTM) models for Large scale NLP tasks
Documents exhibit sequential structure at multiple levels of abstraction...
research
∙
04/28/2015