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Found 10 papers, 4 papers with code
Disentangling Language and Knowledge in Task-Oriented Dialogs
We also systematically modify existing datasets to measure disentanglement and show BoSsNet to be robust to KB modifications.
Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned
We present the Neural Covidex, a search engine that exploits the latest neural ranking architectures to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI.
Rapidly Bootstrapping a Question Answering Dataset for COVID-19
We present CovidQA, the beginnings of a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered from Kaggle's COVID-19 Open Research Dataset Challenge.
Unsupervised Learning of KB Queries in Task-Oriented Dialogs
Task-oriented dialog (TOD) systems often need to formulate knowledge base (KB) queries corresponding to the user intent and use the query results to generate system responses.
Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset
The Neural Covidex is a search engine that exploits the latest neural ranking architectures to provide information access to the COVID-19 Open Research Dataset (CORD-19) curated by the Allen Institute for AI.
Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset
We present Covidex, a search engine that exploits the latest neural ranking models to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI.
Rational Dynamic Price Model for Demand Response Programs in Modern Distribution Systems
The novelty of the proposed model lies in the fact that the financial benefits and penalties pertaining to DR are self-adjusted among customers while preserving social equity and profit of the utility.
An Adaptive Demand Response Framework using Price Elasticity Model in Distribution Networks: A Case Study
Thus, this article presents an adaptive economic DR framework with attributes of DR via a dynamic elasticity approach to model customers sensitivity.
A Bi-level Decision Framework for Incentive-Based Demand Response in Distribution Systems
It presents a bi-level decision framework under the ambit of multiple demand response providers (DRPs) in the retail competition.
Optimally Coordinated Energy Management Framework for Profit Maximization Considering Dispatchable and Non-Dispatchable Energy Resources
Contemporary distribution network can be seen with diverse dispatchable and non-dispatchable energy resources.
