Elman Mansimov | DeepAI

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∙ 05/24/2023

Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent Classification

Intent classification (IC) plays an important role in task-oriented dial...

0 Mujeen Sung, et al. ∙

∙ 02/16/2023

Conversation Style Transfer using Few-Shot Learning

Conventional text style transfer approaches for natural language focus o...

0 Shamik Roy, et al. ∙

∙ 02/04/2023

Improving Prediction Backward-Compatiblility in NLP Model Upgrade with Gated Fusion

When upgrading neural models to a newer version, new errors that were no...

0 Yi-An Lai, et al. ∙

∙ 01/25/2023

Backward Compatibility During Data Updates by Weight Interpolation

Backward compatibility of model predictions is a desired property when u...

0 Raphael Schumann, et al. ∙

∙ 12/20/2022

Dialog2API: Task-Oriented Dialogue with API Description and Example Programs

Functionality and dialogue experience are two important factors of task-...

0 Raphael Shu, et al. ∙

∙ 04/14/2022

Label Semantic Aware Pre-training for Few-shot Text Classification

In text classification tasks, useful information is encoded in the label...

0 Aaron Mueller, et al. ∙

∙ 02/07/2022

Measuring and Reducing Model Update Regression in Structured Prediction for NLP

Recent advance in deep learning has led to rapid adoption of machine lea...

12 Deng Cai, et al. ∙

∙ 09/29/2021

Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System

Pre-trained language models have been recently shown to benefit task-ori...

4 Yixuan Su, et al. ∙

∙ 09/09/2021

Semantic Parsing in Task-Oriented Dialog with Recursive Insertion-based Encoder

We introduce a Recursive INsertion-based Encoder (RINE), a novel approac...

0 Elman Mansimov, et al. ∙

∙ 10/20/2020

Towards End-to-End In-Image Neural Machine Translation

In this paper, we offer a preliminary investigation into the task of in-...

0 Elman Mansimov, et al. ∙

∙ 03/11/2020

Capturing document context inside sentence-level neural machine translation models with self-training

Neural machine translation (NMT) has arguably achieved human level parit...

0 Elman Mansimov, et al. ∙

∙ 05/29/2019

A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models

Undirected neural sequence models such as BERT have received renewed int...

2 Elman Mansimov, et al. ∙

∙ 03/31/2019

Molecular geometry prediction using a deep generative graph neural network

A molecule's geometry, also known as conformation, is one of a molecule'...

14 Elman Mansimov, et al. ∙

∙ 02/19/2018

Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement

We propose a conditional non-autoregressive neural sequence model based ...

0 Jason Lee, et al. ∙

∙ 08/17/2017

Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

In this work, we propose to apply trust region optimization to deep rein...

0 Yuhuai Wu, et al. ∙

∙ 11/09/2015

Generating Images from Captions with Attention

Motivated by the recent progress in generative models, we introduce a mo...

0 Elman Mansimov, et al. ∙

∙ 03/25/2015

Initialization Strategies of Spatio-Temporal Convolutional Neural Networks

We propose a new way of incorporating temporal information present in vi...

0 Elman Mansimov, et al. ∙

∙ 02/16/2015

Unsupervised Learning of Video Representations using LSTMs

We use multilayer Long Short Term Memory (LSTM) networks to learn repres...

0 Nitish Srivastava, et al. ∙

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