Search Results for author: Elman Mansimov

Found 19 papers, 9 papers with code

Conversation Style Transfer using Few-Shot Learning

no code implementations16 Feb 2023 Shamik Roy, Raphael Shu, Nikolaos Pappas, Elman Mansimov, Yi Zhang, Saab Mansour, Dan Roth

Conventional text style transfer approaches for natural language focus on sentence-level style transfer without considering contextual information, and the style is described with attributes (e. g., formality).

Few-Shot Learning intent-classification +3

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

no code implementations4 Feb 2023 Yi-An Lai, Elman Mansimov, Yuqing Xie, Yi Zhang

When upgrading neural models to a newer version, new errors that were not encountered in the legacy version can be introduced, known as regression errors.


Backward Compatibility During Data Updates by Weight Interpolation

no code implementations25 Jan 2023 Raphael Schumann, Elman Mansimov, Yi-An Lai, Nikolaos Pappas, Xibin Gao, Yi Zhang

This method interpolates between the weights of the old and new model and we show in extensive experiments that it reduces negative flips without sacrificing the improved accuracy of the new model.


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

no code implementations9 Sep 2021 Elman Mansimov, Yi Zhang

At the generation time, the model constructs the semantic parse tree by recursively inserting the predicted non-terminal labels at the predicted positions until termination.

named-entity-recognition Named Entity Recognition +2

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

no code implementations EMNLP (nlpbt) 2020 Elman Mansimov, Mitchell Stern, Mia Chen, Orhan Firat, Jakob Uszkoreit, Puneet Jain

In this paper, we offer a preliminary investigation into the task of in-image machine translation: transforming an image containing text in one language into an image containing the same text in another language.

Machine Translation Translation

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

1 code implementation29 May 2019 Elman Mansimov, Alex Wang, Sean Welleck, Kyunghyun Cho

We investigate this problem by proposing a generalized model of sequence generation that unifies decoding in directed and undirected models.

Machine Translation Natural Language Inference +3

Molecular geometry prediction using a deep generative graph neural network

1 code implementation31 Mar 2019 Elman Mansimov, Omar Mahmood, Seokho Kang, Kyunghyun Cho

Conventional conformation generation methods minimize hand-designed molecular force field energy functions that are often not well correlated with the true energy function of a molecule observed in nature.

Simple Nearest Neighbor Policy Method for Continuous Control Tasks

no code implementations ICLR 2018 Elman Mansimov, Kyunghyun Cho

As this policy does not require any optimization, it allows us to investigate the underlying difficulty of a task without being distracted by optimization difficulty of a learning algorithm.

Continuous Control

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

8 code implementations NeurIPS 2017 Yuhuai Wu, Elman Mansimov, Shun Liao, Roger Grosse, Jimmy Ba

In this work, we propose to apply trust region optimization to deep reinforcement learning using a recently proposed Kronecker-factored approximation to the curvature.

Atari Games Continuous Control +2

Generating Images from Captions with Attention

2 code implementations9 Nov 2015 Elman Mansimov, Emilio Parisotto, Jimmy Lei Ba, Ruslan Salakhutdinov

Motivated by the recent progress in generative models, we introduce a model that generates images from natural language descriptions.


Initialization Strategies of Spatio-Temporal Convolutional Neural Networks

no code implementations25 Mar 2015 Elman Mansimov, Nitish Srivastava, Ruslan Salakhutdinov

We propose a new way of incorporating temporal information present in videos into Spatial Convolutional Neural Networks (ConvNets) trained on images, that avoids training Spatio-Temporal ConvNets from scratch.

Unsupervised Learning of Video Representations using LSTMs

10 code implementations16 Feb 2015 Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov

We further evaluate the representations by finetuning them for a supervised learning problem - human action recognition on the UCF-101 and HMDB-51 datasets.

Action Recognition Temporal Action Localization

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