no code implementations • 17 Feb 2025 • Karthikeyan K, Michelle Yuan, Elman Mansimov, Katerina Margatina, Anurag Pratik, Daniele Bonadiman, Monica Sunkara, Yi Zhang, Yassine Benajiba
In this study, we investigate how search and model's self-feedback can be leveraged for reasoning tasks.
no code implementations • 10 Jan 2024 • Dennis Ulmer, Elman Mansimov, Kaixiang Lin, Justin Sun, Xibin Gao, Yi Zhang
This metric is used to filter the generated conversational data that is fed back in LLM for training.
1 code implementation • 24 May 2023 • Mujeen Sung, James Gung, Elman Mansimov, Nikolaos Pappas, Raphael Shu, Salvatore Romeo, Yi Zhang, Vittorio Castelli
Intent classification (IC) plays an important role in task-oriented dialogue systems.
no code implementations • 16 Feb 2023 • Shamik Roy, Raphael Shu, Nikolaos Pappas, Elman Mansimov, Yi Zhang, Saab Mansour, Dan Roth
Conventional text style transfer approaches focus on sentence-level style transfer without considering contextual information, and the style is described with attributes (e. g., formality).
no code implementations • 4 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.
no code implementations • 25 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.
no code implementations • 20 Dec 2022 • Raphael Shu, Elman Mansimov, Tamer Alkhouli, Nikolaos Pappas, Salvatore Romeo, Arshit Gupta, Saab Mansour, Yi Zhang, Dan Roth
The conversational model interacts with the environment by generating and executing programs triggering a set of pre-defined APIs.
1 code implementation • ACL 2022 • Aaron Mueller, Jason Krone, Salvatore Romeo, Saab Mansour, Elman Mansimov, Yi Zhang, Dan Roth
Label semantic aware systems have leveraged this information for improved text classification performance during fine-tuning and prediction.
no code implementations • 7 Feb 2022 • Deng Cai, Elman Mansimov, Yi-An Lai, Yixuan Su, Lei Shu, Yi Zhang
First, we measure and analyze model update regression in different model update settings.
2 code implementations • ACL 2022 • Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai, Yi Zhang
Pre-trained language models have been recently shown to benefit task-oriented dialogue (TOD) systems.
no code implementations • 9 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.
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.
no code implementations • CODI 2021 • Elman Mansimov, Gábor Melis, Lei Yu
Neural machine translation (NMT) has arguably achieved human level parity when trained and evaluated at the sentence-level.
1 code implementation • 29 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.
1 code implementation • 31 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.
2 code implementations • EMNLP 2018 • Jason Lee, Elman Mansimov, Kyunghyun Cho
We propose a conditional non-autoregressive neural sequence model based on iterative refinement.
Ranked #5 on
Machine Translation
on IWSLT2015 German-English
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.
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.
2 code implementations • 9 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.
no code implementations • 25 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.
11 code implementations • 16 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.