Kyunghyun Cho

Orcid: 0000-0003-1669-3211

Affiliations:
  • New York University, Courant Institute of Mathematical Sciences


According to our database1, Kyunghyun Cho authored at least 348 papers between 2010 and 2024.

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Bibliography

2024
: Visualization of AI-Assisted Task Guidance in AR.
IEEE Trans. Vis. Comput. Graph., January, 2024

Blind Biological Sequence Denoising with Self-Supervised Set Learning.
Trans. Mach. Learn. Res., 2024

Learning from Natural Language Feedback.
Trans. Mach. Learn. Res., 2024

Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs.
Trans. Mach. Learn. Res., 2024

LLMs are Highly-Constrained Biophysical Sequence Optimizers.
CoRR, 2024

Generalizing to any diverse distribution: uniformity, gentle finetuning and rebalancing.
CoRR, 2024

Using Deep Autoregressive Models as Causal Inference Engines.
CoRR, 2024

On the design space between molecular mechanics and machine learning force fields.
CoRR, 2024

Targeted Cause Discovery with Data-Driven Learning.
CoRR, 2024

Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning?
CoRR, 2024

Non-convolutional Graph Neural Networks.
CoRR, 2024

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design.
CoRR, 2024

𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs.
CoRR, 2024

Harmful Suicide Content Detection.
CoRR, 2024

MentalAgora: A Gateway to Advanced Personalized Care in Mental Health through Multi-Agent Debating and Attribute Control.
CoRR, 2024

Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms.
CoRR, 2024

Following Length Constraints in Instructions.
CoRR, 2024

Modified Risk Formulation for Improving the Prediction of Knee Osteoarthritis Progression.
CoRR, 2024

Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task.
CoRR, 2024

Preference Learning Algorithms Do Not Learn Preference Rankings.
CoRR, 2024

Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient.
CoRR, 2024

A Framework for Multi-modal Learning: Jointly Modeling Inter- & Intra-Modality Dependencies.
CoRR, 2024

A Brief Introduction to Causal Inference in Machine Learning.
CoRR, 2024

MR-Transformer: Vision Transformer for Total Knee Replacement Prediction Using Magnetic Resonance Imaging.
CoRR, 2024

Iterative Reasoning Preference Optimization.
CoRR, 2024

Generalization Measures for Zero-Shot Cross-Lingual Transfer.
CoRR, 2024

Hyperparameters in Continual Learning: a Reality Check.
CoRR, 2024

Self-Rewarding Language Models.
CoRR, 2024

Let's Go Shopping (LGS) - Web-Scale Image-Text Dataset for Visual Concept Understanding.
CoRR, 2024

First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Show Your Work with Confidence: Confidence Bands for Tuning Curves.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Self-Rewarding Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

BOtied: Multi-objective Bayesian optimization with tied multivariate ranks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Concept Bottleneck Generative Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Protein Discovery with Discrete Walk-Jump Sampling.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

System-Level Natural Language Feedback.
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

Leveraging Implicit Feedback from Deployment Data in Dialogue.
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

Holistic Patient Assessment System using Digital Twin for XR Medical Teleconsultation.
Proceedings of the Augmented Humans International Conference 2024, 2024

2023
Predicting Out-of-Domain Generalization with Neighborhood Invariance.
Trans. Mach. Learn. Res., 2023

Detecting incidental correlation in multimodal learning via latent variable modeling.
Trans. Mach. Learn. Res., 2023

Latent State Models of Training Dynamics.
Trans. Mach. Learn. Res., 2023

Health system-scale language models are all-purpose prediction engines.
Nat., 2023

Perspectives on the State and Future of Deep Learning - 2023.
CoRR, 2023

Peer Reviews of Peer Reviews: A Randomized Controlled Trial and Other Experiments.
CoRR, 2023

PaperCard for Reporting Machine Assistance in Academic Writing.
CoRR, 2023

AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models.
CoRR, 2023

Multiple Physics Pretraining for Physical Surrogate Models.
CoRR, 2023

xVal: A Continuous Number Encoding for Large Language Models.
CoRR, 2023

Active and Passive Causal Inference Learning.
CoRR, 2023

ARGUS: Visualization of AI-Assisted Task Guidance in AR.
CoRR, 2023

Training Language Models with Language Feedback at Scale.
CoRR, 2023

Improving Code Generation by Training with Natural Language Feedback.
CoRR, 2023

Unsupervised Learning of Initialization in Deep Neural Networks via Maximum Mean Discrepancy.
CoRR, 2023

AbDiffuser: full-atom generation of in-vitro functioning antibodies.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Protein Design with Guided Discrete Diffusion.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis.
Proceedings of the Medical Imaging with Deep Learning, 2023

Improving Joint Speech-Text Representations Without Alignment.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Towards Understanding and Improving GFlowNet Training.
Proceedings of the International Conference on Machine Learning, 2023

Linear Connectivity Reveals Generalization Strategies.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Non-monotonic Self-terminating Language Model.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Comparison of Semi-Supervised Learning Techniques for Streaming ASR at Scale.
Proceedings of the IEEE International Conference on Acoustics, 2023

Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling.
Proceedings of the Conference on Causal Learning and Reasoning, 2023

A Transformer-based Function Symbol Name Inference Model from an Assembly Language for Binary Reversing.
Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023

Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2023

Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2023

On the Blind Spots of Model-Based Evaluation Metrics for Text Generation.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
NetTIME: a multitask and base-pair resolution framework for improved transcription factor binding site prediction.
Bioinform., October, 2022

Can Current Task-oriented Dialogue Models Automate Real-world Scenarios in the Wild?
CoRR, 2022

Joint Embedding Predictive Architectures Focus on Slow Features.
CoRR, 2022

Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction.
CoRR, 2022

A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences.
CoRR, 2022

PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design.
CoRR, 2022

Predicting Out-of-Domain Generalization with Local Manifold Smoothness.
CoRR, 2022

Endowing Language Models with Multimodal Knowledge Graph Representations.
CoRR, 2022

Translating Hanja historical documents to understandable Korean and English.
CoRR, 2022

Multi-segment preserving sampling for deep manifold sampler.
CoRR, 2022

Learning from Natural Language Feedback.
CoRR, 2022

Separating the World and Ego Models for Self-Driving.
CoRR, 2022

Causal Scene BERT: Improving object detection by searching for challenging groups of data.
CoRR, 2022

Dual Learning for Large Vocabulary On-Device ASR.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Generative multitask learning mitigates target-causing confounding.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Towards Disentangled Speech Representations.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

Characterizing and addressing the issue of oversmoothing in neural autoregressive sequence modeling.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022

Characterizing and Overcoming the Greedy Nature of Learning in Multi-modal Deep Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022

Chemical-Reaction-Aware Molecule Representation Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Translating Hanja Historical Documents to Contemporary Korean and English.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Translation between Molecules and Natural Language.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

DEEP: DEnoising Entity Pre-training for Neural Machine Translation.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data.
PLoS Comput. Biol., 2021

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization.
Medical Image Anal., 2021

Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms.
J. Digit. Imaging, 2021

LINDA: Unsupervised Learning to Interpolate in Natural Language Processing.
CoRR, 2021

Amortized Noisy Channel Neural Machine Translation.
CoRR, 2021

Causal Effect Variational Autoencoder with Uniform Treatment.
CoRR, 2021

AlphaD3M: Machine Learning Pipeline Synthesis.
CoRR, 2021

Stereo Video Reconstruction Without Explicit Depth Maps for Endoscopic Surgery.
CoRR, 2021

An Empirical Study on Few-shot Knowledge Probing for Pretrained Language Models.
CoRR, 2021

Meta-repository of screening mammography classifiers.
CoRR, 2021

AAVAE: Augmentation-Augmented Variational Autoencoders.
CoRR, 2021

KLUE: Korean Language Understanding Evaluation.
CoRR, 2021

Future is not One-dimensional: Graph Modeling based Complex Event Schema Induction for Event Prediction.
CoRR, 2021

Online hyperparameter optimization by real-time recurrent learning.
CoRR, 2021

Self-Supervised Equivariant Scene Synthesis from Video.
CoRR, 2021

NetQuilt: deep multispecies network-based protein function prediction using homology-informed network similarity.
Bioinform., 2021

Monotonic Simultaneous Translation with Chunk-wise Reordering and Refinement.
Proceedings of the Sixth Conference on Machine Translation, 2021

NaturalProofs: Mathematical Theorem Proving in Natural Language.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

True Few-Shot Learning with Language Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


Rissanen Data Analysis: Examining Dataset Characteristics via Description Length.
Proceedings of the 38th International Conference on Machine Learning, 2021

Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule.
Proceedings of the 9th International Conference on Learning Representations, 2021

Causal BERT: Improving object detection by searching for challenging groups.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

AdapterFusion: Non-Destructive Task Composition for Transfer Learning.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Comparing Test Sets with Item Response Theory.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Mode recovery in neural autoregressive sequence modeling.
Proceedings of the 5th Workshop on Structured Prediction for NLP, 2021

MLE-Guided Parameter Search for Task Loss Minimization in Neural Sequence Modeling.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.
IEEE Trans. Medical Imaging, 2020

Navigation-based candidate expansion and pretrained language models for citation recommendation.
Scientometrics, 2020

Neural machine translation with a polysynthetic low resource language.
Mach. Transl., 2020

A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks.
J. Mach. Learn. Res., 2020

Classifier-agnostic saliency map extraction.
Comput. Vis. Image Underst., 2020

A Study on the Autoregressive and non-Autoregressive Multi-label Learning.
CoRR, 2020

Differences between human and machine perception in medical diagnosis.
CoRR, 2020

Learned Equivariant Rendering without Transformation Supervision.
CoRR, 2020

Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms.
CoRR, 2020

Evaluating representations by the complexity of learning low-loss predictors.
CoRR, 2020

A Framework For Contrastive Self-Supervised Learning And Designing A New Approach.
CoRR, 2020

VisualSem: a high-quality knowledge graph for vision and language.
CoRR, 2020

Rapidly Bootstrapping a Question Answering Dataset for COVID-19.
CoRR, 2020

Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned.
CoRR, 2020

Understanding the robustness of deep neural network classifiers for breast cancer screening.
CoRR, 2020

Compositionality and Capacity in Emergent Languages.
Proceedings of the 5th Workshop on Representation Learning for NLP, 2020

Improving the Ability of Deep Neural Networks to Use Information from Multiple Views in Breast Cancer Screening.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Semi-supervised learning for predicting total knee replacement with unsupervised data augmentation.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Attention-based CNN for KL Grade Classification: Data from the Osteoarthritis Initiative.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation.
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, 2020

Dynamics-Aware Embeddings.
Proceedings of the 8th International Conference on Learning Representations, 2020

Neural Text Generation With Unlikelihood Training.
Proceedings of the 8th International Conference on Learning Representations, 2020

Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models.
Proceedings of the 8th International Conference on Learning Representations, 2020

The Break-Even Point on Optimization Trajectories of Deep Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset.
Proceedings of the First Workshop on Scholarly Document Processing, 2020

Consistency of a Recurrent Language Model With Respect to Incomplete Decoding.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

AdapterHub: A Framework for Adapting Transformers.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2020

Unsupervised Question Decomposition for Question Answering.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Connecting the Dots: Event Graph Schema Induction with Path Language Modeling.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning Non-Monotonic Automatic Post-Editing of Translations from Human Orderings.
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 2020

Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Evaluating Pretrained Transformer Models for Citation Recommendation.
Proceedings of the 10th International Workshop on Bibliometric-enhanced Information Retrieval co-located with 42nd European Conference on Information Retrieval, 2020

Capacity, Bandwidth, and Compositionality in Emergent Language Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Asking and Answering Questions to Evaluate the Factual Consistency of Summaries.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

On the Discrepancy between Density Estimation and Sequence Generation.
Proceedings of the Fourth Workshop on Structured Prediction for NLP@EMNLP 2020, 2020

Log-Linear Reformulation of the Noisy Channel Model for Document-Level Neural Machine Translation.
Proceedings of the Fourth Workshop on Structured Prediction for NLP@EMNLP 2020, 2020

Neural Machine Translation with Byte-Level Subwords.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Learning to Learn Morphological Inflection for Resource-Poor Languages.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Insertion-based Decoding with Automatically Inferred Generation Order.
Trans. Assoc. Comput. Linguistics, 2019

Conditional Molecular Design with Deep Generative Models.
J. Chem. Inf. Model., 2019

Multi-Stage Document Ranking with BERT.
CoRR, 2019

Mix-review: Alleviate Forgetting in the Pretrain-Finetune Framework for Neural Language Generation Models.
CoRR, 2019

Generalized Inner Loop Meta-Learning.
CoRR, 2019

Inducing Constituency Trees through Neural Machine Translation.
CoRR, 2019

Improving localization-based approaches for breast cancer screening exam classification.
CoRR, 2019

Screening Mammogram Classification with Prior Exams.
CoRR, 2019

Multi-Turn Beam Search for Neural Dialogue Modeling.
CoRR, 2019

A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models.
CoRR, 2019

Using local plasticity rules to train recurrent neural networks.
CoRR, 2019

Automatic Machine Learning by Pipeline Synthesis using Model-Based Reinforcement Learning and a Grammar.
CoRR, 2019

Task-Driven Data Verification via Gradient Descent.
CoRR, 2019

Advancing GraphSAGE with A Data-Driven Node Sampling.
CoRR, 2019

Document Expansion by Query Prediction.
CoRR, 2019

Molecular geometry prediction using a deep generative graph neural network.
CoRR, 2019

Context-Aware Learning for Neural Machine Translation.
CoRR, 2019

Continual Learning via Neural Pruning.
CoRR, 2019

Augmentation for small object detection.
CoRR, 2019

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model.
CoRR, 2019

Passage Re-ranking with BERT.
CoRR, 2019

Sequential Graph Dependency Parser.
Proceedings of the International Conference on Recent Advances in Natural Language Processing, 2019

Can Unconditional Language Models Recover Arbitrary Sentences?
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Globally-Aware Multiple Instance Classifier for Breast Cancer Screening.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Deep Unsupervised Drum Transcription.
Proceedings of the 20th International Society for Music Information Retrieval Conference, 2019

Importance of Search and Evaluation Strategies in Neural Dialogue Modeling.
Proceedings of the 12th International Conference on Natural Language Generation, 2019

Non-Monotonic Sequential Text Generation.
Proceedings of the 36th International Conference on Machine Learning, 2019

DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder.
Proceedings of the 7th International Conference on Learning Representations, 2019

Finding Generalizable Evidence by Learning to Convince Q&A Models.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Countering Language Drift via Visual Grounding.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Emergent Linguistic Phenomena in Multi-Agent Communication Games.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Retrieval-Augmented Convolutional Neural Networks Against Adversarial Examples.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Dialogue Natural Language Inference.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Generating Diverse Translations with Sentence Codes.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Neural Unsupervised Parsing Beyond English.
Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP, 2019

2018
The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging.
IEEE Trans. Emerg. Top. Comput. Intell., 2018

Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia.
NeuroImage, 2018

Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes.
Neural Comput., 2018

Fine-grained attention mechanism for neural machine translation.
Neurocomputing, 2018

Importance of a Search Strategy in Neural Dialogue Modelling.
CoRR, 2018

Directional Analysis of Stochastic Gradient Descent via von Mises-Fisher Distributions in Deep learning.
CoRR, 2018

Backplay: "Man muss immer umkehren".
CoRR, 2018

Context-Attentive Embeddings for Improved Sentence Representations.
CoRR, 2018

Vehicle Community Strategies.
CoRR, 2018

Controlling Decoding for More Abstractive Summaries with Copy-Based Networks.
CoRR, 2018

Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples.
CoRR, 2018

New York University at TREC 2018 Complex Answer Retrieval Track.
Proceedings of the Twenty-Seventh Text REtrieval Conference, 2018

Loss Functions for Multiset Prediction.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Training a Ranking Function for Open-Domain Question Answering.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, 2018

Emergent Translation in Multi-Agent Communication.
Proceedings of the 6th International Conference on Learning Representations, 2018

Boundary Seeking GANs.
Proceedings of the 6th International Conference on Learning Representations, 2018

Emergent Communication in a Multi-Modal, Multi-Step Referential Game.
Proceedings of the 6th International Conference on Learning Representations, 2018

Stable and Effective Trainable Greedy Decoding for Sequence to Sequence Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Unsupervised Neural Machine Translation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Breast Density Classification with Deep Convolutional Neural Networks.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

A Comparison of Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging.
Proceedings of the 26th European Signal Processing Conference, 2018

Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Dynamic Meta-Embeddings for Improved Sentence Representations.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Multi-lingual Common Semantic Space Construction via Cluster-Consistent Word Embedding.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Grammar Induction with Neural Language Models: An Unusual Replication.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Conditional Word Embedding and Hypothesis Testing via Bayes-by-Backprop.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Meta-Learning for Low-Resource Neural Machine Translation.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

A Stable and Effective Learning Strategy for Trainable Greedy Decoding.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Jump to better conclusions: SCAN both left and right.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018

Letting a Neural Network Decide Which Machine Translation System to Use for Black-Box Fuzzy-Match Repair.
Proceedings of the 21st Annual Conference of the European Association for Machine Translation, 2018

The NYU System for the CoNLL-SIGMORPHON 2018 Shared Task on Universal Morphological Reinflection.
Proceedings of the CoNLL SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection, Brussels, October 31, 2018

Pommerman: A Multi-Agent Playground.
Proceedings of the Joint Proceedings of the AIIDE 2018 Workshops co-located with 14th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2018), 2018

Zero-Shot Transfer Learning for Event Extraction.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Code-Switched Named Entity Recognition with Embedding Attention.
Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching@ACL 2018, 2018

Search Engine Guided Neural Machine Translation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Fully Character-Level Neural Machine Translation without Explicit Segmentation.
Trans. Assoc. Comput. Linguistics, 2017

The representational geometry of word meanings acquired by neural machine translation models.
Mach. Transl., 2017

From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042).
Dagstuhl Reports, 2017

On integrating a language model into neural machine translation.
Comput. Speech Lang., 2017

Multi-way, multilingual neural machine translation.
Comput. Speech Lang., 2017

Introduction to the special issue on deep learning approaches for machine translation.
Comput. Speech Lang., 2017

Context-dependent word representation for neural machine translation.
Comput. Speech Lang., 2017

Graph Convolutional Networks for Classification with a Structured Label Space.
CoRR, 2017

Attention-based Mixture Density Recurrent Networks for History-based Recommendation.
CoRR, 2017

A Tutorial on Deep Learning for Music Information Retrieval.
CoRR, 2017

Does Neural Machine Translation Benefit from Larger Context?
CoRR, 2017

Zero-Shot Transfer Learning for Event Extraction.
CoRR, 2017

Boundary-Seeking Generative Adversarial Networks.
CoRR, 2017

Search Engine Guided Non-Parametric Neural Machine Translation.
CoRR, 2017

High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks.
CoRR, 2017

Emergent Language in a Multi-Modal, Multi-Step Referential Game.
CoRR, 2017

SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine.
CoRR, 2017

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks.
CoRR, 2017

On the Robustness of Deep Convolutional Neural Networks for Music Classification.
CoRR, 2017

Strawman: an Ensemble of Deep Bag-of-Ngrams for Sentiment Analysis.
CoRR, 2017

Saliency-based Sequential Image Attention with Multiset Prediction.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Transfer Learning for Music Classification and Regression Tasks.
Proceedings of the 18th International Society for Music Information Retrieval Conference, 2017

Convolutional recurrent neural networks for music classification.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Task-Oriented Query Reformulation with Reinforcement Learning.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Trainable Greedy Decoding for Neural Machine Translation.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Nematus: a Toolkit for Neural Machine Translation.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

Learning to Translate in Real-time with Neural Machine Translation.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

Neural Machine Translation for Cross-Lingual Pronoun Prediction.
Proceedings of the Third Workshop on Discourse in Machine Translation, 2017

Learning to Parse and Translate Improves Neural Machine Translation.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

Query-Efficient Imitation Learning for End-to-End Simulated Driving.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Learning to Understand Phrases by Embedding the Dictionary.
Trans. Assoc. Comput. Linguistics, 2016

Query-Efficient Imitation Learning for End-to-End Autonomous Driving.
CoRR, 2016

Efficient Character-level Document Classification by Combining Convolution and Recurrent Layers.
CoRR, 2016

WebNav: A New Large-Scale Task for Natural Language based Sequential Decision Making.
CoRR, 2016

Semantic Noise Modeling for Better Representation Learning.
CoRR, 2016

Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes.
CoRR, 2016

Can neural machine translation do simultaneous translation?
CoRR, 2016

Noisy Parallel Approximate Decoding for Conditional Recurrent Language Model.
CoRR, 2016

Recurrent Neural Networks for Multivariate Time Series with Missing Values.
CoRR, 2016

First Result on Arabic Neural Machine Translation.
CoRR, 2016

Theano: A Python framework for fast computation of mathematical expressions.
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CoRR, 2016

NYU-MILA Neural Machine Translation Systems for WMT'16.
Proceedings of the First Conference on Machine Translation, 2016

Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach.
Proceedings of the 2016 IEEE Southwest Symposium on Image Analysis and Interpretation, 2016

A Two-stage Approach for Extending Event Detection to New Types via Neural Networks.
Proceedings of the 1st Workshop on Representation Learning for NLP, 2016

End-to-End Goal-Driven Web Navigation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Iterative Refinement of the Approximate Posterior for Directed Belief Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Joint Event Extraction via Recurrent Neural Networks.
Proceedings of the NAACL HLT 2016, 2016

Learning Distributed Representations of Sentences from Unlabelled Data.
Proceedings of the NAACL HLT 2016, 2016

Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism.
Proceedings of the NAACL HLT 2016, 2016

Gated Word-Character Recurrent Language Model.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Zero-Resource Translation with Multi-Lingual Neural Machine Translation.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation.
Proceedings of the COLING 2016, 2016

Oracle Performance for Visual Captioning.
Proceedings of the British Machine Vision Conference 2016, 2016

Larger-Context Language Modelling with Recurrent Neural Network.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

A Character-level Decoder without Explicit Segmentation for Neural Machine Translation.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015
Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks.
IEEE Trans. Multim., 2015

Two-layer contractive encodings for learning stable nonlinear features.
Neural Networks, 2015

Measuring the usefulness of hidden units in Boltzmann machines with mutual information.
Neural Networks, 2015

Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism.
CoRR, 2015

Trainable performance upper bounds for image and video captioning.
CoRR, 2015

Larger-Context Language Modelling.
CoRR, 2015

ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks.
CoRR, 2015

ReSeg: A Recurrent Neural Network for Object Segmentation.
CoRR, 2015

A Controller Recognizer Framework: How necessary is recognition for control?
CoRR, 2015

Iterative Refinement of Approximate Posterior for Training Directed Belief Networks.
CoRR, 2015

Embedding Word Similarity with Neural Machine Translation.
Proceedings of the 3rd International Conference on Learning Representations, 2015

On Using Monolingual Corpora in Neural Machine Translation.
CoRR, 2015

First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks.
CoRR, 2015

Natural Language Understanding with Distributed Representation.
CoRR, 2015

Neural Machine Translation by Jointly Learning to Align and Translate.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Montreal Neural Machine Translation Systems for WMT'15.
Proceedings of the Tenth Workshop on Statistical Machine Translation, 2015

Learning Distributed Representations from Reviews for Collaborative Filtering.
Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Attention-Based Models for Speech Recognition.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A study of the recurrent neural network encoder-decoder for large vocabulary speech recognition.
Proceedings of the 16th Annual Conference of the International Speech Communication Association, 2015

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Gated Feedback Recurrent Neural Networks.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Describing Videos by Exploiting Temporal Structure.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

On Using Very Large Target Vocabulary for Neural Machine Translation.
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015

2014
Foundations and Advances in Deep Learning.
PhD thesis, 2014

How to Construct Deep Recurrent Neural Networks.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Not All Neural Embeddings are Born Equal.
CoRR, 2014

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.
CoRR, 2014

End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results.
CoRR, 2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.
CoRR, 2014

Exponentially Increasing the Capacity-to-Computation Ratio for Conditional Computation in Deep Learning.
CoRR, 2014

Classifying and Visualizing Motion Capture Sequences using Deep Neural Networks.
Proceedings of the VISAPP 2014, 2014

Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation.
Proceedings of SSST@EMNLP 2014, 2014

On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.
Proceedings of SSST@EMNLP 2014, 2014

On the Equivalence between Deep NADE and Generative Stochastic Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Iterative Neural Autoregressive Distribution Estimator NADE-k.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On the Number of Linear Regions of Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2013
Enhanced Gradient for Training Restricted Boltzmann Machines.
Neural Comput., 2013

Boltzmann Machines and Denoising Autoencoders for Image Denoising
Proceedings of the 1st International Conference on Learning Representations, 2013

Learned-norm pooling for deep neural networks.
CoRR, 2013

Gaussian-Bernoulli deep Boltzmann machine.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Two-Layer Contractive Encodings with Shortcuts for Semi-supervised Learning.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

Understanding Dropout: Training Multi-Layer Perceptrons with Auxiliary Independent Stochastic Neurons.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images.
Proceedings of the 30th International Conference on Machine Learning, 2013

Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation.
Proceedings of the IEEE International Conference on Acoustics, 2013

A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

Boltzmann Machines for Image Denoising.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

2012
An iterative algorithm for singular value decomposition on noisy incomplete matrices.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Tikhonov-Type Regularization for Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011
Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines.
Proceedings of the 28th International Conference on Machine Learning, 2011

Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010
Parallel tempering is efficient for learning restricted Boltzmann machines.
Proceedings of the International Joint Conference on Neural Networks, 2010


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