Neural Machine Translation by Jointly Learning to Align and Translate

2014/09/01 by Dzmitry Bahdanau, Kyunghyun Cho, Bahdanau, Dzmitry +3 · 9 voices · 14,622 citations
Computer Science · Mathematics · #Artificial intelligence #Artificial neural network #Bottleneck #Computer science #Encoder #Example-based machine translation #Machine translation #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Natural language processing #Phrase #Sentence #Speech recognition #Topic Modeling #Transfer-based machine translation #Translation (biology) #Word (group theory) #cs.CL #cs.LG #cs.NE #stat.ML

paper · pdf · doi:10.48550/arxiv.1409.0473

published in arXiv (Cornell University) (Cornell University) · Accepted at ICLR 2015 as oral presentation

openalex publication_date 2014/09/01 · arxiv created 2016/05/19 · arxiv updated 2016/05/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance. The models proposed recently for neural machine translation often belong to a family of encoder-decoders and consists of an encoder that encodes a source sentence into a fixed-length vector from which a decoder generates a translation. In this paper, we conjecture that the use of a fixed-length vector is a bottleneck in improving the performance of this basic encoder-decoder architecture, and propose to extend this by allowing a model to automatically (soft-)search for parts of a source sentence that are relevant to predicting a target word, without having to form these parts as a hard segment explicitly. With this new approach, we achieve a translation performance comparable to the existing state-of-the-art phrase-based system on the task of English-to-French translation. Furthermore, qualitative analysis reveals that the (soft-)alignments found by the model agree well with our intuition.

Citations

• ADADELTA: An Adaptive Learning Rate Method
• Bidirectional recurrent neural networks
• On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

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• From Time-series Generation, Model Selection to Transfer Learning: A Comparative Review of Pixel-wise Approaches for Large-scale Crop Mapping
• Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME
• Emerging Properties in Self-Supervised Vision Transformers
• On the Definition of Japanese Word
• Incremental Adaptation of NMT for Professional Post-editors: A User Study
• Deep Learning: Our Miraculous Year 1990-1991
• Seq2seq Translation Model for Sequential Recommendation
• OSU Multimodal Machine Translation System Report
• Translating Natural Language to SQL using Pointer-Generator Networks and How Decoding Order Matters
• Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions
• Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency
• Paraphrase Generation as Unsupervised Machine Translation
• Domain-Adaptive Small Language Models for Structured Tax Code Prediction
• Time-series forecasting for nonlinear high-dimensional system using hybrid method combining autoencoder and multi-parallelized quantum long short-term memory and gated recurrent unit
• TSRec: Enhancing Repeat-Aware Recommendation from a Temporal-Sequential Perspective
• Understood in Translation, Transformers for Domain Understanding
• Multimodal Dialogue State Tracking By QA Approach with Data Augmentation
• Multi-Head Attention: Collaborate Instead of Concatenate
• Visual Question Answering with Memory-Augmented Networks
• Semantic-Unit-Based Dilated Convolution for Multi-Label Text Classification
• CycleGAN-Driven Transfer Learning for Electronics Response Emulation in High-Purity Germanium Detectors
• Queue up for takeoff: a transferable deep learning framework for flight delay prediction
• TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration
• Towards Extracting Software Requirements from App Reviews using Seq2seq Framework
• Emergent Natural Language with Communication Games for Improving Image Captioning Capabilities without Additional Data
• Universal Approximation Theorem for a Single-Layer Transformer
• Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule
• Quantifying Mix Network Privacy Erosion with Generative Models
• Probabilistic Transformers
• SAS: Simulated Attention Score
• Cross-Lingual Transfer for Machine Translation in Turkic Languages
• A multi-task encoder-dual-decoder framework for mixed frequency data prediction
• KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks
• PhoniTale: Phonologically Grounded Mnemonic Generation for Typologically Distant Language Pairs
• A Survey of Pun Generation: Datasets, Evaluations and Methodologies
• PRISM: Pointcloud Reintegrated Inference via Segmentation and Cross-attention for Manipulation
• Multi-node Bert-pretraining: Cost-efficient Approach
• ViTaL: A Multimodality Dataset and Benchmark for Multi-pathological Ovarian Tumor Recognition
• Relational inductive biases on attention mechanisms
• Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
• RECA-PD: A Robust Explainable Cross-Attention Method for Speech-based Parkinson's Disease Classification
• Automatically Generating Commit Messages from Diffs using Neural Machine Translation
• Memory Mosaics at scale
• Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
• Can Artificial Intelligence solve the blockchain oracle problem? Unpacking the Challenges and Possibilities
• Multi-hop Inference for Question-driven Summarization
• Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences
• A Sketch-Based Neural Model for Generating Commit Messages from Diffs
• A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
• Memory-augmented Dense Predictive Coding for Video Representation Learning
• A Review on Sound Source Localization in Robotics: Focusing on Deep Learning Methods
• Examining Reject Relations in Stimulus Equivalence Simulations
• Learning quantum phase transition in parametrized quantum circuits with an attention mechanism
• Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models
• Multilingual Hate Speech Detection in Social Media Using Translation-Based Approaches with Large Language Models
• Minimizing the Bag-of-Ngrams Difference for Non-Autoregressive Neural Machine Translation
• Relevance-Promoting Language Model for Short-Text Conversation
• Hierarchical Lexical Graph for Enhanced Multi-Hop Retrieval
• Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
• Concept Pinpoint Eraser for Text-to-image Diffusion Models via Residual Attention Gate
• Improved and Robust Controversy Detection in General Web Pages Using Semantic Approaches under Large Scale Conditions
• Object Based Attention Through Internal Gating
• SU-RUG at the CoNLL-SIGMORPHON 2017 shared task: Morphological Inflection with Attentional Sequence-to-Sequence Models
• Offensive Language Detection on Social Media Using XLNet
• GoIRL: Graph-Oriented Inverse Reinforcement Learning for Multimodal Trajectory Prediction
• Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things
• Variational Digital Twins
• Program Language Translation Using a Grammar-Driven Tree-to-Tree Model
• Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models
• daVinciNet: Joint Prediction of Motion and Surgical State in Robot-Assisted Surgery
• DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing
• Enhanced Hybrid Transducer and Attention Encoder Decoder with Text Data
• FPETS : Fully Parallel End-to-End Text-to-Speech System
• An Interpretable Transformer-Based Foundation Model for Cross-Procedural Skill Assessment Using Raw fNIRS Signals
• Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data
• A Survey of State Representation Learning for Deep Reinforcement Learning
• VeriLocc: End-to-End Cross-Architecture Register Allocation via LLM
• Sequence-to-Sequence Models with Attention Mechanistically Map to the Architecture of Human Memory Search
• Reinforced Mnemonic Reader for Machine Reading Comprehension
• Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation
• Aligning where to see and what to tell: image caption with region-based attention and scene factorization
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• Better Language Model Inversion by Compactly Representing Next-Token Distributions
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• Passing the Turing Test in Political Discourse: Fine-Tuning LLMs to Mimic Polarized Social Media Comments
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• Investigation of learning abilities on linguistic features in sequence-to-sequence text-to-speech synthesis
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• Detecting Hard-Coded Credentials in Software Repositories via LLMs
• Churn Intent Detection in Multilingual Chatbot Conversations and Social Media
• End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification
• The Helsinki Neural Machine Translation System
• Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers
• Automated proof synthesis for propositional logic with deep neural networks
• Bridging the Digital Divide: Small Language Models as a Pathway for Physics and Photonics Education in Underdeveloped Regions
• Manager: Aggregating Insights from Unimodal Experts in Two-Tower VLMs and MLLMs
• FAD-Net: Frequency-Domain Attention-Guided Diffusion Network for Coronary Artery Segmentation using Invasive Coronary Angiography
• Retrieval-Augmented Code Review Comment Generation
• Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
• Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification
• Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Method
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• Controllable Coupled Image Generation via Diffusion Models
• How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics
• From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies
• Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings
• Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks
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• Power Law Guided Dynamic Sifting for Efficient Attention
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• Domain Control for Neural Machine Translation
• ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT
• Regression as Classification: Influence of Task Formulation on Neural Network Features
• Voice Imitating Text-to-Speech Neural Networks
• A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification
• Discriminative Neural Clustering for Speaker Diarisation
• Jointly Trained Sequential Labeling and Classification by Sparse Attention Neural Networks
• On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
• LCSTS: A Large Scale Chinese Short Text Summarization Dataset
• Adversarially Robust Neural Architectures
• On the Dimensionality of Word Embedding
• Backpropagation through time and the brain
• A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generation
• Sequential Context Encoding for Duplicate Removal
• To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference
• Sequence-to-Set Semantic Tagging: End-to-End Multi-label Prediction using Neural Attention for Complex Query Reformulation and Automated Text Categorization
• Adversarial Ranking for Language Generation
• Reconstruction Network for Video Captioning
• ReDecode Framework for Iterative Improvement in Paraphrase Generation
• Attention-Aware Compositional Network for Person Re-identification
• Sounding that Object: Interactive Object-Aware Image to Audio Generation
• Shift-Reduce Constituent Parsing with Neural Lookahead Features
• CodeSum: Translate Program Language to Natural Language
• SynLang and Symbiotic Epistemology: A Manifesto for Conscious Human-AI Collaboration
• End-to-end Silent Speech Recognition with Acoustic Sensing
• Learning to Optimize in Swarms
• Natural, Artificial, and Human Intelligences
• MVAN: Multi-View Attention Networks for Fake News Detection on Social Media
• Conditional Variational Autoencoder for Neural Machine Translation
• Visual Concept Reasoning Networks
• SynPO: Synergizing Descriptiveness and Preference Optimization for Video Detailed Captioning
• Visual Agreement Regularized Training for Multi-Modal Machine Translation
• A Deep Learning Approach to Automate High-Resolution Blood Vessel Reconstruction on Computerized Tomography Images With or Without the Use of Contrast Agent
• Channel-Imposed Fusion: A Simple yet Effective Method for Medical Time Series Classification
• Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
• Subjective Bias in Abstractive Summarization
• Improving Language and Modality Transfer in Translation by Character-level Modeling
• Two failure modes of deep transformers and how to avoid them: a unified theory of signal propagation at initialisation
• Generation of Synthetic Electronic Medical Record Text
• Machine Translation Approaches and Survey for Indian Languages
• Evaluating Syntactic Properties of Seq2seq Output with a Broad Coverage HPSG: A Case Study on Machine Translation
• Explainable Depression Detection using Masked Hard Instance Mining
• Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
• A crossover code for high-dimensional composition
• Learning to Encode Evolutionary Knowledge for Automatic Commenting Long Novels
• Using holistic event information in the trigger
• Real-time low-resource phoneme recognition on edge devices
• Untangling tradeoffs between recurrence and self-attention in neural networks
• Towards one-shot learning for rare-word translation with external experts
• Structured-based Curriculum Learning for End-to-end English-Japanese Speech Translation
• Two-Stage Feature Generation with Transformer and Reinforcement Learning
• Towards Robust Assessment of Pathological Voices via Combined Low-Level Descriptors and Foundation Model Representations
• Identifying Super Spreaders in Multilayer Networks
• A Physics-Augmented GraphGPS Framework for the Reconstruction of 3D Riemann Problems from Sparse Data
• S-OHEM: Stratified Online Hard Example Mining for Object Detection
• Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretable
• VoiceStar: Robust Zero-Shot Autoregressive TTS with Duration Control and Extrapolation
• Joint Training for Neural Machine Translation Models with Monolingual Data
• Towards Proof Synthesis Guided by Neural Machine Translation for Intuitionistic Propositional Logic
• The pointer network for reward maximisation in multi-target space mission sequence selection
• Design Challenges in Named Entity Transliteration
• Dual Ask-Answer Network for Machine Reading Comprehension
• CSVideoNet: A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive Sensing
• Detecting Interrogative Utterances with Recurrent Neural Networks
• Multimodal Memory Modelling for Video Captioning
• Classification of assembly tasks combining multiple primitive actions using Transformers and xLSTMs
• LMask: Learn to Solve Constrained Routing Problems with Lazy Masking
• Selection Mechanisms for Sequence Modeling using Linear State Space Models
• Low-Resource NMT: A Case Study on the Written and Spoken Languages in Hong Kong
• DeepTransport: Learning Spatial-Temporal Dependency for Traffic Condition Forecasting
• A Multi-Head Attention Soft Random Forest for Interpretable Patient No-Show Prediction
• Attention with Trained Embeddings Provably Selects Important Tokens
• Self-attention based end-to-end Hindi-English Neural Machine Translation
• Physical models realizing the transformer architecture of large language models
• A Framework for Non-Linear Attention via Modern Hopfield Networks
• SUS backprop: linear backpropagation algorithm for long inputs in transformers
• Cross-Modal Alignment with Mixture Experts Neural Network for Intral-City Retail Recommendation
• Secrets Everywhere: Auditing Memorization in Mobility Prediction Models
• Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity
• Grounded Recurrent Neural Networks
• Abstract Syntax Networks for Code Generation and Semantic Parsing
• Regularizing Output Distribution of Abstractive Chinese Social Media Text Summarization for Improved Semantic Consistency
• Challenges and Thrills of Legal Arguments
• Continuous Space Reordering Models for Phrase-based MT
• TransBench: Benchmarking Machine Translation for Industrial-Scale Applications
• Probabilistic Attention for Interactive Segmentation
• Augmenting human innovation teams with artificial intelligence: Exploring transformer‐based language models
• Going deep into schizophrenia with artificial intelligence
• Attention-based clustering
• Lightweight and Interpretable Transformer via Mixed Graph Algorithm Unrolling for Traffic Forecast
• Meta-Learning a Dynamical Language Model
• Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation
• Improving Next-Application Prediction with Deep Personalized-Attention Neural Network
• SchoenbAt: Rethinking Attention with Polynomial basis
• Learning to Dissipate Energy in Oscillatory State-Space Models
• Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions
• A Survey on Large Language Models in Multimodal Recommender Systems
• Schedule repair for flexible job shops under machine breakdowns by deep reinforcement learning
• Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency
• Recursive Recurrent Nets with Attention Modeling for OCR in the Wild
• Unsupervised Neural Text Simplification
• Multi-Component Graph Convolutional Collaborative Filtering
• Putting It All into Context: Simplifying Agents with LCLMs
• EmotionX-DLC: Self-Attentive BiLSTM for Detecting Sequential Emotions in Dialogue
• Overflow Prevention Enhances Long-Context Recurrent LLMs
• What value do explicit high level concepts have in vision to language problems?
• Learning Penalty for Optimal Partitioning via Automatic Feature Extraction
• Security through the Eyes of AI: How Visualization is Shaping Malware Detection
• Joint Intent Detection And Slot Filling Based on Continual Learning Model
• Attention-based Mixture Density Recurrent Networks for History-based Recommendation
• Attention-Enhanced Reservoir Computing as a Multiple Dynamical System Approximator
• Graph Constrained Reinforcement Learning for Natural Language Action Spaces
• FNED
• Generative Models for Long Time Series: Approximately Equivariant Recurrent Network Structures for an Adjusted Training Scheme
• Geometric Analysis of Token Selection in Multi-Head Attention
• Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition
• A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem
• A Comprehensive Analysis of Adversarial Attacks against Spam Filters
• Multimodal Machine Learning: A Survey and Taxonomy
• k-Nearest Neighbor Augmented Neural Networks for Text Classification
• QiMeng-Xpiler: Transcompiling Tensor Programs for Deep Learning Systems with a Neural-Symbolic Approach
• Concept Tagging for Natural Language Understanding: Two Decadelong Algorithm Development
• SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection
• Syntactic Scaffolds for Semantic Structures
• GeloVec: Higher Dimensional Geometric Smoothing for Coherent Visual Feature Extraction in Image Segmentation
• Applications of deep learning in stock market prediction: recent progress
• Harnessing Structured Knowledge: A Concept Map-Based Approach for High-Quality Multiple Choice Question Generation with Effective Distractors
• Detecting the Root Cause Code Lines in Bug-Fixing Commits by Heterogeneous Graph Learning
• Dynamic Forecasting and Temporal Feature Evolution of Stock Repurchases in Listed Companies Using Attention-Based Deep Temporal Networks
• SA-GAT-SR: Self-Adaptable Graph Attention Networks with Symbolic Regression for high-fidelity material property prediction
• The LAMBADA dataset: Word prediction requiring a broad discourse context
• Relative Positional Encoding for Transformers with Linear Complexity
• Personalizing Search Results Using Hierarchical RNN with Query-aware Attention
• Dual-Primal Graph Convolutional Networks
• Show and tell: A neural image caption generator
• Adversarial Examples in the Physical World
• Automatic Acrostic Couplet Generation with Three-Stage Neural Network Pipelines
• The Neuroscience of Transformers
• In-context learning emerges in chemical reaction networks without attention
• Machine Translation: A Literature Review
• Exploiting Linguistic Resources for Neural Machine Translation Using Multi-task Learning
• QCRI Machine Translation Systems for IWSLT 16
• A Multi-Object Rectified Attention Network for Scene Text Recognition
• Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition
• A contextual hierarchical attention network for detecting mental health disorders using social media
• On Subquadratic Architectures: From Applications to Principles
• A Reinforced Generation of Adversarial Examples for Neural Machine Translation
• Modeling of Rakugo Speech and Its Limitations: Toward Speech Synthesis That Entertains Audiences
• Mutual Information Scaling and Expressive Power of Sequence Models
• Image to Video Domain Adaptation Using Web Supervision
• Evaluating Sequence-to-Sequence Learning Models for If-Then Program Synthesis
• Signed Dual Attention: Capturing Signed Dependencies in Time Series Forecasting
• When Deep Learning Meets Information Retrieval-based Bug Localization: A Survey
• Learning better discourse representation for implicit discourse relation recognition via attention networks
• Strategies for Training Large Vocabulary Neural Language Models
• Fast Transformer Inference on ARM-Based HMPSoCs
• Translators as Invisible Teachers of AI: Copyright, Translation Memory, and the Political Economy of Linguistic Data
• Polish - English Speech Statistical Machine Translation Systems for the\n IWSLT 2014
• Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spaces
• Hierarchical Multi-Label Generation with Probabilistic Level-Constraint
• A comparative study of deep learning and ensemble learning to extend the horizon of traffic forecasting
• Jekyll-and-Hyde Tipping Point in an AI's Behavior
• Softpick: No Attention Sink, No Massive Activations with Rectified Softmax
• Characterizing the Expressivity of Local Attention in Transformers
• Leveraging Depth Maps and Attention Mechanisms for Enhanced Image Inpainting
• Enhancing event reconstruction for γ-ray particle detector arrays using transformers
• The State-Prediction Separation Hypothesis
• Position-aware deep multi-task learning for drug–drug interaction extraction
• Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving
• Nested Learning: The Illusion of Deep Learning Architectures
• Enhanced Partially Relevant Video Retrieval through Inter- and Intra-Sample Analysis with Coherence Prediction
• Hierarchical Reinforcement Learning in Multi-Goal Spatial Navigation with Autonomous Mobile Robots
• Spatial Speech Translation: Translating Across Space With Binaural Hearables
• Myocardial Infarction Severity Stages Classification From ECG Signals Using Attentional Recurrent Neural Network
• Escaping the BLEU Trap: A Signal-Grounded Framework with Decoupled Semantic Guidance for EEG-to-Text Decoding
• Deep Learning
• A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction
• Low-Resource Neural Machine Translation Using Recurrent Neural Networks and Transfer Learning: A Case Study on English-to-Igbo
• You Need Better Attention Priors
• Simplify-then-Translate: Automatic Preprocessing for Black-Box Machine Translation
• Cross-Level Cross-Scale Cross-Attention Network for Point Cloud Representation
• Instance-aware Image and Sentence Matching with Selective Multimodal LSTM
• Semi-Supervised Confidence Network aided Gated Attention based Recurrent Neural Network for Clickbait Detection
• The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs
• Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification
• Deep Choice Model Using Pointer Networks for Airline Itinerary Prediction
• A General Survey on Attention Mechanisms in Deep Learning
• Representation Learning for Natural Language Processing
• Inf-VAE
• Deep Multi-View Learning for Tire Recommendation
• Attention-based Clinical Note Summarization
• End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results
• Wavelet-Enhanced Sequence-to-Sequence Modeling with Attention Mechanism for Short-Term Wind Power Forecasting
• A Spatial-Temporal Graph Neural Network Framework for Automated Software Bug Triaging
• Semantic Graphs for Generating Deep Questions
• Capturing AI's Attention: Physics of Repetition, Hallucination, Bias and Beyond
• A Novel Hybrid Approach Using an Attention-Based Transformer + GRU Model for Predicting Cryptocurrency Prices
• Multivariate LSTM-FCNs for time series classification
• A Hybrid Convolutional Variational Autoencoder for Text Generation
• Set-to-Sequence Methods in Machine Learning: A Review
• Neural Rating Regression with Abstractive Tips Generation for Recommendation
• Attention-Based Multimodal Fusion for Video Description
• SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning
• NUIG-Shubhanker@Dravidian-CodeMix-FIRE2020: Sentiment Analysis of Code-Mixed Dravidian text using XLNet
• GADS: A Super Lightweight Model for Head Pose Estimation
• Teaching Machines to Code: Neural Markup Generation with Visual Attention
• A survey of state-of-the-art approaches for emotion recognition in text
• Multi-Level Attention Pooling for Graph Neural Networks: Unifying Graph Representations with Multiple Localities
• What do Neural Machine Translation Models Learn about Morphology?
• Quantitative Clustering in Mean-Field Transformer Models
• Self-Explaining Structures Improve NLP Models
• Learning to Attribute with Attention
• Multimodal time-aware attention networks for depression detection
• Automatic Commit Message Generation: A Critical Review and Directions for Future Work
• Generating captions without looking beyond objects
• Prior Knowledge Driven Label Embedding for Slot Filling in Natural Language Understanding
• Insights on Neural Representations for End-to-End Speech Recognition
• From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs
• Question Answering over Knowledge Base using Language Model Embeddings
• Artificial intelligence and deep learning algorithms for epigenetic sequence analysis: A review for epigeneticists and AI experts
• Identifying Harm Events in Clinical Care through Medical Narratives
• Sequence-to-sequence models for workload interference prediction on batch processing datacenters
• Local minima in training of neural networks
• Experiment Segmentation in Scientific Discourse as Clause-level Structured Prediction using Recurrent Neural Networks
• Tag-less back-translation
• End-to-End ASR-Free Keyword Search From Speech
• Spatial-temporal Conv-sequence Learning with Accident Encoding for Traffic Flow Prediction
• Environmental sound classification using convolution neural networks with different integrated loss functions
• Structure-Tags Improve Text Classification for Scholarly Document Quality Prediction
• Denoising Multi-Source Weak Supervision for Neural Text Classification
• Sparks of Science: Hypothesis Generation Using Structured Paper Data
• Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations
• Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks
• Multilingual Contextualization of Large Language Models for Document-Level Machine Translation
• Clarifying Ambiguities: on the Role of Ambiguity Types in Prompting Methods for Clarification Generation
• SemDiff: Generating Natural Unrestricted Adversarial Examples via Semantic Attributes Optimization in Diffusion Models
• Predicting Wave Dynamics using Deep Learning with Multistep Integration Inspired Attention and Physics-Based Loss Decomposition
• Action-Attending Graphic Neural Network
• Pay Attention to What and Where? Interpretable Feature Extractor in Vision-based Deep Reinforcement Learning
• Siamese Network with Dual Attention for EEG-Driven Social Learning: Bridging the Human-Robot Gap in Long-Tail Autonomous Driving
• Ordinary Least Squares as an Attention Mechanism
• Modeling Time Series Similarity with Siamese Recurrent Networks
• Large Language Models and Attention-Based AI for Hardware Design and Security: Progress, Challenges, and Opportunities
• SRVP: Strong Recollection Video Prediction Model Using Attention-Based Spatiotemporal Correlation Fusion
• PROPEL: Supervised and Reinforcement Learning for Large-Scale Supply Chain Planning
• Predicting Temporal Sets with Deep Neural Networks
• Show and Tell: Lessons Learned from the 2015 MSCOCO Image Captioning Challenge
• MHSA-Net: Multihead Self-Attention Network for Occluded Person Re-Identification
• Hogwild! Inference: Parallel LLM Generation via Concurrent Attention
• Separator Injection Attack: Uncovering Dialogue Biases in Large Language Models Caused by Role Separators

Discussions

• Me rationalising what I am currently doing: There is no shame in designing a recipish, clunky, deep architecture kept together with duct tape. This is how we move into new territories. The Transformer [bsky, 26 points, 1 comments]
• interesting connection, but the transformer paper didn’t invent attention? arxiv.org/abs/1409.0473 [bsky, 23 points, 1 comments]
• For those of you who don't know (or don't remember), the original paper introducing "attention" was Bahdanau, Cho, & Bengio's "Neural machine translation by jointly learning to align and translate" (2 [bsky, 8 points, 1 comments]
• Neural Machine Translation by Jointly Learning to Align and Translate [hn, 2 points, 0 comments]
• וזה המאמר שתאר לראשונה-Attention עבור רשתות ניורונים: arxiv.org/abs/1409.0473 אבל בתכלס עדיף לקרוא דברים מאוחרים יותר. [bsky, 2 points, 0 comments]
• CDS Prof. @kyunghyuncho.bsky.social's 2014 "attention" paper was recently the Runner-Up for the ICLR 2025 Test of Time Award. The paper introduced dynamic attention in machine translation, laying the [bsky, 2 points, 0 comments]
• We've come full circle [lemmy, 1 points, 0 comments]
• Neural Machine Translation by Jointly Learning to Align and Translate (2015) [hn, 1 points, 0 comments]
• what a nice paper this is arxiv.org/pdf/1409.0473 [bsky, 1 points, 0 comments]

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