{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/machine-translation/papers/55","list_of":"/task/machine-translation","task":"Machine Translation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":55,"pages_in_order":108,"rows_per_page":100,"rows":[5401,5500],"of":10752,"counts":{"archive_papers_tagged":10752,"with_a_code_link":2444,"where_syntology_ran_a_sample":477,"not_listed_spam_title":0,"listed":10752,"listed_where_code_ran":477,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":381,"every_run_a_failure_of_syntologys_instrument":96,"listed_with_a_run_with_no_instrument_failure":381,"listed_every_run_a_failure_of_syntologys_instrument":96,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/machine-translation","prev":"/task/machine-translation/papers/54","next":"/task/machine-translation/papers/56","papers":[{"url":null,"slug":"assessing-the-bilingual-knowledge-learned-by","title":"Assessing the Bilingual Knowledge Learned by Neural Machine Translation Models","date":"2020-04-28","arxiv_id":"2004.13270","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-attention-with-cross-lingual-position","title":"Self-Attention with Cross-Lingual Position Representation","date":"2020-04-28","arxiv_id":"2004.13310","repositories_listed":0,"syntology":null},{"url":null,"slug":"bleu-neighbors-a-reference-less-approach-to","title":"BLEU Neighbors: A Reference-less Approach to Automatic Evaluation","date":"2020-04-27","arxiv_id":"2004.12726","repositories_listed":0,"syntology":null},{"url":null,"slug":"jointly-trained-transformers-models-for","title":"Jointly Trained Transformers models for Spoken Language Translation","date":"2020-04-25","arxiv_id":"2004.12111","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiple-segmentations-of-thai-sentences-for","title":"Multiple Segmentations of Thai Sentences for Neural Machine Translation","date":"2020-04-23","arxiv_id":"2004.11472","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-of-non-autoregressive-model-for","title":"A Study of Non-autoregressive Model for Sequence Generation","date":"2020-04-22","arxiv_id":"2004.10454","repositories_listed":0,"syntology":null},{"url":null,"slug":"discretized-bottleneck-in-vae-posterior","title":"Improve Variational Autoencoder for Text Generationwith Discrete Latent Bottleneck","date":"2020-04-22","arxiv_id":"2004.10603","repositories_listed":0,"syntology":null},{"url":null,"slug":"syntactic-structure-from-deep-learning","title":"Syntactic Structure from Deep Learning","date":"2020-04-22","arxiv_id":"2004.10827","repositories_listed":0,"syntology":null},{"url":null,"slug":"testing-machine-translation-via-referential","title":"Testing Machine Translation via Referential Transparency","date":"2020-04-22","arxiv_id":"2004.10361","repositories_listed":0,"syntology":null},{"url":null,"slug":"when-and-why-is-unsupervised-neural-machine","title":"When and Why is Unsupervised Neural Machine Translation Useless?","date":"2020-04-22","arxiv_id":"2004.10581","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-distillation-for-multilingual","title":"Knowledge Distillation for Multilingual Unsupervised Neural Machine Translation","date":"2020-04-21","arxiv_id":"2004.10171","repositories_listed":0,"syntology":null},{"url":null,"slug":"learnings-from-technological-interventions-in","title":"Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi","date":"2020-04-21","arxiv_id":"2004.10270","repositories_listed":0,"syntology":null},{"url":"/paper/phinc-a-parallel-hinglish-social-media-code","slug":"phinc-a-parallel-hinglish-social-media-code","title":"PHINC: A Parallel Hinglish Social Media Code-Mixed Corpus for Machine Translation","date":"2020-04-20","arxiv_id":"2004.09447","repositories_listed":0,"syntology":null},{"url":null,"slug":"cwy-parametrization-for-scalable-learning-of","title":"CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices","date":"2020-04-18","arxiv_id":"2004.08675","repositories_listed":0,"syntology":null},{"url":null,"slug":"enriching-the-transformer-with-linguistic-and","title":"Enriching the Transformer with Linguistic Factors for Low-Resource Machine Translation","date":"2020-04-17","arxiv_id":"2004.08053","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-a-multi-domain-neural-machine","title":"Building a Multi-domain Neural Machine Translation Model using Knowledge Distillation","date":"2020-04-15","arxiv_id":"2004.07324","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-machine-translation-closing-the","title":"Multilingual Machine Translation: Closing the Gap between Shared and Language-specific Encoder-Decoders","date":"2020-04-14","arxiv_id":"2004.06575","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-translation-and-the-end-to-end-promise","title":"Speech Translation and the End-to-End Promise: Taking Stock of Where We Are","date":"2020-04-14","arxiv_id":"2004.06358","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforced-curriculum-learning-on-pre-trained","title":"Reinforced Curriculum Learning on Pre-trained Neural Machine Translation Models","date":"2020-04-13","arxiv_id":"2004.05757","repositories_listed":0,"syntology":null},{"url":null,"slug":"when-does-unsupervised-machine-translation","title":"When Does Unsupervised Machine Translation Work?","date":"2020-04-12","arxiv_id":"2004.05516","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-in-depth-walkthrough-on-evolution-of","title":"An In-depth Walkthrough on Evolution of Neural Machine Translation","date":"2020-04-10","arxiv_id":"2004.04902","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-multilingual-frontend-for-tts","title":"Scalable Multilingual Frontend for TTS","date":"2020-04-10","arxiv_id":"2004.04934","repositories_listed":0,"syntology":null},{"url":null,"slug":"style-transfer-and-paraphrase-looking-for-a","title":"Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric","date":"2020-04-10","arxiv_id":"2004.05001","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-scale-multilingual","title":"Learning to Scale Multilingual Representations for Vision-Language Tasks","date":"2020-04-09","arxiv_id":"2004.04312","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-training-for-unsupervised-neural-machine","title":"Self-Training for Unsupervised Neural Machine Translation in Unbalanced Training Data Scenarios","date":"2020-04-09","arxiv_id":"2004.04507","repositories_listed":0,"syntology":null},{"url":null,"slug":"explicit-reordering-for-neural-machine","title":"Explicit Reordering for Neural Machine Translation","date":"2020-04-08","arxiv_id":"2004.03818","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-fluency-of-non-autoregressive","title":"Improving Fluency of Non-Autoregressive Machine Translation","date":"2020-04-07","arxiv_id":"2004.03227","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-with-unsupervised-length","title":"Machine Translation with Unsupervised Length-Constraints","date":"2020-04-07","arxiv_id":"2004.03176","repositories_listed":0,"syntology":null},{"url":null,"slug":"re-translation-versus-streaming-for","title":"Re-translation versus Streaming for Simultaneous Translation","date":"2020-04-07","arxiv_id":"2004.03643","repositories_listed":0,"syntology":null},{"url":null,"slug":"salience-estimation-with-multi-attention","title":"Salience Estimation with Multi-Attention Learning for Abstractive Text Summarization","date":"2020-04-07","arxiv_id":"2004.03589","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-induced-curriculum-learning-in-neural-1","title":"Self-Induced Curriculum Learning in Self-Supervised Neural Machine Translation","date":"2020-04-07","arxiv_id":"2004.03151","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-neural-machine-translation-with-4","title":"Cross-lingual Supervision Improves Unsupervised Neural Machine Translation","date":"2020-04-07","arxiv_id":"2004.03137","repositories_listed":0,"syntology":null},{"url":null,"slug":"applying-cyclical-learning-rate-to-neural","title":"Applying Cyclical Learning Rate to Neural Machine Translation","date":"2020-04-06","arxiv_id":"2004.02401","repositories_listed":0,"syntology":null},{"url":null,"slug":"dictionary-based-data-augmentation-for-cross","title":"Dictionary-based Data Augmentation for Cross-Domain Neural Machine Translation","date":"2020-04-06","arxiv_id":"2004.02577","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-learning-for-few-shot-nmt-adaptation","title":"Meta-Learning for Few-Shot NMT Adaptation","date":"2020-04-06","arxiv_id":"2004.02745","repositories_listed":0,"syntology":null},{"url":null,"slug":"ar-auto-repair-the-synthetic-data-for-neural","title":"AR: Auto-Repair the Synthetic Data for Neural Machine Translation","date":"2020-04-05","arxiv_id":"2004.02196","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-and-understanding-generalization","title":"Detecting and Understanding Generalization Barriers for Neural Machine Translation","date":"2020-04-05","arxiv_id":"2004.02181","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-bilingual-dictionaries-for-low","title":"Incorporating Bilingual Dictionaries for Low Resource Semi-Supervised Neural Machine Translation","date":"2020-04-05","arxiv_id":"2004.02071","repositories_listed":0,"syntology":null},{"url":"/paper/machine-translation-pre-training-for-data-to","slug":"machine-translation-pre-training-for-data-to","title":"Machine Translation Pre-training for Data-to-Text Generation -- A Case Study in Czech","date":"2020-04-05","arxiv_id":"2004.02077","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-learning-dynamics-for-neural","title":"Understanding Learning Dynamics for Neural Machine Translation","date":"2020-04-05","arxiv_id":"2004.02199","repositories_listed":0,"syntology":null},{"url":null,"slug":"recognizing-long-grammatical-sequences-using","title":"Recognizing Long Grammatical Sequences Using Recurrent Networks Augmented With An External Differentiable Stack","date":"2020-04-04","arxiv_id":"2004.07623","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-synchronous-context-free-grammars","title":"Learning synchronous context-free grammars with multiple specialised non-terminals for hierarchical phrase-based translation","date":"2020-04-03","arxiv_id":"2004.01422","repositories_listed":0,"syntology":null},{"url":"/paper/igbo-english-machine-translation-an","slug":"igbo-english-machine-translation-an","title":"Igbo-English Machine Translation: An Evaluation Benchmark","date":"2020-04-01","arxiv_id":"2004.00648","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-human-translations-from-french-to","title":"Assessing Human Translations from French to Bambara for Machine Learning: a Pilot Study","date":"2020-03-31","arxiv_id":"2004.00068","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-amharic-machine-translation","title":"Evaluating Amharic Machine Translation","date":"2020-03-31","arxiv_id":"2003.14386","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-integration-of-linguisticfeatures-into","title":"On the Integration of LinguisticFeatures into Statistical and Neural Machine Translation","date":"2020-03-31","arxiv_id":"2003.14324","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-contextualized-sentence","title":"Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation","date":"2020-03-30","arxiv_id":"2003.13205","repositories_listed":0,"syntology":null},{"url":null,"slug":"repository-for-reusing-artifacts-of","title":"Repository for Reusing Artifacts of Artificial Neural Networks","date":"2020-03-30","arxiv_id":"2003.13619","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-lstm-to-translate-french-to-senegalese","title":"Using LSTM to Translate French to Senegalese Local Languages: Wolof as a Case Study","date":"2020-03-27","arxiv_id":"2004.13840","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-neural-machine-translation-for-edoid","title":"Towards Neural Machine Translation for Edoid Languages","date":"2020-03-24","arxiv_id":"2003.10704","repositories_listed":0,"syntology":null},{"url":null,"slug":"sac-accelerating-and-structuring-self","title":"SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection","date":"2020-03-22","arxiv_id":"2003.09833","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-joint-approach-to-compound-splitting-and","title":"A Joint Approach to Compound Splitting and Idiomatic Compound Detection","date":"2020-03-21","arxiv_id":"2003.09606","repositories_listed":0,"syntology":null},{"url":null,"slug":"normalized-and-geometry-aware-self-attention","title":"Normalized and Geometry-Aware Self-Attention Network for Image Captioning","date":"2020-03-19","arxiv_id":"2003.08897","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-language-relatedness-to-improve","title":"Utilizing Language Relatedness to improve Machine Translation: A Case Study on Languages of the Indian Subcontinent","date":"2020-03-19","arxiv_id":"2003.08925","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-pidgin-text-generation-by","title":"Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training","date":"2020-03-18","arxiv_id":"2003.08272","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-machine-learning-application-for-raising","title":"A Machine Learning Application for Raising WASH Awareness in the Times of COVID-19 Pandemic","date":"2020-03-16","arxiv_id":"2003.07074","repositories_listed":0,"syntology":null},{"url":"/paper/trans-blstm-transformer-with-bidirectional","slug":"trans-blstm-transformer-with-bidirectional","title":"TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding","date":"2020-03-16","arxiv_id":"2003.07000","repositories_listed":0,"syntology":null},{"url":null,"slug":"asr-error-correction-and-domain-adaptation","title":"ASR Error Correction and Domain Adaptation Using Machine Translation","date":"2020-03-13","arxiv_id":"2003.07692","repositories_listed":0,"syntology":null},{"url":null,"slug":"capturing-document-context-inside-sentence","title":"Capturing document context inside sentence-level neural machine translation models with self-training","date":"2020-03-11","arxiv_id":"2003.05259","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-the-decoders-of-maximum","title":"Investigating the Decoders of Maximum Likelihood Sequence Models: A Look-ahead Approach","date":"2020-03-08","arxiv_id":"2003.03716","repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-of-word-embeddings-on-sentiment","title":"Quality of Word Embeddings on Sentiment Analysis Tasks","date":"2020-03-06","arxiv_id":"2003.03264","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-accuracy-law-for-sequential","title":"An Empirical Accuracy Law for Sequential Machine Translation: the Case of Google Translate","date":"2020-03-05","arxiv_id":"2003.02817","repositories_listed":0,"syntology":null},{"url":null,"slug":"distill-adapt-distill-training-small-in","title":"Distill, Adapt, Distill: Training Small, In-Domain Models for Neural Machine Translation","date":"2020-03-05","arxiv_id":"2003.02877","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-low-resource-machine-translation","title":"Evaluating Low-Resource Machine Translation between Chinese and Vietnamese with Back-Translation","date":"2020-03-04","arxiv_id":"2003.02197","repositories_listed":0,"syntology":null},{"url":null,"slug":"controllable-time-delay-transformer-for-real","title":"Controllable Time-Delay Transformer for Real-Time Punctuation Prediction and Disfluency Detection","date":"2020-03-03","arxiv_id":"2003.01309","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-embeddings-based-on-self-attention","title":"Meta-Embeddings Based On Self-Attention","date":"2020-03-03","arxiv_id":"2003.01371","repositories_listed":0,"syntology":null},{"url":null,"slug":"transformer","title":"Transformer++","date":"2020-03-02","arxiv_id":"2003.04974","repositories_listed":0,"syntology":null},{"url":null,"slug":"soft-root-sign-activation-function","title":"Soft-Root-Sign Activation Function","date":"2020-03-01","arxiv_id":"2003.00547","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-finite-state-transducer-based-morphological","title":"A Finite State Transducer Based Morphological Analyzer of Maithili Language","date":"2020-02-29","arxiv_id":"2003.00234","repositories_listed":0,"syntology":null},{"url":"/paper/word-sense-disambiguation-a-comprehensive","slug":"word-sense-disambiguation-a-comprehensive","title":"Word Sense Disambiguation: A comprehensive knowledge exploitation framework","date":"2020-02-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"do-all-roads-lead-to-rome-understanding-the","title":"Do all Roads Lead to Rome? Understanding the Role of Initialization in Iterative Back-Translation","date":"2020-02-28","arxiv_id":"2002.12867","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-future-cost-for-neural-machine","title":"Modeling Future Cost for Neural Machine Translation","date":"2020-02-28","arxiv_id":"2002.12558","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-unsupervised-neural-machine","title":"Robust Unsupervised Neural Machine Translation with Adversarial Denoising Training","date":"2020-02-28","arxiv_id":"2002.12549","repositories_listed":0,"syntology":null},{"url":null,"slug":"echo-state-neural-machine-translation","title":"Echo State Neural Machine Translation","date":"2020-02-27","arxiv_id":"2002.11847","repositories_listed":0,"syntology":null},{"url":"/paper/must-cinema-a-speech-to-subtitles-corpus","slug":"must-cinema-a-speech-to-subtitles-corpus","title":"MuST-Cinema: a Speech-to-Subtitles corpus","date":"2020-02-25","arxiv_id":"2002.10829","repositories_listed":0,"syntology":null},{"url":null,"slug":"fixed-encoder-self-attention-patterns-in","title":"Fixed Encoder Self-Attention Patterns in Transformer-Based Machine Translation","date":"2020-02-24","arxiv_id":"2002.10260","repositories_listed":0,"syntology":null},{"url":null,"slug":"gret-global-representation-enhanced","title":"GRET: Global Representation Enhanced Transformer","date":"2020-02-24","arxiv_id":"2002.10101","repositories_listed":0,"syntology":null},{"url":null,"slug":"a3-accelerating-attention-mechanisms-in","title":"A$^3$: Accelerating Attention Mechanisms in Neural Networks with Approximation","date":"2020-02-22","arxiv_id":"2002.10941","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-system-selection-from","title":"Machine Translation System Selection from Bandit Feedback","date":"2020-02-22","arxiv_id":"2002.09646","repositories_listed":0,"syntology":null},{"url":null,"slug":"guider-lattention-dans-les-modeles-de","title":"Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue","date":"2020-02-21","arxiv_id":"2002.09419","repositories_listed":0,"syntology":null},{"url":null,"slug":"balancing-cost-and-benefit-with-tied-multi-1","title":"Balancing Cost and Benefit with Tied-Multi Transformers","date":"2020-02-20","arxiv_id":"2002.08614","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-coupled-policies-for-simultaneous","title":"Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning","date":"2020-02-11","arxiv_id":"2002.04306","repositories_listed":0,"syntology":null},{"url":null,"slug":"mask-focus-conversation-modelling-by-learning","title":"Mask & Focus: Conversation Modelling by Learning Concepts","date":"2020-02-11","arxiv_id":"2003.04976","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-deep-rdfs-reasoner","title":"Explainable Deep RDFS Reasoner","date":"2020-02-10","arxiv_id":"2002.03514","repositories_listed":0,"syntology":null},{"url":null,"slug":"fastwave-accelerating-autoregressive","title":"FastWave: Accelerating Autoregressive Convolutional Neural Networks on FPGA","date":"2020-02-09","arxiv_id":"2002.04971","repositories_listed":0,"syntology":null},{"url":null,"slug":"importance-driven-deep-learning-system","title":"Importance-Driven Deep Learning System Testing","date":"2020-02-09","arxiv_id":"2002.03433","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multilingual-view-of-unsupervised-machine","title":"A Multilingual View of Unsupervised Machine Translation","date":"2020-02-07","arxiv_id":"2002.02955","repositories_listed":0,"syntology":null},{"url":null,"slug":"translating-web-search-queries-into-natural-2","title":"Translating Web Search Queries into Natural Language Questions","date":"2020-02-07","arxiv_id":"2002.02631","repositories_listed":0,"syntology":null},{"url":null,"slug":"compositional-neural-machine-translation-by","title":"Compositional Neural Machine Translation by Removing the Lexicon from Syntax","date":"2020-02-06","arxiv_id":"2002.08899","repositories_listed":0,"syntology":null},{"url":null,"slug":"lost-in-embedding-space-explaining-cross","title":"The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures","date":"2020-01-30","arxiv_id":"2001.11136","repositories_listed":0,"syntology":null},{"url":null,"slug":"pre-training-via-leveraging-assisting","title":"Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation","date":"2020-01-23","arxiv_id":"2001.08353","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-autoregressive-training-improves-mask","title":"Semi-Autoregressive Training Improves Mask-Predict Decoding","date":"2020-01-23","arxiv_id":"2001.08785","repositories_listed":0,"syntology":null},{"url":null,"slug":"normalization-of-input-output-shared","title":"Normalization of Input-output Shared Embeddings in Text Generation Models","date":"2020-01-22","arxiv_id":"2001.07885","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-speech-to-speech-translation-to","title":"From Speech-to-Speech Translation to Automatic Dubbing","date":"2020-01-19","arxiv_id":"2001.06785","repositories_listed":0,"syntology":null},{"url":null,"slug":"bi-decoder-augmented-network-for-neural","title":"Bi-Decoder Augmented Network for Neural Machine Translation","date":"2020-01-14","arxiv_id":"2001.04586","repositories_listed":0,"syntology":null},{"url":null,"slug":"urdu-english-machine-transliteration-using","title":"Urdu-English Machine Transliteration using Neural Networks","date":"2020-01-12","arxiv_id":"2001.05296","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-multi-task-learn-for-better","title":"Learning to Multi-Task Learn for Better Neural Machine Translation","date":"2020-01-10","arxiv_id":"2001.03294","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-approaches-for-amharic-parts","title":"Machine Learning Approaches for Amharic Parts-of-speech Tagging","date":"2020-01-10","arxiv_id":"2001.03324","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-benefits-of-transfer-learning-in","title":"Exploring Benefits of Transfer Learning in Neural Machine Translation","date":"2020-01-06","arxiv_id":"2001.01622","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-of-multilingual-neural","title":"A Comprehensive Survey of Multilingual Neural Machine Translation","date":"2020-01-04","arxiv_id":"2001.01115","repositories_listed":0,"syntology":null}],"record_sha256":"64a1ad66162a34afd11a65859aa8b98aa8f6517561f4c61ff177b104eb183e38","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}