{"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/41","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":41,"pages_in_order":108,"rows_per_page":100,"rows":[4001,4100],"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/40","next":"/task/machine-translation/papers/42","papers":[{"url":null,"slug":"can-multilinguality-benefit-non","title":"Can Multilinguality benefit Non-autoregressive Machine Translation?","date":"2021-12-16","arxiv_id":"2112.08570","repositories_listed":0,"syntology":null},{"url":"/paper/docmt5-document-level-pretraining-of","slug":"docmt5-document-level-pretraining-of","title":"DOCmT5: Document-Level Pretraining of Multilingual Language Models","date":"2021-12-16","arxiv_id":"2112.08709","repositories_listed":0,"syntology":null},{"url":null,"slug":"idiomatic-expression-paraphrasing-without","title":"Idiomatic Expression Paraphrasing without Strong Supervision","date":"2021-12-16","arxiv_id":"2112.08592","repositories_listed":0,"syntology":null},{"url":null,"slug":"isometricmt-neural-machine-translation-for","title":"Isometric MT: Neural Machine Translation for Automatic Dubbing","date":"2021-12-16","arxiv_id":"2112.08682","repositories_listed":0,"syntology":null},{"url":null,"slug":"prosody-aware-neural-machine-translation-for","title":"Isochrony-Aware Neural Machine Translation for Automatic Dubbing","date":"2021-12-16","arxiv_id":"2112.08548","repositories_listed":0,"syntology":null},{"url":null,"slug":"faster-nearest-neighbor-machine-translation","title":"Faster Nearest Neighbor Machine Translation","date":"2021-12-15","arxiv_id":"2112.08152","repositories_listed":0,"syntology":null},{"url":null,"slug":"lesan-machine-translation-for-low-resource","title":"Lesan -- Machine Translation for Low Resource Languages","date":"2021-12-15","arxiv_id":"2112.08191","repositories_listed":0,"syntology":null},{"url":null,"slug":"geo-bleu-similarity-measure-for-geospatial","title":"GEO-BLEU: Similarity Measure for Geospatial Sequences","date":"2021-12-14","arxiv_id":"2112.07144","repositories_listed":0,"syntology":null},{"url":null,"slug":"communication-efficient-federated-learning-11","title":"Communication-Efficient Federated Learning for Neural Machine Translation","date":"2021-12-12","arxiv_id":"2112.06135","repositories_listed":0,"syntology":null},{"url":null,"slug":"prosody-labelled-dataset-for-hindi-using-semi","title":"Prosody Labelled Dataset for Hindi using Semi-Automated Approach","date":"2021-12-11","arxiv_id":"2112.05973","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-language-model-to-predict-metabolic","title":"A deep language model to predict metabolic network equilibria","date":"2021-12-07","arxiv_id":"2112.03588","repositories_listed":0,"syntology":null},{"url":null,"slug":"skeletal-graph-self-attention-embedding-a","title":"Skeletal Graph Self-Attention: Embedding a Skeleton Inductive Bias into Sign Language Production","date":"2021-12-06","arxiv_id":"2112.05277","repositories_listed":0,"syntology":null},{"url":null,"slug":"multitask-finetuning-for-improving-neural","title":"Multitask Finetuning for Improving Neural Machine Translation in Indian Languages","date":"2021-12-03","arxiv_id":"2112.01742","repositories_listed":0,"syntology":null},{"url":null,"slug":"translating-politeness-across-cultures-case","title":"Translating Politeness Across Cultures: Case of Hindi and English","date":"2021-12-03","arxiv_id":"2112.01822","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-experiment-on-speech-to-text-translation","title":"An Experiment on Speech-to-Text Translation Systems for Manipuri to English on Low Resource Setting","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"are-ellipses-important-for-machine","title":"Are Ellipses Important for Machine Translation?","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"constrained-decoding-for-technical-term","title":"Constrained Decoding for Technical Term Retention in English-Hindi MT","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"document-level-hierarchical-transformer","title":"Document Level Hierarchical Transformer","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"edumt-developing-machine-translation-system","title":"EduMT: Developing Machine Translation System for Educational Content in Indian Languages","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"introduction-to-proverbnet-an-online","title":"Introduction to ProverbNet: An Online Multilingual Database of Proverbs and Comprehensive Metadata","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"laksyartha-indicated-meaning-of-sabdavyapara","title":"lakṣyārtha (Indicated Meaning) of Śabdavyāpāra (Function of a Word) framework from kāvyaśāstra (The Science of Literary Studies) in Samskṛtam : Its application to Literary Machine Translation and other NLP tasks","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-learning-for-improving-gender","title":"Multi-Task Learning for Improving Gender Accuracy in Neural Machine Translation","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"named-entity-factored-transformer-for-proper","title":"Named Entity-Factored Transformer for Proper Noun Translation","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-transferability-of-massively","title":"On the Transferability of Massively Multilingual Pretrained Models in the Pretext of the Indo-Aryan and Tibeto-Burman Languages","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"part-of-speech-tagging-for-a-resource-poor","title":"Part of Speech Tagging for a Resource Poor Language : Sindhi in Devanagari Script using HMM and CRF","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"prosody-labelled-dataset-for-hindi","title":"Prosody Labelled Dataset for Hindi","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantics-of-spatio-directional-geometric","title":"Semantics of Spatio-Directional Geometric Terms of Indian Languages","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improvement-in-machine-translation-with","title":"Improvement in Machine Translation with Generative Adversarial Networks","date":"2021-11-30","arxiv_id":"2111.15166","repositories_listed":0,"syntology":null},{"url":null,"slug":"karl-trans-ner-knowledge-aware-representation","title":"KARL-Trans-NER: Knowledge Aware Representation Learning for Named Entity Recognition using Transformers","date":"2021-11-30","arxiv_id":"2111.15436","repositories_listed":0,"syntology":null},{"url":"/paper/do-we-still-need-automatic-speech-recognition","slug":"do-we-still-need-automatic-speech-recognition","title":"Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?","date":"2021-11-29","arxiv_id":"2111.14842","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-neural-machine-translation-with-1","title":"Deps-SAN: Neural Machine Translation with Dependency-Scaled Self-Attention Network","date":"2021-11-23","arxiv_id":"2111.11707","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-softmax-approximation-for-deep","title":"Efficient Softmax Approximation for Deep Neural Networks with Attention Mechanism","date":"2021-11-21","arxiv_id":"2111.10770","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-processing-matters-srph-konvergen-ai-s","title":"Data Processing Matters: SRPH-Konvergen AI's Machine Translation System for WMT'21","date":"2021-11-20","arxiv_id":"2111.10513","repositories_listed":0,"syntology":null},{"url":null,"slug":"minimum-bayes-risk-decoding-with-neural","title":"High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics","date":"2021-11-17","arxiv_id":"2111.09388","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-graph-fusion-approach-to-cross-lingual","title":"A Graph Fusion Approach to Cross-Lingual Machine Reading Comprehension","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-natural-diet-towards-improving-naturalness","title":"A Natural Diet: Towards Improving Naturalness of Machine Translation Output","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-neural-approach-to-kgqa-via-sparql","title":"A Neural Approach to KGQA via SPARQL Silhouette Generation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-primer-in-nmtology-what-we-have-understood","title":"A Primer in NMTology: What we have understood about NMT","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-online-posterior-alignments-for","title":"Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-study-of-document-to-document","title":"An Empirical Study of Document-to-document Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"as-little-as-possible-as-much-as-necessary","title":"As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"automode-choosing-the-best-machine","title":"Automode: Choosing the Best Machine Translation Supplier Based on Source Text","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bidirectional-modeling-for-simultaneous","title":"Bidirectional Modeling for Simultaneous Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-the-data-gap-between-training-and","title":"Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"causal-transformers-improving-the-robustness","title":"Causal Transformers: Improving the Robustness on Spurious Correlations","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-conditional-masked-language-model","title":"Contrastive Conditional Masked Language Model for Non-autoregressive Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-learning-for-low-resource-machine","title":"Contrastive Learning for Low Resource Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cost-effective-training-in-low-resource","title":"Cost-Effective Training in Low-Resource Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"daqe-exploring-the-direct-assessment-on-word","title":"DAQE: Exploring the Direct Assessment on Word-Level Quality Estimation in Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"data-adaptive-transfer-learning-for-low","title":"Data-adaptive Transfer Learning for Low-resource Translation: A Case Study in Haitian","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"data-driven-adaptive-simultaneous-machine","title":"Data-Driven Adaptive Simultaneous Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dict-nmt-bilingual-dictionary-based-nmt-for","title":"Dict-NMT: Bilingual Dictionary based NMT for Extremely Low Resource Languages","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"disentangled-sequence-to-sequence-learning-1","title":"Disentangled Sequence to Sequence Learning for Compositional Generalization","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"divide-and-rule-effective-pre-training-for","title":"Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-neural-machine-translation-with","title":"Enhancing Neural Machine Translation with Syntactic Ambiguities","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-the-nonlinear-mutual-dependencies","title":"Enhancing the Nonlinear Mutual Dependencies in Transformers with Mutual Information","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"focus-on-the-targets-vocabulary-masked-label","title":"Focus on the Target’s Vocabulary: Masked Label Smoothing for Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"freezing-the-pivot-for-triangular-machine","title":"Freezing the Pivot for Triangular Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-authentic-adversarial-examples","title":"Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-neural-networks-for-multiparallel-word","title":"Graph Neural Networks for Multiparallel Word Alignment","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-translate-your-samples-and-choose-your","title":"How to Translate Your Samples and Choose Your Shots? Analyzing Translate-train & Few-shot Cross-lingual Transfer","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-paraphrase-generation-models-with","title":"Improving Paraphrase Generation models with machine translation generated pre-training","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"indicbart-a-pre-trained-model-for-indic","title":"IndicBART: A Pre-trained Model for Indic Natural Language Generation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"indicxnli-a-dataset-for-studying-nli-in-indic","title":"INDICXNLI: A Dataset for Studying NLI in Indic Languages","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-vectorized-lexical-constraints","title":"Integrating Vectorized Lexical Constraints for Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"language-family-adapters-for-multilingual","title":"Language-Family Adapters for Multilingual Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"low-rank-softmax-can-have-unargmaxable","title":"Low rank softmax can have unargmaxable classes in theory but rarely in practice","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mad-for-robust-reinforcement-learning-in","title":"MAD for Robust Reinforcement Learning in Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"maximum-proxy-likelihood-estimation-for-non","title":"Maximum Proxy-Likelihood Estimation for Non-autoregressive Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mitigating-gender-bias-in-machine-translation-1","title":"Mitigating Gender Bias in Machine Translation through Adversarial Learning","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-stage-framework-with-refinement-based","title":"Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-document-level-translation-1","title":"Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nvidia-nemo-neural-machine-translation","title":"NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21","date":"2021-11-16","arxiv_id":"2111.08634","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-systematic-style-differences-between","title":"On Systematic Style Differences between Unsupervised and Supervised MT and an Application for High-Resource Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-vision-features-in-multimodal-machine","title":"On Vision Features in Multimodal Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"onealigner-zero-shot-cross-lingual-transfer","title":"OneAligner: Zero-shot Cross-lingual Transfer with One Rich-Resource Language Pair for Low-Resource Sentence Retrieval","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"overcoming-a-theoretical-limitation-of-self","title":"Overcoming a Theoretical Limitation of Self-Attention","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-attention-sparsity-in-transformers-1","title":"Predicting Attention Sparsity in Transformers","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-aware-decoding-for-neural-machine","title":"Quality-Aware Decoding for Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"rare-tokens-degenerate-all-tokens-improving","title":"Rare Tokens Degenerate All Tokens: Improving Neural Text Generation via Adaptive Gradient Gating for Rare Token Embeddings","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"research-on-the-evaluation-of-token-imbalance","title":"Research on the Evaluation of Token Imbalance Degree of NMT Corpus","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"stablemoe-stable-routing-strategy-for-mixture","title":"StableMoE: Stable Routing Strategy for Mixture of Experts","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"teaching-bert-to-wait-balancing-accuracy-and","title":"Teaching BERT to Wait: Balancing Accuracy and Latency for Streaming Disfluency Detection","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"that-slepen-al-the-nyght-with-open-ye-cross","title":"That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-fine-grained-multi-domain-neural","title":"Towards a Fine-Grained Multi-Domain Neural Machine Translation Using Inter-Domain Relationships","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"training-data-is-more-valuable-than-you-think","title":"Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-and-improving-sequence-to","title":"Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-nmt-models-for-the-indian","title":"Unified NMT models for the Indian subcontinent transcending script-barriers","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"wets-a-benchmark-for-translation-suggestion-1","title":"WeTS: A Benchmark for Translation Suggestion","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"what-works-and-doesn-t-work-a-deep-decoder","title":"What Works and Doesn't Work, A Deep Decoder for Neural Machine Translation","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"when-does-translation-require-context-a-data-1","title":"When Does Translation Require Context? A Data-driven, Multilingual Exploration","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"measuring-uncertainty-in-translation-quality","title":"Measuring Uncertainty in Translation Quality Evaluation (TQE)","date":"2021-11-15","arxiv_id":"2111.07699","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-denoising-entity-pre-training-for-neural","title":"DEEP: DEnoising Entity Pre-training for Neural Machine Translation","date":"2021-11-14","arxiv_id":"2111.07393","repositories_listed":0,"syntology":null},{"url":null,"slug":"sign-language-translation-with-hierarchical","title":"Sign Language Translation with Hierarchical Spatio-TemporalGraph Neural Network","date":"2021-11-14","arxiv_id":"2111.07258","repositories_listed":0,"syntology":null},{"url":null,"slug":"bitextedit-automatic-bitext-editing-for","title":"BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation","date":"2021-11-12","arxiv_id":"2111.06787","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-neural-networks-predict-dynamics-they","title":"Can neural networks predict dynamics they have never seen?","date":"2021-11-12","arxiv_id":"2111.06783","repositories_listed":0,"syntology":null},{"url":null,"slug":"developing-neural-machine-translation-models","title":"Developing neural machine translation models for Hungarian-English","date":"2021-11-07","arxiv_id":"2111.04099","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-architectures-for-neural-machine","title":"Analyzing Architectures for Neural Machine Translation Using Low Computational Resources","date":"2021-11-06","arxiv_id":"2111.03813","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-syntax-guided-grammatical-error-correction","title":"A Syntax-Guided Grammatical Error Correction Model with Dependency Tree Correction","date":"2021-11-05","arxiv_id":"2111.03294","repositories_listed":0,"syntology":null},{"url":null,"slug":"oracle-teacher-towards-better-knowledge","title":"Oracle Teacher: Leveraging Target Information for Better Knowledge Distillation of CTC Models","date":"2021-11-05","arxiv_id":"2111.03664","repositories_listed":0,"syntology":null}],"record_sha256":"29b5ea25023c9088c70a01cc2b9b70634417d0f305d823ee80f06379c74de8fc","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}