Who cites «A Study of Translation Edit Rate with Targeted Human Annotation» · page 15

1514 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

pasricha-2023-cured4nlg-dataset-table-text-generation
pasunuru-2020-dorb-dynamically-optimizing-multiple-rewards
patel-2024-tweak-trust-assessing-reliability-summarization
patro-2018-learning-semantic-sentence-embeddings-pair
peitz-2013-rwth-aachen-machine-translation-system
pengpun-2024-creating-english-thai-code-switched
penkale-2010-accuracy-based-scoring-phrase-based
peter-2016-rwth-aachen-university-english-romanian
piwek-2012-varieties-question-generation-introduction-this
popovic-2019-automatic-error-classification-multiple-error
potash-2016-simihawk-semeval-2016-task-1
potet-2011-oracle-based-training-phrase-based
potet-2012-better-understanding-statistical-post-editing
powell-2008-use-machine-generated-transcripts-during
przybyla-2016-nactem-semeval-2016-task-1
puranik-2021-attentive-fine-tuning-transformers-translation
pylypenko-2018-dfki-mlt-system-description-wmt18
quernheim-2014-large-scale-exact-decoding-ims
rikters-2015-multi-system-machine-translation-online
rios-2018-creating-best-development-corpus-statistical
rosendahl-2021-recurrent-attention-transformer
rosti-2012-review-hypothesis-alignment-algorithms-mt
russo-2024-click-it-or-not-click
sabet-2016-unsupervised-method-automatic-translation-memory
salazar-2020-ipn-cic-team-system-submission
salvador-2025-benchmarking-llms-semantic-overlap-summarization
sayed-2024-spring-lab-iitm-s-submission
scansani-2019-do-translator-trainees-trust-machine
scansani-2020-how-do-lsps-compute-mt
scao-2023-joint-representations-text-knowledge-graphs
schaefer-2014-moses-smt-as-aid-translators
schwenk-2009-lium-s-statistical-machine-translation
schwenk-2010-adaptation-d-un-systeme-de
screen-2017-machine-translation-welsh-analysing-free
sen-2019-iitp-mt-system-gujarati-english
servan-2012-calculation-phrase-probabilities-statistical-machine
servan-2015-adaptation-par-enrichissement-terminologique-en
sharami-2025-analysis-vocabulary-subword-tokenization-settings
sharma-2022-mtlens-machine-translation-output-debugging
sharma-2024-aixplain-sdk-high-level-standardized
sharma-2025-quality-informed-segment-level-error
shivashankar-2016-filter-match-approach-pair-wise
shterionov-2016-improving-kantanmt-training-efficiency-fast
signoroni-2023-muni-nlp-systems-low-resource
simianer-2019-measuring-immediate-adaptation-performance-neural
singh-2015-empirical-study-diversity-word-alignment
singh-2020-nits-cnlp-system-unsupervised-mt
singh-2025-information-theoretic-approach-reducing-fertility
sofianopoulos-2007-demonstration-greek-english-metis-ii
sokolov-2015-coactive-learning-view-online-structured
solfrini-2025-normaliser-le-moyen-francais-du
soto-2022-comparing-combining-tagging-different-decoding
sousa-2023-enhancing-accessible-communication-european-portuguese
srivastava-2016-how-configure-statistical-machine-translation
stanchev-2019-eed-extended-edit-distance-measure
stanchev-2020-better-evaluation-metrics-machine-translation
stanojevic-2015-reordering-grammar-induction
stanojevic-2015-results-wmt15-metrics-shared-task
stasimioti-2020-machine-translation-quality-comparative-evaluation
sudoh-2014-japanese-english-patent-translation-system
sun-2010-mining-correlation-between-human-automatic
sun-2012-can-word-segmentation-be-considered
takebayashi-2018-word-rewarding-adequate-neural-machine
tambouratzis-2014-comparing-crf-template-matching-phrasing
tambouratzis-2014-expanding-language-model-low-resource
tambouratzis-2015-establishing-sentential-structure-realignments-small
tambouratzis-2016-linguistically-inspired-language-model-augmentation
tang-2023-dual-reinforcement-method-data-augmentation
tayir-2024-visual-pivoting-unsupervised-multimodal-machine
tebbifakhr-2018-multi-source-transformer-automatic-post
tebbifakhr-2019-effort-aware-neural-automatic-post
temnikova-2012-clcm-linguistic-resource-effective-simplification
tezcan-2016-ugent-lt3-scate-submission-wmt16
tillmann-2008-rule-driven-dynamic-programming-decoder
toral-2014-is-machine-translation-ready-literature
trilles-2010-online-language-model-adaptation-n
trilles-2014-efficient-wordgraph-interactive-translation-prediction
twitto-2015-statistical-machine-translation-automatic-identification
unanue-2018-shared-attention-mechanism-interpretation-neural
vadehra-2025-time-is-effort-estimating-human
vanallemeersch-2015-semantics-based-pretranslation-smt-fuzzy
velazquez-2025-langmark-multilingual-dataset-automatic-post
vico-2023-larth-dataset-machine-translation-etruscan
vieira-2013-evaluation-tools-post-editing-research
vinh-2020-uet-ictu-submissions-vlsp-2020
vo-2024-eatt-knowledge-graph-integration-transformer
vongpaseut-2023-evaluating-generalization-property-prefix-based
vu-2015-tato-leveraging-multiple-strategies-semantic
vu-2021-automatic-post-editing-vietnamese
wang-2015-english-chinese-translation-how-chinese
wang-2021-transformer-based-direct-hidden-markov
wenniger-2017-elastic-substitution-decoding-hierarchical-smt
wisniewski-2013-corpus-post-edited-translations-un
wolk-2013-polish-english-speech-statistical-machine
wong-2018-register-sensitive-translation-case-study
wu-2014-red-dcu-casict-submission-metrics
wu-2015-improved-hierarchical-word-sequence-language
wu-2016-generalized-framework-hierarchical-word-sequence
wuebker-2012-fast-scalable-decoding-language-model
wuebker-2013-length-incremental-phrase-training-smt

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