[PDF] Top 20 Machine Translation Using Abductive Inference
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Machine Translation Using Abductive Inference
... Machine Translation Using Abductive Inference M a c h i n e T r a n s l a t i o n U s i n g A b d u c t i v e I n f e r e n c e Jerry R Hobbs and Megumi Kameyama SI LI International 333 Ravenswood Ave[.] ... See full document
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Bridging the Gap between Training and Inference for Neural Machine Translation
... at inference. To mitigate the discrepancy be- tween training and inference, when predicting one word, we feed as context either the ground truth word or the previous predicted word with a sam- pling ...real ... See full document
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Models and Inference for Prefix Constrained Machine Translation
... The same model scores both alignment of the prefix and translation of the suffix. However, dif- ferent feature weights may be appropriate for scor- ing each step of the inference process. In order to learn ... See full document
10
On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference
... Why use recast NLI? We focus on NLI, as op- posed to a wide range of NLP taks, as a uni- fied framework that can capture a variety of se- mantic phenomena based on arguments by Whi- te et al. (2017). Their recast dataset ... See full document
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GREAT: A Finite State Machine Translation Toolkit Implementing a Grammatical Inference Approach for Transducer Inference (GIATI)
... should not be taken into account. However, as far as the words in the test sentence are compatible with the corresponding transitions, and according to the phrase score, this (word) synchronous pars- ing algorithm may ... See full document
9
Fast Neural Machine Translation Implementation
... Our second system uses multiplicative- LSTM (Krause et al., 2017) in the encoder and the first layer of a decder, and a GRU in the second layer, trained with an extension of the Nematus (Sennrich et al., 2017) toolkit ... See full document
6
Survey on Attention Neural Network Models for Natural Language Processing
... like machine translation, sentence summarization,sentence pair modeling, paraphrase identification, natural language inference, question answering etc typically learn the sentence embedding for ... See full document
5
Towards Better Modeling Hierarchical Structure for Self Attention with Ordered Neurons
... on machine translation, targeted linguis- tic evaluation and logical inference tasks show that the proposed models achieve better performances by modeling hierarchical structure of ... See full document
6
Contextual Text Denoising with Masked Language Model
... We test the performance of the proposed text de- noising method on three downstream tasks: neural machine translation, natural language inference, and paraphrase detection. All experiments are ... See full document
5
cdec: A Decoder, Alignment, and Learning Framework for Finite State and Context Free Translation Models
... surface using k- best approximations of the decoder search space, cdec’s implementation performs inference over the full hypergraph structure (Kumar et ...simply using the I NSIDE algorithm. Since ... See full document
6
Domain Adaptive Inference for Neural Machine Translation
... At inference time we may not know the test data domain to match with the best adapted model, let alone optimal weights for an ensemble on that do- ...labelling using our adaptive decod- ing schemes with ... See full document
7
Probabilistic Inference for Machine Translation
... given translation string is calculated as the sum of the probabilities of all the derivations that yield that ...reference translation is not known, the exact calculation of this summa- tion is ... See full document
9
Non-Autoregressive Machine Translation with Auxiliary Regularization
... efficient inference of the NAT ...representations using two auxiliary regularization terms for model ...repeated translation, we propose to force the similarity of two neighboring hidden state ... See full document
8
A Markov Model of Machine Translation using Non parametric Bayesian Inference
... in machine translation, starting with the venerable IBM trans- lation models (Brown et ...and translation performance over simpler ...lar translation decisions, alignment jumps and fer- ... See full document
10
Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques
... the translation in the models. We built this test set using a sentence pattern “I’ve known {her, him, <proper noun>} for a long time, my friend works as {a, an} ...before using them in the ... See full document
8
Abductive Inference for Interpretation of Metaphors
... The output of the abduction engine is similar to the logical forms provided in Fig. 2. In order to make the output more reader friendly, we produce a natural language representation of the metaphor interpretation ... See full document
9
Learning to translate with products of novices: a suite of open ended challenge problems for teaching MT
... chine translation should be good paraphrases of each other (Owczarzak et ...between machine translation and reference under a simple model in which words could align if they were ... See full document
14
Proceedings of the Third Conference on Machine Translation: Research Papers
... Yongchao Deng, Shanbo Cheng, Jun Lu, Kai Song, Jingang Wang, Shenglan Wu, Liang Yao, Guchun Zhang, Haibo Zhang, Pei Zhang, Changfeng Zhu and Boxing Chen . . . . . . . . . . . . . . . . . . . . . . 368 The RWTH Aachen ... See full document
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Using Lexicalized Tags for Machine Translation
... Using Lexicalized Tags for Machine Translation Using Lexicalized Tags for Machine Translation * Anne Abeilld University of Paris 7 Jussieu LADL 2 place Jussieu, 75005 Paris France abeilleC~franz ibp f[.] ... See full document
6
Interactive Machine Translation using Hierarchical Translation Models
... Finally, we compared the estimated human effort required to translate the test partitions of the EU and TED corpora with the best IMT configuration (inde- pendent suffix formalization with hierarchical trans- lation ... See full document
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