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A Template-based Method for Constrained Neural Machine Translation [article]

Shuo Wang, Peng Li, Zhixing Tan, Zhaopeng Tu, Maosong Sun, Yang Liu
2022 arXiv   pre-print
In this work, we propose a template-based method that can yield results with high translation quality and match accuracy while keeping the decoding speed.  ...  Experimental results show that the proposed template-based methods can outperform several representative baselines in lexically and structurally constrained translation tasks.  ...  Joanis et al. (2013) examine a two-stage method for statistical machine translation systems, which firstly translates the plain text and then injects the tags based on phrase alignments and some carefully  ... 
arXiv:2205.11255v1 fatcat:omqf6pfczraihklv35ghzu42pq

A Survey on Retrieval-Augmented Text Generation [article]

Huayang Li and Yixuan Su and Deng Cai and Yan Wang and Lemao Liu
2022 arXiv   pre-print
It firstly highlights the generic paradigm of retrieval-augmented generation, and then it reviews notable approaches according to different tasks including dialogue response generation, machine translation  ...  This paper aims to conduct a survey about retrieval-augmented text generation.  ...  Retrieve, rerank and rewrite: Soft template based neural summarization.  ... 
arXiv:2202.01110v2 fatcat:vo6i5vq62raxtcry2xcbrm55be

Duplex Sign Language Communicator

Prof. Prema Sahane
2021 International Journal for Research in Applied Science and Engineering Technology  
, based on the data sets and various Machine learning algorithms the text will be converted to sign language.  ...  The finger gestures are captured by the camera and using various machine learning algorithms the system will automatically translate the signs to the readable text, similarly in sign to text conversion  ...  Classification methods used for recognition is Neural Network(NN). A.  ... 
doi:10.22214/ijraset.2021.35059 fatcat:gsltxfcpj5crhdstpdj56ylcyy

Pattern-based Acquisition of Scientific Entities from Scholarly Article Titles [article]

Jennifer D'Souza, Soeren Auer
2021 arXiv   pre-print
We describe a rule-based approach for the automatic acquisition of salient scientific entities from Computational Linguistics (CL) scholarly article titles.  ...  In total, 19,799 research problems, 18,111 solutions, 20,033 resources, 1,059 languages, 6,878 tools, and 21,687 methods were extracted at an average precision of 75%.  ...  (7) 21st machine translation (210) Twitter (204) neural networks (57) 20th speech recognition (16) TAGs (9) neural networks (6) 21st neural machine translation (193) social media (132) conditional  ... 
arXiv:2109.00199v2 fatcat:m6unmkjofjfe3ckfnb5h5f7zc4

Protein structure prediction by AlphaFold2: are attention and symmetries all you need?

Nazim Bouatta, Peter Sorger, Mohammed AlQuraishi
2021 Acta Crystallographica Section D: Structural Biology  
longstanding physics-based approaches.  ...  unifying framework for learning from protein data.  ...  MA is a member of the SAB of FL2021-002, a Foresite Labs company, and consults for Interline Therapeutics.  ... 
doi:10.1107/s2059798321007531 pmid:34342271 pmcid:PMC8329862 fatcat:sam47cns4fhg3hgo273qoshlta

NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics [article]

Ximing Lu, Sean Welleck, Peter West, Liwei Jiang, Jungo Kasai, Daniel Khashabi, Ronan Le Bras, Lianhui Qin, Youngjae Yu, Rowan Zellers, Noah A. Smith, Yejin Choi
2021 arXiv   pre-print
Our approach outperforms competitive baselines on five generation tasks, and achieves new state-of-the-art performance on table-to-text generation, constrained machine translation, and keyword-constrained  ...  We develop efficient lookahead heuristics that are efficient for large-scale language models, making our method a drop-in replacement for common techniques such as beam search and top-k sampling.  ...  Constrained Machine Translation It is often critical to have control over machine translation output.  ... 
arXiv:2112.08726v1 fatcat:2b6havfx2jfwzhxge27uuyuxh4

Face Recognition: A Survey

Shailaja A Patil1 And Dr. P. J. Deore2
2013 Zenodo  
The methods which are used to extract features are robust to low-resolution images. The method is a trainable system for selecting face features.  ...  After the feature selection procedure next procedure is matching for face recognition. The recognition accuracy is increased by advanced methods.  ...  Deore for his continuous support. Also I am very much thankful to Prof. Dr. J. B. Patil. Finally I would like to thanks my husband Mr. Dinesh A Patil for his continuous support.  ... 
doi:10.5281/zenodo.1438611 fatcat:gmznwbriuvccrnyj4pgbbzxuci

Learning Neural Templates for Text Generation

Sam Wiseman, Stuart Shieber, Alexander Rush
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
This work proposes a neural generation system using a hidden semimarkov model (HSMM) decoder, which learns latent, discrete templates jointly with learning to generate.  ...  We show that this model learns useful templates, and that these templates make generation both more interpretable and controllable.  ...  Acknowledgments SW gratefully acknowledges the support of a Siebel Scholars award. AMR gratefully acknowledges the support of NSF CCF-1704834, Intel Research, and Amazon AWS Research grants.  ... 
doi:10.18653/v1/d18-1356 dblp:conf/emnlp/WisemanSR18 fatcat:gdlefutuc5go5mysbhluxxkdbi

Chinese Poetry Generation with Planning based Neural Network [article]

Zhe Wang, Wei He, Hua Wu, Haiyang Wu, Wei Li, Haifeng Wang, Enhong Chen
2016 arXiv   pre-print
, using a modified recurrent neural network encoder-decoder framework.  ...  The proposed planning-based method can ensure that the generated poem is coherent and semantically consistent with the user's intent.  ...  The Attention based Neural Machine Translation method. It considers the problem as a machine translation task, which is similar to the traditional SMT approach.  ... 
arXiv:1610.09889v2 fatcat:fcs64ata2rc5zp6nabve3d5kn4

Findings of the Third Workshop on Neural Generation and Translation

Hiroaki Hayashi, Yusuke Oda, Alexandra Birch, Ioannis Konstas, Andrew Finch, Minh-Thang Luong, Graham Neubig, Katsuhito Sudoh
2019 Proceedings of the 3rd Workshop on Neural Generation and Translation  
This document describes the findings of the Third Workshop on Neural Generation and Translation, held in concert with the annual conference of the Empirical Methods in Natural Language Processing (EMNLP  ...  Second, we describe the results of the two shared tasks 1) efficient neural machine translation (NMT) where participants were tasked with creating NMT systems that are both accurate and efficient, and  ...  Acknowledgments We thank Apple and Google for their monetary support of student travel awards for the workshop, and AWS for its gift of AWS credits (to Graham Neubig) that helped support the evaluation  ... 
doi:10.18653/v1/d19-5601 dblp:conf/emnlp/HayashiOBKFLNS19 fatcat:k4xypk6a6rhipgh4oiqdrnew7y

Natural Language Processing with Small Feed-Forward Networks [article]

Jan A. Botha, Emily Pitler, Ji Ma, Anton Bakalov, Alex Salcianu, David Weiss, Ryan McDonald, Slav Petrov
2017 arXiv   pre-print
Motivated by resource-constrained environments like mobile phones, we showcase simple techniques for obtaining such small neural network models, and investigate different tradeoffs when deciding how to  ...  We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while being considerably cheaper  ...  Acknowledgments We thank Kuzman Ganchev, Fernando Pereira, and the anonymous reviewers for their useful comments.  ... 
arXiv:1708.00214v1 fatcat:u7yylq746rek5frunw3kq724be

Natural language understanding for task oriented dialog in the biomedical domain in a low resources context [article]

Antoine Neuraz, Leonardo Campillos Llanos, Anita Burgun, Sophie Rosset
2018 arXiv   pre-print
Our results show that this method could be used to develop a baseline system.  ...  To overcome this issue, we explore data generation using templates and terminologies and data augmentation approaches.  ...  We use a machine translation method to increase the variability of the training set by producing paraphrases of the question templates.  ... 
arXiv:1811.09417v2 fatcat:rgxvew5cizgbxmwmv4n6w5gpwq

Why is constrained neural language generation particularly challenging? [article]

Cristina Garbacea, Qiaozhu Mei
2022 arXiv   pre-print
for constrained text generation.  ...  conditions and constraints (the latter being testable conditions on the output text instead of the input), present constrained text generation tasks, and review existing methods and evaluation metrics  ...  Unsupervised machine translation methods are adapted for the task of text-style transfer by incorporating stylistic constraints in a neural seq2seq model with attention and using a style classifier to  ... 
arXiv:2206.05395v1 fatcat:nnoqdgda4be45lj5tjo3xt7kbe

Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods [article]

Wei Li, Wenhao Wu, Moye Chen, Jiachen Liu, Xinyan Xiao, Hua Wu
2022 arXiv   pre-print
Many studies on analysis, evaluation, and optimization methods for faithfulness problems have been proposed for various tasks, but have not been organized, compared and discussed in a combined manner.  ...  We organize the evaluation and optimization methods for different tasks into a unified taxonomy to facilitate comparison and learning across tasks. Several research trends are discussed further.  ...  Other Methods Kim et al. ( Faithfulness in Machine Translation Neural machine translation (NMT) has achieved great success due to the ability to generate highquality sentences.  ... 
arXiv:2203.05227v1 fatcat:q2u3ojyi6vb7pjt6ajwbinjmpa

Lexicon-constrained Copying Network for Chinese Abstractive Summarization [article]

Boyan Wan, Mishal Sohail
2021 arXiv   pre-print
To solve this problem, we propose a lexicon-constrained copying network that models multi-granularity in both encoder and decoder.  ...  Both forms can outperform previous character-based models and achieve competitive performances.  ...  Tu, “Multi-granularity self- former encoder for neural machine translation,” in Proceedings of the attention for neural machine translation,” in Proceedings of the 2019 57th Conference  ... 
arXiv:2010.08197v2 fatcat:7mp7mvrh2jbqzpch4zp7axfoce
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