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The Amazing World of Neural Language Generation

Yangfeng Ji, Antoine Bosselut, Thomas Wolf, Asli Celikyilmaz
2020 Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts   unpublished
Neural Language Generation (NLG) -using neural network models to generate coherent text -is among the most promising methods for automated text creation.  ...  In this tutorial, we will present an overview of the current state-of-the-art in neural network architectures, and how they shaped recent research directions in text generation.  ...  Interest in neural text generation was recently catalyzed by the renaissance of neural network research in natural language processing, particularly with the development of neural language models and encoder-decoder  ... 
doi:10.18653/v1/2020.emnlp-tutorials.7 fatcat:xmejiul23vc3dgtr5bmxzwsea4

The Complete Analysis of Machine Learning and Artificial Intelligence

Mahmoud Abdellatif
2020 Zenodo  
As mankind is making tremendous strides in development the use of Machine Learning and Artificial Intelligence has got even more important since these are arguably the building blocks of the future.  ...  In this paper I highlight the benefits of all mainstream forms of Artificial Intelligence and Machine Learning.  ...  NLP or better known as Normal Language Dealing is the limit of Computers to analyze, appreciate, and to produce the human language, including the method of speaking.  ... 
doi:10.5281/zenodo.3985329 fatcat:eg566enqfvbcxnqksmntionvh4

On End-to-End Program Generation from User Intention by Deep Neural Networks [article]

Lili Mou, Rui Men, Ge Li, Lu Zhang, Zhi Jin
2015 arXiv   pre-print
This paper envisions an end-to-end program generation scenario using recurrent neural networks (RNNs): Users can express their intention in natural language; an RNN then automatically generates corresponding  ...  Although much long-term research shall be addressed in this new field, we believe end-to-end program generation would become a reality in future decades, and we are looking forward to its practice.  ...  ., deep neural network) learns the mapping from natural language of problem descriptions to source code.  ... 
arXiv:1510.07211v1 fatcat:gmmz2vceybe5liqes5ke5f7zxu

Narrowing pay gaps

2014 Nature  
Janelia was one of the few places in the world where this research could have been developed.  ...  But I was also interested in biology, stemming largely from wanting to understand the neural basis of language and behaviour.  ... 
doi:10.1038/nj7499-251d fatcat:qi3vvjjhxzeozm6ylsw5sx3m3u

Learn from leisure

2014 Nature  
Janelia was one of the few places in the world where this research could have been developed.  ...  But I was also interested in biology, stemming largely from wanting to understand the neural basis of language and behaviour.  ... 
doi:10.1038/nj7499-251b fatcat:j5fun7ea6fbylllst3hy6sofdi

Cognitive Computational Neuroscience: A New Conference for an Emerging Discipline

Thomas Naselaris, Danielle S. Bassett, Alyson K. Fletcher, Konrad Kording, Nikolaus Kriegeskorte, Hendrikje Nienborg, Russell A. Poldrack, Daphna Shohamy, Kendrick Kay
2018 Trends in Cognitive Sciences  
Despite this shared goal, the three disciplines largely work independently of one another and have developed strikingly different languages, concepts, and tools.  ...  In September 2017 more than 600 research leaders and trainees from the different disciplines came together for three days of  ...  Acknowledgments The authors thank A. Oliva for critical early encouragement and advice. They gratefully acknowledge support from the National Science Foundation (  ... 
doi:10.1016/j.tics.2018.02.008 pmid:29500078 pmcid:PMC5911192 fatcat:dkhiilcxy5g4blhgc44ijx4l7i

Explaining Deep Neural Networks [article]

Oana-Maria Camburu
2021 arXiv   pre-print
The second direction consists of self-explanatory neural models that generate natural language explanations, that is, models that have a built-in module that generates explanations for the predictions  ...  However, the decision-making processes of these models are generally not interpretable to users.  ...  is to be applied to complex real-world neural network models.  ... 
arXiv:2010.01496v2 fatcat:knihfgpgr5efvc4nnqcbrmseue

Panel

Yueting Zhuang, Ramesh Jain, Wen Gao, Liu Ren, Kiyoharu Aizawa
2017 Proceedings of the 2017 ACM on Multimedia Conference - MM '17  
Thus, the effective employment of the interaction between cross-media data during inference and reasoning becomes a challenge to populate the cross-media knowledge graph.  ...  Some other fundamental and controversial issues such as leveraging the auxiliary information to boost the cross-media understanding, the existence of unified framework to bridge the gap between multi-modality  ...  Integrated together, these media data represent different aspects of the real-world and help document the evolution of the world.  ... 
doi:10.1145/3123266.3133336 dblp:conf/mm/ZhuangJGRA17 fatcat:uhmtomk3tzfb7hdp626ptlom64

Complex systems: the amazing cross-disciplinary journey of statistical physics

Christian Beck
2022 EurophysicsNews  
Statistical analysis of data-driven research, complex network topologies, neural networks and modern machine learning algorithms provide a powerful universal language, helping to optimize the real-world  ...  importance of modelling, understanding and tackling climate change (the work of Manabe and Hasselmann), and for the theoretical modelling and understanding of complex systems in general (the work of Parisi  ... 
doi:10.1051/epn/2022103 fatcat:lmohmwefqnhozdafmjzasbo7au

Harvesting Creative Templates for Generating Stylistically Varied Restaurant Reviews [article]

Shereen Oraby, Sheideh Homayon, Marilyn Walker
2017 arXiv   pre-print
Many of the creative and figurative elements that make language exciting are lost in translation in current natural language generation engines.  ...  natural language generator.  ...  , some of # Stars Review 1 1/5 This place is probably the worst thing that ever happened to the history of the known world  ... 
arXiv:1709.05308v1 fatcat:au4tv72i5bccnaevczd6nlufx4

Page 641 of The Journal of Speech and Hearing Disorders Vol. 23, Issue 5 [page]

1958 The Journal of Speech and Hearing Disorders  
tion and recognition, mechanical transla- tion of languages, theory of neural nets, simulation of brain models on digital computers, and techniques of automation to perform such human functions as learning  ...  of countries in all parts of the world.  ... 

Page 3005 of Psychological Abstracts Vol. 89, Issue 8 [page]

2002 Psychological Abstracts  
[from the chapter] — Human languages use an amazing variety of subtly different speech sounds to convey meaning. The author discusses a short history of modeling.  ...  [from the chapter] — Focuses on the simulation of the acquisition and evolution of grounded languages. It gives a definition of symbol based mainly cognitive and neurally-related semiotic factors.  ... 

Predicting Sentiment Polarity of Microblogs using an LSTM – CNN Deep Learning Model

2019 International Journal of Engineering and Advanced Technology  
The encodings produced by the LSTM layer are then fed to a CNN layer, which generates localized patterns of higher accuracy.  ...  The proposed model has a stacked neural network structure consisting of Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN) layers.  ...  While language generation aims at generating natural languages with meaningful features and context by artificial systems.  ... 
doi:10.35940/ijeat.f8933.088619 fatcat:uo5golwcy5dibon5hx53mde6ni

Deep Reinforcement Learning for Conversational AI [article]

Mahipal Jadeja, Neelanshi Varia, Agam Shah
2017 arXiv   pre-print
It is possible to scale deep reinforcement learning with the use of deep learning and do amazing tasks such as use of pixels in playing video games.  ...  Currently, it serves as a good starting point for constructing intelligent autonomous systems which offer a better knowledge of the visual world.  ...  A er around one month of this amazing work, the company DeepMind was bought by Google. A er Google's entry in this eld, there is a lot of buzz about reinforcement learning in the eld of AI.  ... 
arXiv:1709.05067v1 fatcat:ogg6iej4jjdflp2wcvpwxmfegi

Entrevista - George P. Lakoff

Helen de Andrade Abreu
2016 Revista Linguística  
George Lakoff is one of the most widely recognized and celebrated scholars in the field of Cognitive Linguistics in the world today.  ...  The conceptual system is learned before you learn language, but the same kind of neural mechanism works in language and in thought.  ...  sorts of details of language.  ... 
doaj:27e97262b41a4a5184aaaf8572e086d9 fatcat:ac3zeyjsv5goxn557276cesrlm
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