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Resolving the Human-subjects Status of Machine Learning's Crowdworkers

Resolving the Human-subjects Status of Machine Learning's Crowdworkers
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United States , City Of , United Kingdom , Sina Fazelpour , Youakim Badr , Divyansh Kaushik , Alvaro Videla , Holly Fernandez Lynch , I Glenn Cohen , Edlynv Levine , Raghvinders Sangwan , Satishm Srinivasan , Zacharyc Lipton , Federation Of American Scientists , Birmingham Southern College , Meta Research , Loyola University , Kl Gates Initiative In Ethics , Us Department Of Health , International Joint Conference On Natural Language Processing , Amazon Research , Ethics Human Research , Carnegie Mellon University Block Center , Oxford University , Oxford University Press , Whittier College ,

Human-like systematic generalization through a meta-learning neural network

The power of human language and thought arises from systematic compositionality—the algebraic ability to understand and produce novel combinations from known components. Fodor and Pylyshyn1 famously argued that artificial neural networks lack this capacity and are therefore not viable models of the mind. Neural networks have advanced considerably in the years since, yet the systematicity challenge persists. Here we successfully address Fodor and Pylyshyn’s challenge by providing evidence that neural networks can achieve human-like systematicity when optimized for their compositional skills. To do so, we introduce the meta-learning for compositionality (MLC) approach for guiding training through a dynamic stream of compositional tasks. To compare humans and machines, we conducted human behavioural experiments using an instruction learning paradigm. After considering seven different models, we found that, in contrast to perfectly systematic but rigid probabilistic sy ....

Conference Of The Cognitive Science Society , International Conference On Learning Representations , International Joint Conference On Natural Language Processing , Curran Associates , International Conference On Computational Linguistics , Proc International Conference On Machine Learning , Meeting Of The Association For Computational Linguistics , Cognitive Science Society , Association For Computational Linguistics , Meeting Of The Cognitive Science Society , International Conference On Machine Learning , Algebraic Mind , Integrating Connectionism , Cognitive Science , Rethinking Fodor , Systematicity Challenge , International Conference , Learning Representations , Proc International Conference , Machine Learning , Computational Linguistics , Visually Grounded Interaction , Empirical Methods , Natural Language Processing , Neural Information Processing Systems , Thirty Second Annual Conference ,

GitHub - adbar/trafilatura: Python & command-line tool to gather text on the Web: web crawling/scraping, extraction of text, metadata, comments

Python & command-line tool to gather text on the Web: web crawling/scraping, extraction of text, metadata, comments - GitHub - adbar/trafilatura: Python & command-line tool to gather text on the Web: web crawling/scraping, extraction of text, metadata, comments ....

Lejeune Adrien Barbaresi , International Joint Conference On Natural Language Processing , Meeting Of The Association For Computational Linguistics , A Web Scraping Library , Association For Computational Linguistics , Adrien Barbaresi , Public License , Web Scraping Library , Command Line Tool , Text Discovery , Joint Conference , Annual Meeting , Computational Linguistics , International Joint Conference , Natural Language Processing ,

Honeypot security technique can also stop attacks in natural language processing

Honeypot security technique can also stop attacks in natural language processing
Borrowing a technique commonly used in cybersecurity to defend against these universal trigger-based attacks, researchers at the Penn State College of Information Sciences and Technology have developed a machine learning framework that can proactively defend against the same types of attacks in natural language processing applications 99% of the time.
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Honeypot security technique can also stop attacks in natural language processing
Jessica Hallman
July 28, 2021
UNIVERSITY PARK, Pa. As online fake news detectors and spam filters become more sophisticated, so do attackers’ methods to trick them including attacks through the “universal trigger.” In this learning-based method, an attacker uses a phrase or set of words to fool an indefinite number of inputs. A successful attack could mean more fake news appearing in your social media feed or spam reaching ....

Dongwon Lee , International Joint Conference On Natural Language Processing , Penn State College Of Information Sciences , Yonsei University , Meeting Of The Association For Computational Linguistics , National Science Foundation , Penn State College , Information Sciences , Noseong Park , Joint Conference , Annual Meeting , Computational Linguistics , International Joint Conference , Natural Language Processing , National Science , சர்வதேச கூட்டு மாநாடு ஆன் இயற்கை மொழி ப்ரோஸெஸிஂக் , பென் நிலை கல்லூரி ஆஃப் தகவல் அறிவியல் , சந்தித்தல் ஆஃப் தி சங்கம் க்கு கணக்கீட்டு மொழியியல் , தேசிய அறிவியல் அடித்தளம் , பென் நிலை கல்லூரி , தகவல் அறிவியல் , கூட்டு மாநாடு , ஆண்டு சந்தித்தல் , கணக்கீட்டு மொழியியல் , சர்வதேச கூட்டு மாநாடு , இயற்கை மொழி ப்ரோஸெஸிஂக் ,