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Deep Learning for Conversational AI

Pei-Hao Su, Nikola Mrkšić, Iñigo Casanueva, Ivan Vulić
<span title="">2018</span> <i title="Association for Computational Linguistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/d5ex6ucxtrfz3clshlkh3f6w2q" style="color: black;">Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts</a> </i> &nbsp;
Objectives Spoken Dialogue Systems (SDS) have great commercial potential as they promise to revolutionise the way in which humans interact with machines.  ...  The advent of deep learning led to substantial developments in this area of NLP research, and the goal of this tutorial is to familiarise the research community with the recent advances in what some call  ...  Next, we will frame the response generation task in a broader context by treating end-to-end dialogue modelling as a conditional response generation task.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/n18-6006">doi:10.18653/v1/n18-6006</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/naacl/SuMCV18.html">dblp:conf/naacl/SuMCV18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2psamruxrbbv7pnqfpxi2tnfjy">fatcat:2psamruxrbbv7pnqfpxi2tnfjy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200309062355/https://www.aclweb.org/anthology/N18-6006.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8c/f9/8cf9c6bccccde9283f4089f7fe99fb1fa2c2df9a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/n18-6006"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

TOWARDS USER-CENTRIC EXPLANATIONS FOR EXPLAINABLE MODELS: A REVIEW

Ali Hassan, Riza Sulaiman, Mansoor Abdullateef Abdulgabber, Hasan Kahtan
<span title="2021-09-01">2021</span> <i title="Global Academic Excellence (M) Sdn Bhd"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ecqyrbekjnbctmqsqzyztot7uq" style="color: black;">Journal of Information System and Technology Management</a> </i> &nbsp;
Recent advances in artificial intelligence, particularly in the field of machine learning (ML), have shown that these models can be incredibly successful, producing encouraging results and leading to diverse  ...  The study found that one of the most difficult aspects of implementing machine learning models is gaining the trust of end-users.  ...  Explainability in AI is one of the most important requirements for implementing responsible AI due to several factors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35631/jistm.622004">doi:10.35631/jistm.622004</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pr3kztar4nbklc4x6evjyriqwq">fatcat:pr3kztar4nbklc4x6evjyriqwq</a> </span>
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The Rise of AI-Driven Simulators: Building a New Crystal Ball [article]

Ian Foster, David Parkes, Stephan Zheng
<span title="2020-12-11">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
simulators combine machine-learned and mathematical rules to make accurate and actionable predictions.  ...  The past decade has brought remarkable advances in complementary areas: in sensors, which can now capture enormous amounts of data about the world, and in AI methods capable of learning to extract predictive  ...  Deep learning is also increasingly used to provide end-to-end models, and replace numerical computation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.06049v1">arXiv:2012.06049v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/su5pxwiim5aszfij55lylk3vxa">fatcat:su5pxwiim5aszfij55lylk3vxa</a> </span>
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AI Back-End as a Service for Learning Switching of Mobile Apps between the Fog and the Cloud [article]

Dionysis Athanasopoulos, Dewei Liu
<span title="2021-10-02">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To answer this, we contribute an AI approach that trains machine-learning models of the response time of service instances.  ...  The Fog has been introduced to augment the apps with machines located at the network edge close to the end-users. However, edge machines are usually resource constrained.  ...  To address this challenge, we contribute an artificial intelligence (AI) approach that takes any independent variable as input and constructs machine-learning models that capture the response time of service  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2110.00836v1">arXiv:2110.00836v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lq7qwzcjknfj3ptw3y7mhp777m">fatcat:lq7qwzcjknfj3ptw3y7mhp777m</a> </span>
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Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

Guy Barash, Mauricio Castillo-Effen, Niyati Chhaya, Peter Clark, Huáscar Espinoza, Eitan Farchi, Christopher Geib, Odd Erik Gundersen, Seán HÉigeartaigh, José Hernández-Orallo, Chiori Hori, Xiaowei Huang (+25 others)
<span title="2019-09-30">2019</span> <i title="Association for the Advancement of Artificial Intelligence (AAAI)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/27wksbinzzhjfow2wuy6m2iefm" style="color: black;">The AI Magazine</a> </i> &nbsp;
Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI.  ...  Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction  ...  The challenge consists of three tracks: noetic endto-end response selection, end-to-end conversation modeling, and audiovisual scene-aware dialogue.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1609/aimag.v40i3.4981">doi:10.1609/aimag.v40i3.4981</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tigkbqqkbjd4rcqew4dtallcze">fatcat:tigkbqqkbjd4rcqew4dtallcze</a> </span>
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Neural Approaches to Conversational AI

Jianfeng Gao, Michel Galley, Lihong Li
<span title="">2018</span> <i title="Association for Computational Linguistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5n6volmnonf5tn6xputi5f2t3e" style="color: black;">Proceedings of ACL 2018, Tutorial Abstracts</a> </i> &nbsp;
This tutorial surveys neural approaches to conversational AI that were developed in the last few years.  ...  each category, we present a review of state-of-the-art neural approaches, draw the connection between neural approaches and traditional symbolic approaches, and discuss the progress we have made and challenges  ...  breakthroughs in deep learning (DL) and reinforcement learning (RL) are applied to conversational AI.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/p18-5002">doi:10.18653/v1/p18-5002</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/acl/GaoGL18.html">dblp:conf/acl/GaoGL18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7llxwuntafh4fcjj4ia3tm642a">fatcat:7llxwuntafh4fcjj4ia3tm642a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200508020119/https://www.aclweb.org/anthology/P18-5002.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9e/b7/9eb7e1a767d4eb210fd649bb510d49e556136b60.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/p18-5002"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Artificial Intelligence and its Impact on the Fourth Industrial Revolution: A Review

Gissel Velarde
<span title="2019-11-30">2019</span> <i title="Academy and Industry Research Collaboration Center (AIRCC)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dlcgzkn4cvbevhkswphjjxglsa" style="color: black;">International Journal of Artificial Intelligence &amp; Applications</a> </i> &nbsp;
This paper reviews the development and trends in AI, as well as the benefits, risks, and strategies in the field.  ...  due to its speed and scope.  ...  The trend is to avoid feature engineering and use end-to-end deep learning to extract relevant features directly from the rough data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5121/ijaia.2019.10604">doi:10.5121/ijaia.2019.10604</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hvuxcgxtwnaebankyqzofgwu4q">fatcat:hvuxcgxtwnaebankyqzofgwu4q</a> </span>
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Artificial Intelligence and its impact on the Fourth Industrial Revolution: A Review [article]

Gissel Velarde
<span title="2020-11-05">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reviews the development and trends in AI, as well as the benefits, risks, and strategies in the field.  ...  due to its speed and scope.  ...  The trend is to avoid feature engineering and use end-to-end deep learning to extract relevant features directly from the rough data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.03044v1">arXiv:2011.03044v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mfwqfcoxlfh6fhmzapcqqcxa6y">fatcat:mfwqfcoxlfh6fhmzapcqqcxa6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201110001821/https://arxiv.org/ftp/arxiv/papers/2011/2011.03044.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d1/aa/d1aa2275bf176f2541e897aa8a5ce83da4551186.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.03044v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

IoT , Fog Computing with AI Possibility

Dhananjay Yadav
<span title="2019-06-30">2019</span> <i title="International Journal for Research in Applied Science and Engineering Technology (IJRASET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hsp44774azcezeyiq4kuzpfh5a" style="color: black;">International Journal for Research in Applied Science and Engineering Technology</a> </i> &nbsp;
During the development of technology, we are facing many challenges and responsibility of better solution driven architecture for internet of things.  ...  Now we are generalizing and filter best solution available in IOT fog scenario using AI.  ...  plates for parking payments to be more accurate when I say AI,really mean machine learning.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2019.6306">doi:10.22214/ijraset.2019.6306</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yzh4xq4aibdwllbtiun5oyi6ai">fatcat:yzh4xq4aibdwllbtiun5oyi6ai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200207232018/http://ijraset.com/fileserve.php?FID=24196" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/33/4f/334f3eba356274172c7b67e0115f26a22ea9e250.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2019.6306"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

The 6-Ds of Creating AI-Enabled Systems [article]

John Piorkowski
<span title="2022-02-04">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
AI winters occurred because of ineffective approaches towards navigating the technology valley of death. The 6-D framework provides an end-to-end framework to successfully navigate this challenge.  ...  The 6-D framework starts with problem decomposition to identify potential AI solutions, and ends with considerations for deployment of AI-enabled systems.  ...  This paper describes an end-to-end framework for creating an AI-enabled system. The concept of the 6-D framework is an extension of Neil Lawrence's paper on the 3-Ds of machine learning.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2202.03172v1">arXiv:2202.03172v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5vm7lfoekresjasyt7v5wy5nl4">fatcat:5vm7lfoekresjasyt7v5wy5nl4</a> </span>
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A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records [article]

Parthasarathy Suryanarayanan, Bhavani Iyer, Prithwish Chakraborty, Bibo Hao, Italo Buleje, Piyush Madan, James Codella, Antonio Foncubierta, Divya Pathak, Sarah Miller, Amol Rajmane, Shannon Harrer (+2 others)
<span title="2021-01-05">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we propose a novel canonical architecture for the development of AI models in healthcare that addresses these challenges.  ...  Many institutions within the healthcare ecosystem are making significant investments in AI technologies to optimize their business operations at lower cost with improved patient outcomes.  ...  While these challenges are present in other domains, addressing their aggregation is imperative to stand up production AI systems in healthcare.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2007.12780v2">arXiv:2007.12780v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/i2kfs54uxbgz3dm4jtm5vtg5aa">fatcat:i2kfs54uxbgz3dm4jtm5vtg5aa</a> </span>
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Artificial Intelligence at the Edge [article]

Elisa Bertino, Sujata Banerjee
<span title="2020-12-10">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
At the same time, there have been recent technological breakthroughs in highly relevant fields such as artificial intelligence (AI)/machine learning (ML), advanced communication systems (5G and beyond)  ...  Many of these applications require computations and analytics close to application end-points: that is, at the edge of the network, rather than in a centralized cloud.  ...  Many privacy techniques for data analytics and machine learning have been proposed over the years.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.05410v1">arXiv:2012.05410v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/afwtgeedcradvb326ubimek5w4">fatcat:afwtgeedcradvb326ubimek5w4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201212015504/https://arxiv.org/ftp/arxiv/papers/2012/2012.05410.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ed/f5/edf57bbeea2d13b987792cff9878f25e1e8bcc5c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2012.05410v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Viewpoint: Human-in-the-loop Artificial Intelligence

Fabio Massimo Zanzotto
<span title="2019-02-10">2019</span> <i title="AI Access Foundation"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4ax4efcwajcgvidb6hcg6mwx4a" style="color: black;">The Journal of Artificial Intelligence Research</a> </i> &nbsp;
Many learning AI machines are extracting knowledge from unaware skilled or unskilled workers by analyzing their interactions.  ...  In this paper, we propose Human-in-the-loop Artificial Intelligence (HitAI) as a fairer paradigm for AI systems.  ...  In autonomous learning, machines are asked to learn from experience.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1613/jair.1.11345">doi:10.1613/jair.1.11345</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3xcbvsvqhnefnpbcbioubtrvsu">fatcat:3xcbvsvqhnefnpbcbioubtrvsu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190430141601/https://art.torvergata.it/retrieve/handle/2108/210238/413540/HitAI_jair_final_version_final_check.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8c/22/8c22f36f1b5804e3a08a8640035791e6db3e0771.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1613/jair.1.11345"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Shaping the Next Generation Pharmaceutical Supply Chain Control Tower with Autonomous Intelligence

Matthew Liotine
<span title="2019-05-16">2019</span> <i title="Frontier Scientific Publishing Pte Ltd"> Journal of Autonomous Intelligence </i> &nbsp;
This paper summarizes the findings of an industry panel study evaluating how new Autonomous Intelligence technologies, such as artificial intelligence and machine learning, impact the system and operational  ...  Such technologies can shift CTs to a model in which real-time information gathering, analysis, and decision making are possible.  ...  To this end, it would be desirable to know those supply chain functions that would be best applicable for AI or machine learning and the mechanisms that could be used to validate AI driven decisions in  ... 
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Editorial: Special Issue on the Eighth Dialog System Technology Challenge

Seokhwan Kim, Hannes Schulz, Chulaka Gunasekara, Chiori Hori, Abhinav Rastogi, Luis D'Haro
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rut5unc4enborm7fhpkwgeza7m" style="color: black;">IEEE/ACM Transactions on Audio Speech and Language Processing</a> </i> &nbsp;
In line with recent editions of this challenge, DSTC8 focuses on applying end-to-end technologies to Dialog Systems in a pragmatic way.  ...  This collection of articles covers a broad range of dialog research problems including end-to-end response selection/generation, conversational representation learning, few-shot domain adaptation, robust  ... 
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