LEADER 04759 am 2201033 n 450 001 9910495696103321 005 20200131 010 $a979-1-03-000622-3 024 7 $a10.4000/books.pub.15008 035 $a(CKB)4100000011289042 035 $a(FrMaCLE)OB-pub-15008 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/86102 035 $a(PPN)248497928 035 $a(EXLCZ)994100000011289042 100 $a20200608j|||||||| ||| 0 101 0 $afre 135 $auu||||||m|||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aL?imaginaire du sacré /$fAgnés Lhermitte, Élisabeth Magne 210 $aPessac $cPresses Universitaires de Bordeaux$d2020 215 $a1 online resource (186 p.) 225 1 $aEidôlon 311 $a979-1-0910-5220-7 330 $a« On ne connaît pas de société organisée qui n?ait sa zone de sacralité », répète Régis Debray. Cette sacralité imprègne notre interprétation du monde en s?accrochant à tel ou tel domaine, migrant du religieux au politique ou à l?esthétique (et vice versa parfois), magnifiant tour à tour une valeur ou une autre, se concrétisant dans des rituels ou dans leur transgression, se traduisant par des manifestations collectives ou par une ascèse intérieure. Le sacré, dans sa dimension anthropologique la plus large comme dans ses formes culturelles particulières, alimente l?imaginaire de toute société et, comme tel, constitue un ferment de l?expression artistique et littéraire. Les textes ici réunis font dialoguer des ?uvres poétiques et romanesques, théâtrales, iconiques et plastiques, tirées des cultures arabe et européenne, de façon à questionner en résonance leurs interprétations du sacré et les formes qu?elles lui donnent. Où l?on voit que les écrits sacrés (la Bible et ses prolongements chrétiens et islamiques, mais aussi les mythes de la Grèce antique) continuent à inspirer mises en récits et mises en scène qui les transforment et les revivifient à l?infini. Que la quête poétique, recherche verbale et activité symbolique, reste s?ur des aspirations mystiques intimes et/ou cosmiques. Que la figuration iconique et plastique, en particulier celle du corps humain, garde trace d?une transcendance liée à la conscience de sa finitude. Que l?activité théâtrale n?a rompu ni avec ses racines dionysiaques ni avec ses origines funéraires. Que cette production imaginante est toujours accompagnée de discours réflexifs qui la relativisent et la balisent, dénonçant les dérives possibles (ou tristement actualisées) et maintenant le cap d?une compréhension tolérante, plus que jamais indispensable. 606 $aArt 606 $aReligion 606 $aLiterature (General) 606 $aart 606 $aimaginaire 606 $areligion 606 $alittérature 606 $areprésentation 606 $aMaghreb 606 $aimage 606 $asociété 606 $asacré 606 $afemme 610 $aart 610 $aimaginaire 610 $areligion 610 $alittérature 610 $areprésentation 610 $aMaghreb 610 $aimage 610 $asociété 610 $asacré 610 $afemme 615 4$aArt 615 4$aReligion 615 4$aLiterature (General) 615 4$aart 615 4$aimaginaire 615 4$areligion 615 4$alittérature 615 4$areprésentation 615 4$aMaghreb 615 4$aimage 615 4$asociété 615 4$asacré 615 4$afemme 700 $aAbassi$b Ali$01321561 701 $aAbd-elrazak$b Loula$01321562 701 $aAufort$b Frédérique$01321563 701 $aAzémard$b Ghislaine$01321564 701 $aBen Damir$b Amina$01321565 701 $aBie$b Zhi$01321566 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International Conference, AI-HCI 2024, Held As Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29-July 4, 2024, Proceedings, Part III 205 $a1st ed. 210 1$aCham :$cSpringer,$d2024. 210 4$d©2024. 215 $a1 online resource (498 pages) 225 1 $aLecture Notes in Computer Science Series ;$vv.14736 311 $a3-031-60614-0 327 $aIntro -- Foreword -- HCI International 2024 Thematic Areas and Affiliated Conferences -- List of Conference Proceedings Volumes Appearing Before the Conference -- Preface -- 5th International Conference on Artificial Intelligence in HCI (AI-HCI 2024) -- HCI International 2025 Conference -- Contents - Part III -- Large Language Models for Enhanced Interaction -- Enhancing Relation Extraction from Biomedical Texts by Large Language Models -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Relation Extraction via In-Context Few-Shot Learning with LLMs -- 3.2 Seq2seq-Based Relation Extraction Enhanced by LLMs -- 3.3 Classification-Based Relation Extraction Enhanced by LLMs -- 4 Experimental Settings -- 4.1 DDI Extraction Task Settings -- 4.2 LLMs and Prompts -- 4.3 PLMs for Seq2seq Methods -- 4.4 PLMs for Classification Methods -- 5 Results and Discussions -- 5.1 In-Context Few-Shot Learning-Based Relation Extraction by LLMs -- 5.2 Seq2seq-Based Relation Extraction Enhanced by LLMs -- 5.3 Classification-Based Relation Extraction Enhanced by LLMs -- 6 Conclusion -- References -- Using a LLM-Based Conversational Agent in the Social Robot Mini -- 1 Introduction -- 2 A Short History of Language Models -- 3 The Proposed System -- 3.1 Prompting -- 4 Integration into Mini -- 4.1 Design of the Conversational Agent Skill -- 5 Evaluation -- 6 Conclusions -- References -- A Proposal to Extend the Modeling Language for Interaction as Conversation for the Design of Conversational Agents -- 1 Introduction -- 2 Related Work -- 2.1 Conversational Agents -- 2.2 Modeling Interaction in Conversational Agents -- 3 MoLIC -- 4 MoLIC's Limitation to Represent Conversational Agents -- 4.1 Standardized Communication Snippets -- 4.2 Transfer of Responsibility / Interlocutor During Communication -- 4.3 Modeling Breakdown Recovery -- 4.4 Conversational Agents' Intelligence. 327 $a5 Extending MoLIC -- 5.1 Template Element -- 5.2 Allowing for the Interaction with a Third-Party System -- 5.3 Adaptations to MoLIC 2.0 Elements -- 6 Initial Evaluation of Proposal -- 7 Final Remarks and Future Works -- References -- Optimizing Conversational Commerce Involving Multilingual Consumers Through Large Language Models' Natural Language Understanding Abilities -- 1 Introduction -- 1.1 Objectives and Research Questions -- 2 Review of Related Literature -- 3 Method and Implementation -- 3.1 Technical Architecture -- 3.2 Knowledge Base -- 3.3 Synthetic Customer Data Preparation -- 3.4 Synthetic Seller Persona Creation -- 3.5 Synthetic Sales Conversation Creation -- 4 Results -- 4.1 General Applied CoT Approach -- 4.2 Presence of Necessary Conditions -- 4.3 Product Resolution -- 4.4 Database Insertions -- 4.5 Sample Case -- 4.6 Drawbacks and Limitations -- 5 Discussions -- 6 Conclusion and Future Work -- References -- A Map of Exploring Human Interaction Patterns with LLM: Insights into Collaboration and Creativity -- 1 Introduction -- 2 Related Work -- 2.1 The Undergoing Change in HAII Driven by Large Language Model -- 2.2 The Current Review of Human-AI Interaction -- 3 Method -- 3.1 Search and Selection -- 3.2 Mapping -- 4 Result -- 4.1 Processing Tool -- 4.2 Analysis Assistant -- 4.3 Creative Companion -- 4.4 Processing Agent -- 5 Discussion -- 5.1 Mapping Methodology Based on Human and Algorithmic Approaches -- 5.2 Differences Between Clusters -- 5.3 About the Vacancy in the Mapping -- 5.4 Future Directions -- 6 Limitation and Future Work -- 7 Conclusion -- References -- The Use of Large Language Model in Code Review Automation: An Examination of Enforcing SOLID Principles -- 1 Introduction -- 2 Background -- 2.1 Code Reviews -- 2.2 SOLID Principles -- 2.3 Large Language Model Technology -- 2.4 Mixtral LLM. 327 $a2.5 Role of Bots in Code Development and Review -- 2.6 Benefits for Large Global Development Teams -- 3 Related Works -- 3.1 A Systematic Evaluation of Large Language Models of Code -- 3.2 Effects of Adopting Code Review Bots on Pull Requests to OSS Projects -- 3.3 Reducing Human Effort and Improving Quality in Peer Code Reviews Using Automatic Static Analysis and Reviewer Recommendation -- 3.4 ChatGPT: A Study of Its Utility for Common Software Engineering Tasks -- 3.5 Insights and Implications for LLM-Based Code Review -- 4 Proposed Concept -- 4.1 Proposed Architecture and Integration -- 4.2 Usage of the Proposed Bot -- 5 Impact Analysis -- 5.1 Comparison with Existing Solutions -- 5.2 Potential Benefits -- 5.3 Challenges and Limitations -- 6 Conclusion -- References -- LLM Based Multi-agent Generation of Semi-structured Documents from Semantic Templates in the Public Administration Domain -- 1 Introduction -- 2 Related Work -- 2.1 LLMs in the PA Domain -- 3 Proposed Approach -- 3.1 Template Pre-processing -- 3.2 Multi-agent Interaction -- 3.3 Document Post-processing -- 4 Experimental Evaluation -- 4.1 Semantics Identification Agent -- 4.2 Information Retrieval Agent -- 4.3 Content Generation Agent -- 4.4 Prompt-Engineered Results -- 5 Conclusions -- References -- Enabling Human-Centered Machine Translation Using Concept-Based Large Language Model Prompting and Translation Memory -- 1 Introduction -- 1.1 Challenges in Traditional Machine Translation Within Human-Computer Interaction Contexts -- 1.2 Augmented Machine Translation via Large Language Model -- 2 Augmented Machine Translation via Concept-Driven Large Language Model Prompting -- 2.1 Motivation -- 2.2 Augmented Instruction for Discourse-Level Style -- 2.3 Augmented Instruction for Concept-Based Sentence-Level Post-editing -- 2.4 Performance Evaluation. 327 $a3 Assessing the Proficiency of Large Language Model in Applying Translation Concept -- 3.1 Motivation -- 3.2 The Capability of LLMs to Elucidate Translation Concepts -- 3.3 Assessing the LLM's Proficiency in Identifying When to Apply Translation Concepts -- 3.4 The Capability of LLM to Produce Target Translations that Reflect Relevant Concepts -- 4 Conclusions -- References -- Enhancing Large Language Models Through External Domain Knowledge -- 1 Introduction -- 2 Problem Identification and Objectives -- 3 Related Works -- 4 Design and Development of the Artifact -- 4.1 Expert Knowledge Acquisition -- 4.2 Metadata Provision -- 4.3 Prompt Generation -- 5 Demonstration -- 5.1 Implementation -- 5.2 Case Study -- 6 Discussion -- References -- ChatGPT and Language Translation -- 1 Introduction -- 1.1 Historical Background - PreGPT -- 1.2 Background - LLMs and ChatGPT -- 1.3 ChatGPT and Translation -- 2 Motivation and Methodology for This Study -- 2.1 Motivation -- 2.2 Methodology -- 2.3 Examples -- 3 Results -- 3.1 Classifying AI Generated Text -- 3.2 Human Ratings of Translation Quality -- 4 Conclusions -- References -- Large Language Models for Tracking Reliability of Information Sources -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- The Heuristic Design Innovation Approach for Data-Integrated Large Language Model -- 1 Introduction -- 2 Related Works -- 2.1 Domain-Specific LLMs -- 2.2 Expert System -- 2.3 Human-AI Collaboration Design -- 3 Method -- 3.1 Overview of DIABot -- 3.2 Prompt -- 3.3 Database -- 3.4 Workflow -- 4 Value Assessment -- 4.1 Experimental Design -- 4.2 Participants -- 4.3 Experimental Process -- 4.4 Experimental Result -- 5 Discussion and Conclusion -- 6 Limitation and Future Work -- A Prompt of DIAbot -- B Tools OpenAPI -- References -- Advancing Human-Robot Interaction Through AI. 327 $aFER-Pep: A Deep Learning Based Facial Emotion Recognition Framework for Humanoid Robot Pepper -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Pepper -- 3.2 NAOqi Python API -- 3.3 EfficientNetV2 -- 4 Dataset Collection and Preprocessing -- 5 Experiments -- 5.1 Candidate Models for Facial Emotion Recognition -- 6 System Implementation -- 7 Result and Discussion -- 8 Conclusion -- References -- You Got the Feeling: Attributing Affective States to Dialogical Social Robots -- 1 Introduction -- 2 Empathy and Emotions Theories -- 3 The Experiment -- 3.1 Method and Interaction Steps in the Dialogues -- 4 Evaluation -- 5 Results and Future Works -- References -- Enhancing Usability of Voice Interfaces for Socially Assistive Robots Through Deep Learning: A German Case Study -- 1 Introduction -- 2 Related Work -- 2.1 Voice Interface Evaluations -- 2.2 Technical Construction of Voice Interfaces -- 3 Voice Interface -- 3.1 Design Goals -- 3.2 System Description -- 4 Evaluation -- 4.1 Methods and Material -- 4.2 Participants -- 4.3 Results -- 4.4 Discussion -- 5 Limitations -- 6 Conclusion -- References -- Enhancing User Experience: Designing Intuitive Interfaces for Sumo Robot Operations -- 1 Introduction -- 1.1 Intuitive Interface -- 1.2 Robotics -- 1.3 Sumo Robots -- 1.4 Designing Intuitive Interfaces for Sumo Robot Operations -- 2 Methodology -- 3 Result -- 3.1 Sumo Robot Performance -- 3.2 User Feedback -- 4 Discussion -- 4.1 Interpretation of Results -- 4.2 Comparison with Existing System -- 4.3 Implications and Future Works -- References -- Adaptive Robotics: Integrating Robotic Simulation, AI, Image Analysis, and Cloud-Based Digital Twin Simulation for Dynamic Task Completion -- 1 Introduction -- 1.1 Autonomous Robots -- 1.2 Robotics Simulation -- 1.3 AI in Robotics -- 1.4 Internet of Things -- 1.5 Isaac Simulation -- 1.6 Skydio and Sundt. 327 $a2 Theoretical Framework and Research Objectives. 410 0$aLecture Notes in Computer Science Series 700 $aDegen$b Helmut$01372743 701 $aNtoa$b Stavroula$01372617 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996601562303316 996 $aArtificial Intelligence 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