LEADER 00899nam0-22002891i-450- 001 990004919970403321 005 19990530 010 $a3-500-27070-0 035 $a000491997 035 $aFED01000491997 035 $a(Aleph)000491997FED01 035 $a000491997 100 $a19990530g19739999km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aLeisewitzens Julius von Tarent$fErläuterung und literar-historische Wnrdigung von Walther Knhlhorn 210 $aWiesbaden$cM. SSndig oHG$d1973. 215 $aXV, 84 p.$d22 cm 225 1 $aBausteine zur Geschichte der neueren deutschen Literatur$v10 700 1$aKuhlhorn,$bWalther$0197253 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004919970403321 952 $aALPHA 4533 (90)$bFil. Mod. 35682$fFLFBC 959 $aFLFBC 996 $aLeisewitzens Julius von Tarent$9523148 997 $aUNINA LEADER 04499nam 22006615 450 001 9910847154703321 005 20251008153435.0 010 $a9783031231902 010 $a3031231902 024 7 $a10.1007/978-3-031-23190-2 035 $a(CKB)31377991100041 035 $a(ODN)ODN0010068911 035 $a(DE-He213)978-3-031-23190-2 035 $a(EXLCZ)9931377991100041 100 $a20230523d2023 u| 0 101 0 $aeng 135 $aurcn|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFoundation Models for Natural Language Processing $ePre-trained Language Models Integrating Media /$fby Gerhard Paaß, Sven Giesselbach 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource 225 1 $aArtificial Intelligence: Foundations, Theory, and Algorithms,$x2365-306X 311 08$a9783031231896 311 08$a3031231899 327 $a1. Introduction -- 2. Pre-trained Language Models -- 3. Improving Pre-trained Language Models -- 4. Knowledge Acquired by Foundation Models -- 5. Foundation Models for Information Extraction -- 6. Foundation Models for Text Generation -- 7. Foundation Models for Speech, Images, Videos, and Control -- 8. Summary and Outlook. 330 $aThis open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction tobasic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI. 410 0$aArtificial Intelligence: Foundations, Theory, and Algorithms,$x2365-306X 606 $aNatural language processing (Computer science) 606 $aComputational linguistics 606 $aArtificial intelligence 606 $aExpert systems (Computer science) 606 $aMachine learning 606 $aNatural Language Processing (NLP) 606 $aComputational Linguistics 606 $aArtificial Intelligence 606 $aKnowledge Based Systems 606 $aMachine Learning 615 0$aNatural language processing (Computer science) 615 0$aComputational linguistics. 615 0$aArtificial intelligence. 615 0$aExpert systems (Computer science) 615 0$aMachine learning. 615 14$aNatural Language Processing (NLP). 615 24$aComputational Linguistics. 615 24$aArtificial Intelligence. 615 24$aKnowledge Based Systems. 615 24$aMachine Learning. 676 $a006.35 686 $aCOM004000$aCOM025000$aCOM073000$aLAN009000$2bisacsh 700 $aPaaß$b Gerhard$01830675 701 $aGiesselbach$b Sven$01736135 906 $aBOOK 912 $a9910847154703321 996 $aFoundation models for natural language processing$94401165 997 $aUNINA