LEADER 00921nam1 22002771i 450 001 SUN0034130 005 20141013112614.74 010 $d0.00 100 $a20050317d1991 |0engc50 ba 101 $aeng 102 $aGB 105 $a|||| ||||| 200 1 $aˆThe ‰sculpture of Jacopo Sansovino$fBruce Boucher 210 $aNew Haven$aLondon$cYale university$d1991 215 $a2 volumi$cill.$d29 cm. 463 \1$1001SUN0034133$12001 $a<>sculpture of Jacopo Sansovino 1 463 \1$1001SUN0034147$12001 $a<>sculpture of Jacopo Sansovino 2 620 $aGB$dLondon$3SUNL000015 620 $aUS$dNew Haven$3SUNL000040 676 $a730.92$cScultura. Persone$v21 700 1$aBoucher$b, Bruce$3SUNV020569$010708 712 $aYale university$3SUNV000131$4650 801 $aIT$bSOL$c20181109$gRICA 912 $aSUN0034130 996 $aSculpture of Jacopo Sansovino$91406289 997 $aUNICAMPANIA LEADER 04622nam 22006975 450 001 9910725929703321 005 20231003183650.0 010 $a9783-031-23190-2$b(electronic book) 024 7 $a10.1007/978-3-031-23190-2 035 $a(CKB)5580000000544268 035 $a(MiAaPQ)EBC30550689 035 $a(Au-PeEL)EBL30550689 035 $a(DE-He213)978-3-031-23190-2 035 $a(PPN)270615679 035 $a(OCoLC)1380847755 035 $a(EXLCZ)995580000000544268 100 $a20230523d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFoundation Models for Natural Language Processing$b[electronic resource] $ePre-trained Language Models Integrating Media /$fby Gerhard Paass, Sven Giesselbach 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (xviii, 448 pages) 225 1 $aArtificial Intelligence: Foundations, Theory, and Algorithms,$x2365-306X 311 0 $a3-031-23189-9 320 $aIncludes bibliographical references and index. 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 $aThis open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI. 410 0$aArtificial intelligence (Berlin, Germany) 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 $a006.35 700 $aPaass$b Gerhard$01427544 702 $aGiesselbach$b Sven 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bOD$ 912 $a9910725929703321 996 $aFoundation Models for Natural Language Processing$93561116 997 $aUNINA