Search (35 results, page 1 of 2)

  • × theme_ss:"Computerlinguistik"
  • × type_ss:"a"
  • × year_i:[2020 TO 2030}
  1. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.06
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    Language
    e
    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  2. Morris, V.: Automated language identification of bibliographic resources (2020) 0.03
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    Date
    2. 3.2020 19:04:22
    Language
    e
  3. ¬Der Student aus dem Computer (2023) 0.02
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    Date
    27. 1.2023 16:22:55
  4. Bager, J.: ¬Die Text-KI ChatGPT schreibt Fachtexte, Prosa, Gedichte und Programmcode (2023) 0.01
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    Date
    29.12.2022 18:22:55
  5. Rieger, F.: Lügende Computer (2023) 0.01
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    Date
    16. 3.2023 19:22:55
  6. Roose, K.: ¬The brilliance and weirdness of ChatGPT (2022) 0.00
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  7. Metz, C.: ¬The new chatbots could change the world : can you trust them? (2022) 0.00
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  8. Harari, Y.N.: ¬[Yuval-Noah-Harari-argues-that] AI has hacked the operating system of human civilisation (2023) 0.00
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  9. Zaitseva, E.M.: Developing linguistic tools of thematic search in library information systems (2023) 0.00
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    Abstract
    Within the R&D program "Information support of research by scientists and specialists on the basis of RNPLS&T Open Archive - the system of scientific knowledge aggregation", the RNPLS&T analyzes the use of linguistic tools of thematic search in the modern library information systems and the prospects for their development. The author defines the key common characteristics of e-catalogs of the largest Russian libraries revealed at the first stage of the analysis. Based on the specified common characteristics and detailed comparison analysis, the author outlines and substantiates the vectors for enhancing search inter faces of e-catalogs. The focus is made on linguistic tools of thematic search in library information systems; the key vectors are suggested: use of thematic search at different search levels with the clear-cut level differentiation; use of combined functionality within thematic search system; implementation of classification search in all e-catalogs; hierarchical representation of classifications; use of the matching systems for classification information retrieval languages, and in the long term classification and verbal information retrieval languages, and various verbal information retrieval languages. The author formulates practical recommendations to improve thematic search in library information systems.
    Language
    e
  10. Collard, J.; Paiva, V. de; Fong, B.; Subrahmanian, E.: Extracting mathematical concepts from text (2022) 0.00
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  11. Szöke, D.: ChatGPT : wie Sie die KI ausprobieren können (2022) 0.00
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    Content
    ChatGPT ist ein KI-Chatbot, der menschliche Texteingaben verstehen und möglichst natürlich antworten soll - und für ziemlich viel Begeisterung im Netz sorgt. Jeder kann mit der "künstlichen Intelligenz" einen Dialog führen oder sie um passenden Code oder ein paar launig klingende Gedichtzeilen bitten. Ausprobieren können Sie das kostenlos - wir zeigen Ihnen, wie das geht. Account einrichten ChatGPT wird auf der OpenAI-Website angeboten - allerdings nur für registrierte Nutzer. Um einen OpenAI-Account zu erstellen, muss man eine E-Mail-Adresse und eine Handynummer angeben, gegebenenfalls müssen Sie noch ein Captcha lösen. Die E-Mail-Adresse noreply@tm.openai.com sendet einen Verifizierungslink, welcher Sie zurück zur Website und zum nächsten Schritt führt. Nach der Auswahl des Benutzernamens müssen Sie nur noch den Nutzungsbedingungen zustimmen und eine Verifizierung über die Handynummer vornehmen. Letztere passiert über das Zusenden eines sechsstelligen Bestätigungs-Codes.
  12. Xiang, R.; Chersoni, E.; Lu, Q.; Huang, C.-R.; Li, W.; Long, Y.: Lexical data augmentation for sentiment analysis (2021) 0.00
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    Language
    e
  13. Laparra, E.; Binford-Walsh, A.; Emerson, K.; Miller, M.L.; López-Hoffman, L.; Currim, F.; Bethard, S.: Addressing structural hurdles for metadata extraction from environmental impact statements (2023) 0.00
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  14. Al-Khatib, K.; Ghosa, T.; Hou, Y.; Waard, A. de; Freitag, D.: Argument mining for scholarly document processing : taking stock and looking ahead (2021) 0.00
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  15. Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.00
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  16. Schönbächler, E.; Strasser, T.; Himpsl-Gutermann, K.: Vom Chat zum Check : Informationskompetenz mit ChatGPT steigern (2023) 0.00
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  17. Stieler, W.: Anzeichen von Bewusstsein bei ChatGPT und Co.? (2023) 0.00
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    Abstract
    Ein interdisziplinäres Forschungsteam hat eine Liste von Eigenschaften aufgestellt, die auf Bewusstsein deuten, und aktuelle KI-Systeme darauf abgeklopft. Ein interdisziplinäres Forscherteam hat ein Paper [https://arxiv.org/abs/2308.08708] veröffentlicht, das eine Liste von 14 "Indikatoren" für Bewusstsein enthält, die aus sechs aktuellen Theorien über das Bewusstsein stammen. Aktuelle KI-Modelle wie GPT-3, Palm-E oder AdA von Deepmind weisen demnach einzelne dieser Indikatoren auf. "Es spricht viel dafür, dass die meisten oder alle Bedingungen für das Bewusstsein, die von derzeitigen Theorien vorgeschlagenen Bedingungen für das Bewusstsein mit den bestehenden Techniken der KI erfüllt werden können", schreiben die Autoren. Zum Team gehörte auch der Deep-Learning-Pionier Yoshua Bengio von der Université de Montréal.
  18. Chou, C.; Chu, T.: ¬An analysis of BERT (NLP) for assisted subject indexing for Project Gutenberg (2022) 0.00
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  19. Hausser, R.: Grammatical disambiguation : the linear complexity hypothesis for natural language (2020) 0.00
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  20. Corbara, S.; Moreo, A.; Sebastiani, F.: Syllabic quantity patterns as rhythmic features for Latin authorship attribution (2023) 0.00
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Languages

  • e 29
  • d 6

Types