Sökning: "Generative question answering"

Hittade 5 uppsatser innehållade orden Generative question answering.

  1. 1. Går det att lita på ChatGPT? En kvalitativ studie om studenters förtroende för ChatGPT i lärandesammanhang

    Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Alexandra Härnström; Isak Eljas Bergh; [2023]
    Nyckelord :Artificial intelligence; Generative AI; LLM; NLP; ChatGPT; GPT-3; GPT-3.5; Trust; Educational context; Language technology; Large language models; Information retrieval; Artificiell intelligens; Generativ AI; LLM; NLP; ChatGPT; GPT-3; GPT-3.5; Förtroende; Lärandesammanhang; Språkteknologi; Stora språkmodeller; Informationsinhämtning;

    Sammanfattning : Världens tekniska utveckling går framåt i snabb takt, inte minst när det kommer till ”smarta” maskiner och algoritmer med förmågan att anpassa sig efter sin omgivning. Detta delvis på grund av den enorma mängd data som finns tillgänglig och delvis tack vare en ökad lagringskapacitet. LÄS MER

  3. 2. Synthetic data generation for domain adaptation of a retriever-reader Question Answering system for the Telecom domain : Comparing dense embeddings with BM25 for Open Domain Question Answering

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Filip Döringer Kana; [2023]
    Nyckelord :Natural Language Processing; Transformers; Deep Learning; Question Answering; Data Generation; Språkteknologi; Transformers; Djupinlärning; Frågebesvaring; Datagenerering;

    Sammanfattning : Having computer systems capable of answering questions has been a goal within Natural Language Processing research for many years. Machine Learning systems have recently become increasingly proficient at this task with large language models obtaining state-of-the-art performance. LÄS MER

  4. 3. Can Wizards be Polyglots: Towards a Multilingual Knowledge-grounded Dialogue System

    Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

    Författare :Evelyn Kai Yan Liu; [2022]
    Nyckelord :Knowledge-grounded dialogue; Dialogue systems; Generative question answering; Multilingual question answering; Multilingual dialogue systems; Transfer learning; Multi-task learning; Sequential training; Conversational AI; Natural Language Processing NLP ; Deep learning; Machine learning;

    Sammanfattning : The research of open-domain, knowledge-grounded dialogue systems has been advancing rapidly due to the paradigm shift introduced by large language models (LLMs). While the strides have improved the performance of the dialogue systems, the scope is mostly monolingual and English-centric. LÄS MER

  5. 4. Automatic Question Paraphrasing in Swedish with Deep Generative Models

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Niklas Lindqvist; [2021]
    Nyckelord :Paraphrase Generation; Variational Autoencoder; Generative Adversarial Networks; Natural Language Generation; Deep Learning; Word Embeddings; Parafrasgenerering; Variational Autoencoder; generativa adversariala nätverk; naturlig språkgenerering; djupinlärning; ordinbäddning;

    Sammanfattning : Paraphrase generation refers to the task of automatically generating a paraphrase given an input sentence or text. Paraphrase generation is a fundamental yet challenging natural language processing (NLP) task and is utilized in a variety of applications such as question answering, information retrieval, conversational systems etc. LÄS MER

  7. 5. Conversational Chatbots with Memory-based Question and Answer Generation

    Master-uppsats, Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska högskolan

    Författare :Mikael Lundell Vinkler; Peilin Yu; [2020]
    Nyckelord :;

    Sammanfattning : The aim of the study is to contribute to research in the field of maintaining long-term engagingness in chatbots, which is done through rapport building with the help of user and agent specific memory. Recent advances in end-to-end trained neural conversational models (fully functional chit-chat chatbots created by training a neural model) present chatbots that converse well with respect to context understanding with the help of their short-term memory. LÄS MER