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pro vyhledávání: '"Pour, Mohammad Mahdi Abdollah"'
Knowledge Graph Question Answering (KGQA) methods seek to answer Natural Language questions using the relational information stored in Knowledge Graphs (KGs). With the recent advancements of Large Language Models (LLMs) and their remarkable reasoning
Externí odkaz:
http://arxiv.org/abs/2403.01390
Autor:
Pour, Mohammad Mahdi Abdollah, Farinneya, Parsa, Toroghi, Armin, Korikov, Anton, Pesaranghader, Ali, Sajed, Touqir, Bharadwaj, Manasa, Mavrin, Borislav, Sanner, Scott
Publikováno v:
European Conference on Information Retrieval, pages 3--17, year 2023, Springer
As natural language interfaces enable users to express increasingly complex natural language queries, there is a parallel explosion of user review content that can allow users to better find items such as restaurants, books, or movies that match thes
Externí odkaz:
http://arxiv.org/abs/2308.00762
Autor:
Floto, Griffin, Pour, Mohammad Mahdi Abdollah, Farinneya, Parsa, Tang, Zhenwei, Pesaranghader, Ali, Bharadwaj, Manasa, Sanner, Scott
Text detoxification is a conditional text generation task aiming to remove offensive content from toxic text. It is highly useful for online forums and social media, where offensive content is frequently encountered. Intuitively, there are diverse wa
Externí odkaz:
http://arxiv.org/abs/2306.08505
Akademický článek
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