Buch ; Online: Meta Semantics
Towards better natural language understanding and reasoning
2023
Abstract: Natural language understanding is one of the most challenging topics in artificial intelligence. Deep neural network methods, particularly large language module (LLM) methods such as ChatGPT and GPT-3, have powerful flexibility to adopt informal text but ...
Abstract | Natural language understanding is one of the most challenging topics in artificial intelligence. Deep neural network methods, particularly large language module (LLM) methods such as ChatGPT and GPT-3, have powerful flexibility to adopt informal text but are weak on logical deduction and suffer from the out-of-vocabulary (OOV) problem. On the other hand, rule-based methods such as Mathematica, Semantic web, and Lean, are excellent in reasoning but cannot handle the complex and changeable informal text. Inspired by pragmatics and structuralism, we propose two strategies to solve the OOV problem and a semantic model for better natural language understanding and reasoning. Comment: 10 pages, 8 figures, 2 tables |
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Schlagwörter | Computer Science - Computation and Language ; Computer Science - Artificial Intelligence ; 03B65(Primary) 68T50(Secondary) ; I.2.4 ; I.2.7 |
Erscheinungsdatum | 2023-04-20 |
Erscheinungsland | us |
Dokumenttyp | Buch ; Online |
Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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