Olivero, 2024 - Google Patents
Figurative language understanding based on large language modelsOlivero, 2024
View PDF- Document ID
- 5370154686831115757
- Author
- Olivero S
- Publication year
External Links
Snippet
In the vast realm of Natural Language Processing, one of the areas that still presents a bottleneck is Figurative Language Understanding. However, this field is of fundamental interest both theoretically and practically; in all new applications of Artificial Intelligence …
- 238000012549 training 0 abstract description 92
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2705—Parsing
- G06F17/271—Syntactic parsing, e.g. based on context-free grammar [CFG], unification grammars
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/30675—Query execution
- G06F17/30684—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2785—Semantic analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Ansari et al. | Ensemble hybrid learning methods for automated depression detection | |
Zhang et al. | Multi-turn dialogue reading comprehension with pivot turns and knowledge | |
Yang et al. | Learning symbolic rules for reasoning in quasi-natural language | |
Zhu | Machine reading comprehension: algorithms and practice | |
Sahoo et al. | Comparative analysis of bert models for sentiment analysis on twitter data | |
Sen et al. | Support-BERT: predicting quality of question-answer pairs in MSDN using deep bidirectional transformer | |
Saxena | Beyond Flashcards: Designing an Intelligent Assistant for USMLE Mastery and Virtual Tutoring in Medical Education (A Study on Harnessing Chatbot Technology for Personalized Step 1 Prep) | |
Olivero | Figurative language understanding based on large language models | |
Karim et al. | Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation | |
Zhang et al. | Human-like explanation for text classification with limited attention supervision | |
Andrikakis et al. | Text analysis and recognition of emotional content using deep learning methods and BERT | |
Reda | Intelligent Assistant Agents: Comparative Analysis of Chatbots through Diverse Methodologies | |
Douka et al. | Sentiment analysis with the use of transformers and BERT | |
Sangani et al. | Comparing deep sentiment models using quantified local explanations | |
Dunn et al. | Designing and evaluating context-sensitive visualization models for deep learning text classifiers | |
Cambria | Knowledge Representation & Reasoning | |
丁飛 et al. | Research on Interpretable Text Sentiment Analysis | |
Bakomichalis | Cyberbullying detection through NLP and machine learning | |
Mohasina | RoBERTa: a machine reading comprehension for climate change question answering in natural language processing | |
Ho | Question classification via machine learning techniques | |
Papatheodorou | A comprehensive analysis of pre-trained language models for detecting insincere questions on Quora | |
Olsén | Designing a Pipeline for Creating and Evaluating Swedish Instruction Datasets for Large Language Models | |
Pielka | Linguistically Aware and Augmentation-Driven Methods for Enhancing Natural Language Understanding | |
Sunilkumar et al. | EXIST: sEXism Identification in Social Networks (CLEF 2024) | |
Velu et al. | 5 LLM Pretraining Methods |