The Making and Breaking of Classification Models in Linguistics

The Making and Breaking of Classification Models in Linguistics PDF Author: Jane Klavan
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110665182
Category : Language Arts & Disciplines
Languages : en
Pages : 262

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Book Description
The book provides a methodological blueprint for the study of constructional alternations – using corpus-linguistic methods in combination with different types of experimental data. The book looks at a case study from Estonian. This morphologically rich language is typologically different from Indo-European languages such as English. Corpus-based studies allow us to detect patterns in the data and determine what is typical in the language. Experiments are needed to determine the upper and lower limits of human classification behaviour. They give us an idea of what is possible in a language and show how human classification behaviour is susceptible to more variation than corpus-based models lead us to believe. Corpora and forced choice data tell us that when we produce language, we prefer one construction. Acceptability judgement data tell us that when we comprehend language, we judge both constructions as acceptable. The book makes a theoretical contribution to the what, why, and how of constructional alternations.

The Making and Breaking of Classification Models in Linguistics

The Making and Breaking of Classification Models in Linguistics PDF Author: Jane Klavan
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110665182
Category : Language Arts & Disciplines
Languages : en
Pages : 262

Get Book Here

Book Description
The book provides a methodological blueprint for the study of constructional alternations – using corpus-linguistic methods in combination with different types of experimental data. The book looks at a case study from Estonian. This morphologically rich language is typologically different from Indo-European languages such as English. Corpus-based studies allow us to detect patterns in the data and determine what is typical in the language. Experiments are needed to determine the upper and lower limits of human classification behaviour. They give us an idea of what is possible in a language and show how human classification behaviour is susceptible to more variation than corpus-based models lead us to believe. Corpora and forced choice data tell us that when we produce language, we prefer one construction. Acceptability judgement data tell us that when we comprehend language, we judge both constructions as acceptable. The book makes a theoretical contribution to the what, why, and how of constructional alternations.

The Making and Breaking of Classification Models in Linguistics

The Making and Breaking of Classification Models in Linguistics PDF Author: Jane Klavan
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110668467
Category : Language Arts & Disciplines
Languages : en
Pages : 250

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Book Description
The book provides a methodological blueprint for the study of constructional alternations – using corpus-linguistic methods in combination with different types of experimental data. The book looks at a case study from Estonian. This morphologically rich language is typologically different from Indo-European languages such as English. Corpus-based studies allow us to detect patterns in the data and determine what is typical in the language. Experiments are needed to determine the upper and lower limits of human classification behaviour. They give us an idea of what is possible in a language and show how human classification behaviour is susceptible to more variation than corpus-based models lead us to believe. Corpora and forced choice data tell us that when we produce language, we prefer one construction. Acceptability judgement data tell us that when we comprehend language, we judge both constructions as acceptable. The book makes a theoretical contribution to the what, why, and how of constructional alternations.

Breaking the Language Barrier: Demystifying Language Models with OpenAI

Breaking the Language Barrier: Demystifying Language Models with OpenAI PDF Author: Rayan Wali
Publisher: Rayan Wali
ISBN:
Category : Computers
Languages : en
Pages : 301

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Book Description
Breaking the Language Barrier: Demystifying Language Models with OpenAI is an informative guide that covers practical NLP use cases, from machine translation to vector search, in a clear and accessible manner. In addition to providing insights into the latest technology that powers ChatGPT and other OpenAI language models, including GPT-3 and DALL-E, this book also showcases how to use OpenAI on the cloud, specifically on Microsoft Azure, to create scalable and efficient solutions.

Hands-On Large Language Models

Hands-On Large Language Models PDF Author: Jay Alammar
Publisher: "O'Reilly Media, Inc."
ISBN: 1098150929
Category : Computers
Languages : en
Pages : 449

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Book Description
AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. You'll learn how to use the power of pre-trained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text documents; and use existing libraries and pre-trained models for text classification, search, and clusterings. This book also shows you how to: Build advanced LLM pipelines to cluster text documents and explore the topics they belong to Build semantic search engines that go beyond keyword search with methods like dense retrieval and rerankers Learn various use cases where these models can provide value Understand the architecture of underlying Transformer models like BERT and GPT Get a deeper understanding of how LLMs are trained Understanding how different methods of fine-tuning optimize LLMs for specific applications (generative model fine-tuning, contrastive fine-tuning, in-context learning, etc.)

Natural Language Processing

Natural Language Processing PDF Author: Yue Zhang
Publisher: Cambridge University Press
ISBN: 1108349773
Category : Computers
Languages : en
Pages : 487

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Book Description
With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.

Handbook of Language Analysis in Psychology

Handbook of Language Analysis in Psychology PDF Author: Morteza Dehghani
Publisher: Guilford Publications
ISBN: 1462548431
Category : Social Science
Languages : en
Pages : 650

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Book Description
Recent years have seen an explosion of interest in the use of computerized text analysis methods to address basic psychological questions. This comprehensive handbook brings together leading language analysis scholars to present foundational concepts and methods for investigating human thought, feeling, and behavior using language. Contributors work toward integrating psychological science and theory with natural language processing (NLP) and machine learning. Ethical issues in working with natural language data sets are discussed in depth. The volume showcases NLP-driven techniques and applications in areas including interpersonal relationships, personality, morality, deception, social biases, political psychology, psychopathology, and public health.

Computational Linguistics

Computational Linguistics PDF Author: Le-Minh Nguyen
Publisher: Springer Nature
ISBN: 9811561680
Category : Computers
Languages : en
Pages : 525

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Book Description
This book constitutes the refereed proceedings of the 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, held in Hanoi, Vietnam, in October 2019. The 28 full papers and 14 short papers presented were carefully reviewed and selected from 70 submissions. The papers are organized in topical sections on text summarization; relation and word embedding; machine translation; text classification; web analyzing; question and answering, dialog analyzing; speech and emotion analyzing; parsing and segmentation; information extraction; and grammar error and plagiarism detection.

Models in Software Engineering

Models in Software Engineering PDF Author: Sudipto Ghosh
Publisher: Springer
ISBN: 3642122612
Category : Computers
Languages : en
Pages : 370

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Book Description
This book constitutes a collection of the best papers selected from 9 workshops and 2 symposia held in conjunction iwth MODELS 2009, the 12 International Conference on Model Driven Engineering Languages and Systems, in Denver, CO, USA, in October 2009. The first two sections contain selected papers from the Doctoral Symposium and the Educational Symposium, respectively. The other contributions are organized according to the workshops at which they were presented: 2nd International Workshop on Model Based Architecting and Construction of Embedded Systems (ACES-MB'09); 14th International Workshop on Aspect-Oriented Modeling (AOM); [email protected] ([email protected]); Model-driven Engineering, Verification, and Validation: Integrating Verification and Validation in MDE (MoDeVVa09); Models and Evolution (MoDSE-MCCM); Third International Workshop on Multi-Paradigm Modeling (MPM09); The Pragmatics of OCL and Other Textual Specification Languages (OCL); 2nd International Workshop on Non-Functional System Properties in Domain Specific Modeling Languages (NFPinDSML); and 2nd Workshop on Transformation and Weaving OWL Ontologies and MDE/MDA (TWOMDE2009). Each section includes a summary of the workshop.

Quantitative Data Analysis for Language Assessment Volume II

Quantitative Data Analysis for Language Assessment Volume II PDF Author: Vahid Aryadoust
Publisher: Routledge
ISBN: 1351741209
Category : Education
Languages : en
Pages : 244

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Book Description
Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods demonstrates advanced quantitative techniques for language assessment. The volume takes an interdisciplinary approach and taps into expertise from language assessment, data mining, and psychometrics. The techniques covered include Structural Equation Modeling, Data Mining, Multidimensional Psychometrics and Multilevel Data Analysis.Volume II is distinct among available books in language assessment, as it engages the readers in both theory and application of the methods and introduces relevant techniques for theory construction and validation. This book is highly recommended to graduate students and researchers who are searching for innovative and rigorous approaches and methods to achieve excellence in their dissertations and research. It is also a valuable source for academics who teach quantitative approaches in language assessment and data analysis courses.

Large Language Models in Cybersecurity

Large Language Models in Cybersecurity PDF Author: Andrei Kucharavy
Publisher: Springer Nature
ISBN: 3031548272
Category : Computer security
Languages : en
Pages : 249

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Book Description
This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful large language models (LLMs) and how they can be mitigated. It attempts to outrun the malicious attackers by anticipating what they could do. It also alerts LLM developers to understand their work's risks for cybersecurity and provides them with tools to mitigate those risks. The book starts in Part I with a general introduction to LLMs and their main application areas. Part II collects a description of the most salient threats LLMs represent in cybersecurity, be they as tools for cybercriminals or as novel attack surfaces if integrated into existing software. Part III focuses on attempting to forecast the exposure and the development of technologies and science underpinning LLMs, as well as macro levers available to regulators to further cybersecurity in the age of LLMs. Eventually, in Part IV, mitigation techniques that should allowsafe and secure development and deployment of LLMs are presented. The book concludes with two final chapters in Part V, one speculating what a secure design and integration of LLMs from first principles would look like and the other presenting a summary of the duality of LLMs in cyber-security. This book represents the second in a series published by the Technology Monitoring (TM) team of the Cyber-Defence Campus. The first book entitled "Trends in Data Protection and Encryption Technologies" appeared in 2023. This book series provides technology and trend anticipation for government, industry, and academic decision-makers as well as technical experts.