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Book SynopsisPractical LaTeX covers the material that is needed for everyday LaTeX documents. This accessible manual is friendly, easy to read, and is designed to be as portable as LaTeX itself.A short chapter, Mission Impossible, introduces LaTeX documents and presentations. Read these 30 pages; you then should be able to compose your own work in LaTeX. The remainder of the book delves deeper into the topics outlined in Mission Impossible while avoiding technical subjects. Chapters on presentations and illustrations are a highlight, as is the introduction of LaTeX on an iPad.Students, faculty, and professionals in the worlds of mathematics and technology will benefit greatly from this new, practical introduction to LaTeX. George Grätzer, author of More Math into LaTeX (now in its 4th edition) and First Steps in LaTeX, has been a LaTeX guru for over a quarter of century.From the reviews of More Math into LaTeX:``There are several LaTeX guides, but this one wins hands down for the elegance of its approach and breadth of coverage.''—Amazon.com, Best of 2000, Editors Choice``A very helpful and useful tool for all scientists and engineers.''—Review of Astronomical Tools``A novice reader will be able to learn the most essential features of LaTeX sufficient to begin typesetting papers within a few hours of time…An experienced TeX user, on the other hand, will find a systematic and detailed discussion of all LaTeX features, supporting software, and many other advanced technical issues.''—Reports on Mathematical PhysicsTrade ReviewFrom the book reviews:“I’ve been looking for a friendly and accessible manual that I could recommend to students as a way to get over the initial learning curve, and this book seemed like it would fit the bill. … The emphasis is on skills necessary for writing and presenting in an academic setting, and in particular it is geared toward students in math, physics, and numerate disciplines. … Overall, it is a well-presented volume and pleasant to read.” (Sara Kalvala, Computing Reviews, December, 2014)“The book starts with a quick survey, and then explores a bit deeper how to typeset the text, the use of environments, (mathematical) formulas and arrays, and finally the global structure of the document (top matter, body, back matter). … this book might be interesting to read, not only for the beginner, but also for the experienced LaTeX user.” (Adhemar Bultheel, euro-math-soc.eu, December, 2014)“If I really, really have to learn LaTeX, this is the book I’ll go to in a flash. … Even at a first glance or at first browse it’s abundantly clear that this is a very good book for a TeXtyro like me … . It’s eminently practical and therefore eminently worthwhile.” (Michael Berg, MAA Reviews, November, 2014)Table of Contents​Introduction.- 1. Getting LaTex.- 2. Typing Text.- 3. Text environments.- 4. Typing Formulas.- 5. Displayed Formulas.- 6. Articles.- 7. Making Presentations.- 8. Customization.- 9. The Symbol Tables.- Index.

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Book SynopsisThe purpose of this Handbook is to highlight both theory and applications of weighted automata. Weighted finite automata are classical nondeterministic finite automata in which the transitions carry weights. These weights may model, e. g. , the cost involved when executing a transition, the amount of resources or time needed for this,or the probability or reliability of its successful execution. The behavior of weighted finite automata can then be considered as the function (suitably defined) associating with each word the weight of its execution. Clearly, weights can also be added to classical automata with infinite state sets like pushdown automata; this extension constitutes the general concept of weighted automata. To illustrate the diversity of weighted automata, let us consider the following scenarios. Assume that a quantitative system is modeled by a classical automaton in which the transitions carry as weights the amount of resources needed for their execution. Then the amount of resources needed for a path in this weighted automaton is obtained simply as the sum of the weights of its transitions. Given a word, we might be interested in the minimal amount of resources needed for its execution, i. e. , for the successful paths realizing the given word. In this example, we could also replace the “resources” by “profit” and then be interested in the maximal profit realized, correspondingly, by a given word.Trade ReviewFrom the reviews:"This book is an excellent reference for researchers in the field, as well as students interested in this research area. The presentation of applications makes it interesting to researchers from other fields to study weighted automata. ... One of the main arguments in favor of this handbook is the completeness of its index table — usually a faulty section in such volumes. The chapters are globally well-written and self-contained, thus pleasant to read, and the efforts put to maintain consistency in vocabulary thorough the book are very appreciable." (Michaël Cadilhac, The Book Review Column 43-3, 2012)“The book presents a broad survey, theory and applications, of weighted automata, classical nondeterministic automata in which transitions carry weights. … The individual articles are written by well-known researchers in the field: they include extensive lists of references and many open problems. The book is valuable for both computer scientists and mathematicians (being interested in discrete structures).” (Cristian S. Calude, Zentralblatt MATH, Vol. 1200, 2011)Table of ContentsFoundations.- Semirings and Formal Power Series.- Fixed Point Theory.- Concepts of Weighted Recognizability.- Finite Automata.- Rational and Recognisable Power Series.- Weighted Automata and Weighted Logics.- Weighted Automata Algorithms.- Weighted Discrete Structures.- Algebraic Systems and Pushdown Automata.- Lindenmayer Systems.- Weighted Tree Automata and Tree Transducers.- Traces, Series-Parallel Posets, and Pictures: A Weighted Study.- Applications.- Digital Image Compression.- Fuzzy Languages.- Model Checking Linear-Time Properties of Probabilistic Systems.- Applications of Weighted Automata in Natural Language Processing.

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Book SynopsisThe present book is based on the conference Software Development and Reality Construction held at SchloB Eringerfeld in Germany, September 25 - 30, 1988. This was organized by the Technical University of Berlin (TUB) in cooperation with the German National Research Center for Computer Science (GMD), Sankt Augustin, and sponsored by the Volkswagen Foundation whose financial support we gratefully acknowledge. The conference was an interdisciplinary scientific and cultural event aimed at promoting discussion on the nature of computer science as a scientific discipline and on the theoretical foundations and systemic practice required for human-oriented system design. In keeping with the conversational style of the conference, the book comprises a series of individual contributions, arranged so as to form a coherent whole. Some authors reflect on their practice in computer science and system design. Others start from approaches developed in the humanities and the social sciences for understanding human learning and creativity, individual and cooperative work, and the interrelation between technology and organizations. Thus, each contribution makes its specific point and can be read on its own merit. But, at the same time, it takes its place as a chapter in the book, along with all the other contributions, to give what seemed to us a meaningful overall line of argumentation. This required careful editorial coordination, and we are grateful to all the authors for bearing with us throughout the slow genesis of the book and for complying with our requests for extensive revision of some of the manuscripts.Table of ContentsPrologue.- 1 Thinking About Computer Science.- 1.1 Human Questions in Computer Science.- 1.2 Learning from our Errors.- 2 Living Computer Science.- 2.1 The Technical and the Human Side of Computer Science.- 2.2 Hermeneutics and Path.- 2.3 Computing: Yet Another Reality Construction.- 2.4 How Many Choices Do We Make? How Many Are Difficult?.- 2.5 From Scientific Practice to Epistemological Discovery.- 3 On Reality Construction.- 3.1 Self-Organization and Software Development.- 3.2 Software Development as Reality Construction.- 3.3 The Idea that Reality is Socially Constructed.- 4 Learning to Know.- 4.1 Scientific Expertise as a Social Process.- 4.2 How to Communicate Proofs or Programs.- 4.3 Making Errors, Making Sense, Making Use.- 4.4 Artifacts in Software Design.- 5 Computer Science and Beyond.- 5.1 The Denial of Error.- 5.2 Towards a New Understanding of Data Modelling.- 5.3 A Reappraisal of Information Science.- 6 Understanding the Computer Through Metaphors.- 6.1 Perspectives and Metaphors for Human-Computer Interaction.- 6.2 Software Tools in a Programming Workshop.- 6.3 Soft Engines — Mass-Produced Software for Working People?.- 6.4 Artificial Intelligence: A Hermeneutic Defense.- 7 Designing for People.- 7.1 Shared Responsibility: A Field of Tension.- 7.2 A Subject-Oriented Approach to Information Systems.- 7.3 Anticipating Reality Construction.- 7.4 On Controllability.- 7.5 Work Design for Human Development.- 8 Epistemological Approaches to Informatics.- 8.1 Truth and Meaning Beyond Formalism.- 8.2 Informatics and Hermeneutics.- 8.3 Language and Software, or: Fritzl’s Quest.- 8.4 Activity Theory as a Foundation for Design.- 8.5 Reflections on the Essence of Information.- Epilogue.- List of Authors.

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Book SynopsisSprachliche Verstellungen in inkriminierten Texten wie Erpresserbriefen und Drohschreiben sind ein Phänomen, mit dem Gutachter/innen – beispielsweise im Rahmen von polizeilichen Ermittlungen – immer wieder konfrontiert werden. Um ihre Identität zu verschleiern, verfremden die Autor/innen dieser inkriminierten Texte ihren Sprachstil oder ahmen den Sprachgebrauch anderer Personen und Personengruppen nach. In der forensisch-linguistischen Forschungsliteratur werden diese Verstellungen häufig genannt, Gegenstand wissenschaftlicher Untersuchungen waren sie jedoch selten, so dass bisher nur wenig über sie bekannt war.Diese Arbeit widmet sich diesem Forschungsdesiderat mit dem Ziel, anhand eines Datenkorpus des Bundeskriminalamtes Merkmale von sprachlichen Verstellungen in inkriminierten Texten herauszuarbeiten, damit sie besser erkannt und adäquat beschrieben werden können. Die Untersuchung richtet sich vor allem an Personen, die in ihrer Arbeit mit inkriminierten Texten befasst sind.Table of Contents1. Einleitung.- 2. Theoretischer Rahmen.- 3. Forschungsstand.- 4. Datenkorpus.- 5. Methoden der Analyse.- 6. Analyseergebnisse.- 7. Zusammenfassung und Diskussion der Ergebnisse.- 8. Literaturverzeichnis.- Anhang.

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Book Synopsis.- Information Extraction and Knowledge Graph..- Progressive Training of Transformer for Knowledge Graph Completion Tasks..- Document-level Event Coreference Resolution on Trigger Augmentation and Contrastive Learning..- Dynamic Chain-of-thought for Low-Resource Event Extraction..- On Sentence-level Non-adversarial Robustness of Chinese Named Entity Recognition with Large Language Models..- Spatial Relation Classification on Supervised In-Context Learning..- HGNN2KAN: Distilling hypergraph neural networks into KAN for efficient inference..- Adapting Task-General ORE Systems for Extracting Open Relations between Fictional Characters in Chinese Novels..- DRLF:Denoiser-Reinforcement Learning Framework for Entity Completion..- Fashion-related Attribute Value Extraction with Visual Prompting..- Discovering Latent Relationship for Temporal Knowledge Graph Reasoning..- Logical Rule-Constrained Large Language Models for Document-Level Relation Extraction..- An Adaptive Semantic-Aware Fusion Method for Multimodal Entity Linking..- Retrieve, Interaction, Fusion: a Simple Approach in Ancient Chinese Named Entity Recognition..- Reasoning-Guided Prompt Learning with Historical Knowledge Injection for Ancient Chinese Relation Extraction..- MMD-TKGR: Multi-Agent Multi-Round Debate for Temporal Knowledge Graph Reasoning..- AutoPRE: Discovering Concept Prerequisites with LLM Agents..- Weakly-Supervised Generative Framework for Product Attribute Identification in Live-Streaming E-Commerce..- Exploring Representation-Efficient Transfer Learning Approaches for Speech Recognition and Translation Using Pre-trained Speech Models..- A Neighborhood Aggregation-based Knowledge Graph Reasoning Approach in Operations and Maintenance..- CARE: Contextual Augmentation with Retrieval Enhancement for Relation Extraction in Large Language Models..- RHDG: Retrieval-augmented Heuristics-driven Demonstration Generation for Document-Level Event Argument Extraction..- Large Language Models and Agents..- Beyond One-Size-Fits-All: Adaptive Fine-Tuning for LLMs Based on Data Inherent Heterogeneity..- From Chain to Loop: Improving Reasoning Capability in Small Language Models via Loop-of-Thought..- TaxBen: Benchmarking the Chinese Tax Knowledge of Large Language Models..- Propagandistic Meme Detection via Large Language Model Distillation..- Multi-Candidate Speculative Decoding..- Debate-Driven Legal Reasoning: Disambiguating Confusing Charges through Multi-Agent Debate..- A Human-Centered AI Agent Framework with Large Language Models for Academic Research Tasks..- ReGA: Reasoning and Grounding Decoupled GUI Navigation Agents..- PSYCHE: Practical Synthetic Math Data Evolution. .- MultiJustice: A Chinese Dataset for Multi-Party, Multi-Charge Legal Prediction..- Reward-Guided Many-Shot Jailbreaking..- Self-Prompt Tuning: Enable Autonomous Role-Playing in LLMs..- RASR: A Multi-Perspective RAG-based Strategy for Semantic Textual Similarity..- H2HTALK: Evaluating Large Language Models as Emotional Companion..- EvoP: Robust LLM Inference via Evolutionary Pruning..- Large Language Model based Multi-Agent Learning for Mixed Cooperative-Competitive Environments..- EduMate:LLM-Powered Detection of Student Learning Emotions and Efficacy in Semi-Structured Counseling..- MAD-HD: Multi-Agent Debate-Driven Ungrounded Hallucination Detection..- TIANWEN: A Comprehensive Benchmark for Evaluating LLMs in Chinese Classical Poetry Understanding and Reasoning..- RKE-Coder: A LLMs-based Code Generation Framework with Algorithmic and Code Knowledge Integration..- See Better, Say Better: Vision-Augmented Decoding for Mitigating Hallucinations in Large Vision-Language Models..- Exploring Large Language Models for Grammar Error Explanation and Correction in Indonesian as a Low-Resource Language..- Libra: Large Chinese-based Safeguard for AI Content..- FADERec: Fine-grained Attribute Distillation Enhanced by Collaborative Fusion for LLM-based Recommendation..- Improving RL Exploration for LLM Reasoning through Retrospective Replay.

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Book Synopsis.- IR / Dialogue Systems / Question Answering.- TriG-RAG: Triple-Granularity Fusion for Retrieval-Augmented Generation with Adaptive Context-Relation Balance..- Knowledge Distillation for Large Language Models Based on Global Keywords and Chain of Thought..- Exploring the Capabilities of Chinese LLMs in the Legal Field..- RoleplayLLM: Enhancing Role-Playing Abilities in Large Language Models via Multidimensional Fine Tuning and Preference Optimization..- Multi-task Contrastive Learning Enhanced Instruction Tuning for Dialog Understanding..- DynaRAG: Adaptive Context Compression via Reinforcement Learning for Enhanced Retrieval-Augmented Generation..- Retrieving and Reading Multimodal Documents for Knowledge-based VQA..- Relation-Aware Graph Reasoning for Multiple Choice Question Answering..- Enhancing Depression-Diagnosis-Oriented Chat with Psychological State Tracking. .- ReD-RAG: Rewritable Decomposition-Guided Iterative Retrieval Augmented Generation for Open Domain Multi-Hop Reasoning..- Bridging Questions and Charts: A Weakly Supervised Alignment Model for Chart Question Answering. .- FRAG: Focused Retrieval Augmented Generation Reducing Retrieval Scope by Mapping Table..- Ensuring Context Completeness in Retrieval-Augmented Generation for Knowledge-Intensive Question-answering..- Machine Translation and Multilinguality.- Improving LLM-based Document-level MT with Multi-Knowledge Fusion..- Continual Learning for Multilingual Neural Machine Translation via Meta-Contrastive Memory Replay..- Prompting and Consistency Learning Strategies for Multimodal Grammatical Error Correction in Low Error Density Domains..- Bias Beyond English: Evaluating Social Bias and Debiasing Methods in a Low-Resource Setting..- Doc-Guided Sent2Sent++: A Sent2Sent++ Agent with Doc-Guided memory for Document-level Machine Translation..- Fine-Grained Contrastive Learning for End-to-End Vietnamese Text Image Machine Translation..- Adaptive Inner Speech Text Alignment for LLM-based Speech Translation..- Fine-Tuning for Low-Resource Language Machine Translation Using Large Language Models Integrated with Dependency Parsing Rule..- Simplify Translate: A Unified Framework for Accessible Machine Translation..- PGATA: Phonology-and-Glyph-Aware Token Alignment for Transfer Learning in Cantonese Sarcasm Detection..- LLM-enhanced Translation for Low-resource Languages: Cross-lingual Alignment and Multi-domain Adaptation..- Sentiment analysis / Argumentation Mining / Social Media.- Best-Fit Document: Enhancing Compositional Generalization in Multi-label Text Classification..- Dialogue Multi-dimensional Feature Dividing and Fusion Model for Dialogue Aspect-based Sentiment Quadruple Analysis..- Boosting Affective Events Classification: A Contextual Framework with Chain-of-Thought Prompt..- Hate Speech Detection in Somali-English Code-Switched Texts..- Chinese Spelling Correction for Social-Platform Internet Slang Texts..- DiGTF: A Difference-Guided Two-Stage Fusion Framework for Multimodal Sentiment Analysis. .- EVL-MCoT: Enhanced Vision-Language Multi-CoT for Harmful Meme Detection..- Deep Graph Neural Point Process For Learning Temporal Interactive Networks..- Bayesian Network-based Adaptive Prompt Learning for Emotion-Cause Pair Extraction..- Exploring Sentiment Analysis in Tigrigna: Insights from Social Media Texts..- Unlocking the Advantage of Context Interaction via Bi-Graph Reasoning for Document-level Aspect-based Sentiment Analysis..- EMAO: Expectation-Maximization and Adaptive Objective for Microscopic Cascade Prediction..- Attributed Graph Clustering with Dual Contrastive Regularization..- Deep Learning-Based Knowledge Injection for Metaphor Detection: A Comprehensive Review..- CADA: A Counterfactual Adversarial Data Augmentation Framework for Low-Resource Hate Speech Detection..- Semantic Information Enhanced Fake News Detection..- Fine-grained Inappropriate Speech Detection Based on Momentum Contrastive Learning..- ISIPN: Intention-Semantic Incongruity Perception Network for Multimodal Metaphor Detection..- Self-Distillation Across Modalities: Enhancing Cross-Modal Correlation Perception for Multimodal Fake News Detection..- D-PathVER: Dynamic Reasoning Paths for Complex Claim Verification..- Dynamic Multi-Views In-Context Learning with Large Language Models for Aspect-Based Sentiment Analysis..- MAGI: Modality-Aligned Geometry-aware Integration for Robust Multimodal Sentiment Analysis.

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Book SynopsisPart I Background Knowledge: Chapter 1 Introduction.- Chapter 2 Background.- Chapter 3 Language Model Resources.- Part II Pre-training: Chapter 4 Data Preparation- Chapter 5 Model Architecture.- Chapter 6 Model Pre-training.- Part III Post-Training: Chapter 7 Instruction Tuning.- Chapter 8 Human Alignment.- Part IV Utilization and Evaluation: Chapter 9 Decoding and Deployment.- Chapter10 Prompt Engineering.- Chapter 11 Advanced Reasoning.- Chapter 12 Evaluation.- Chapter 13 Conclusion.

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Book SynopsisChapter 1. Introduction.- Chapter 2. Classical Topic Models.- Chapter 3. Modern Topic Models.- Chapter 4. Applications.- Chapter 5. Discussions.

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Book SynopsisChapter 1: Natural Language Processing and its Applications.- Chapter 2: Traditional Deep Learning Algorithms and Platforms.- Chapter 3 Advances and Trends in Deep Learning.- Chapter 4: Pre-training Models.- Chapter 5: Web Crawlers.- Chapter 6 Multi-format Document Parsing and Management.- Chapter 7 Speech Text Recognition.

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