Semantics - Science topic

This chapter focuses on the grammatical devices used in the languages of the Central Andes to make discourse coherent and cohesive. These include marking of information-structural categories such as topic and focus, evidential marking, tail-head linkage, and grammaticalized ways of tracking reference in discourse. Most attention is granted to the Q...

The purpose of this study was to provide a systematic review of the literature on the relationship between democracy and economic growth. The aim was to provide scholars and policymakers with important up-to-date information on how democracy affects economic growth, as well as solid evidence of the gaps in the literature that need to be filled imme...

This study expands upon previous research on family firm leadership by exploring the role of CEO identity-i.e., family vs. nonfamily CEO-concerning the way media perceive the brand of the family firm-i.e., brand importance. Drawing on endorsement theory, we suggest that CEO identity influences media perception of the family firm and its brand, ther...

Aunque actualmente nadie duda del carácter determinante que tiene en español la subordinación final sobre el modo de la subordinada, hasta el momento no se ha sabido aportar una justificación semántica sólida de este fenómeno. García Yanes (2022b) añade al panorama de los estudios del modo un enfoque novedoso, desarrollado dentro del marco de la li...

The research was initiated out of concern for the lack of knowledge that education students have regarding the concepts of emotion and culture. The specific objective was to investigate the social representations of education students in the region of La Araucaní a, Chile, regarding the concepts of emotion and culture. The method is based on the th...

Details of the workshop is available at: https://ants2024.ieee-ants.org/program/workshops#ws1

While image-to-text models have demonstrated significant advancements in various vision-language tasks, they remain susceptible to adversarial attacks. Existing white-box attacks on image-to-text models require access to the architecture, gradients , and parameters of the target model, resulting in low practicality. Although the recently proposed g...

As early as 1949, Weaver defined communication in a very broad sense to include all procedures by which one mind or technical system can influence another, thus establishing the idea of semantic communication. With the recent success of machine learning in expert assistance systems where sensed information is wirelessly provided to a human to assis...

This paper contributes to the debate on Davidsonian versus Kimian states (K/D distinction). I argue that the K/D distinction is a semantic universal that does not depend on morphosyntax. Copular predicates in the European languages exhibit the K/D distinction, contrary the claims made in the neo-davidsonian tradition. Slavic languages contribute to...

p>The article examines some original words of the Akhty dialect from the point of view of their equivalence or lacunarity in relation to the lexemes of the Lezgin literary language. Their semantic equivalents in the literary language are given, usually presented in the form of descriptive constructions or borrowed words. A comparative-contrastive a...

Facial Expression Recognition has a wide application prospect in social robotics, health care, driver fatigue monitoring, and many other practical scenarios. Automatic recognition of facial expressions has been extensively studied by the Computer Vision research society. But Facial Expression Recognition in real-world is still a challenging task, p...

In this study I explore the transfer and further adaptation of Arabic lazima, first into Swahili and its many varieties and then from Swahili into several local language varieties spoken in East Africa. Establishing the function of lazima as a modal marker, used for conveying strong necessity, I examine the various structural and semantic types of...

Low-resource languages in natural language processing present unique challenges, marked by limited linguistic resources and sparse data. These challenges extend to document clustering tasks, where the need for meaningful and semantically rich representations is crucial. Along with the emergence of transformer-based language models (LM), the need fo...

Currently, intelligent pest monitoring systems transmit entire monitoring images to cloud servers for analysis. This approach not only consumes significant bandwidth and increases monitoring costs, but also struggles with accurately recognizing small-target and overlapping pests. To overcome these challenges, this paper introduces a two-stage multi...

Text embedding plays a crucial role in natural language processing (NLP). Among various approaches, nonnegative matrix factorization (NMF) is an effective method for this purpose. However, the standard NMF approach, fundamentally based on the bag-of-words model, fails to utilize the contextual information of documents and may result in a significan...

When writing SQL queries, it is often convenient to use correlated subqueries. However, for the database engine, these correlated queries are very difficult to evaluate efficiently. The query optimizer will therefore try to eliminate the correlations, a process referred to as unnesting. Recent work has introduced a single pass top-down algorithm fo...

See https://www.semanticscholar.org/author/Silvio-Alen-Canton/35210448

Semantic segmentation is used for identification of buildings, roads, vegetation cover, and water body detection in satellite images. Several state-of-the-art deep learning models investigated have a large number of parameters and are difficult to train on low-configuration machines. To resolve this issue, quadratic encoder–decoder (QuadED), and re...

The rapid growth of academic publications has exacerbated the issue of author name ambiguity in online digital libraries. Despite advances in name disambiguation algorithms, cumulative errors continue to undermine the reliability of academic systems. It is estimated that over 10% paper-author assignments are rectified when constructing the million-...

Knowing functions and functional thinking have recently moved from just knowledge for older students to incorporating younger students, and functional thinking has been identified as one of the core competencies for algebra. Although it is significant for mathematical understanding, there is no unified view of functional thinking and how different...

Augmented reality applications involving human interaction with virtual objects often rely on segmentation-based hand detection techniques. Semantic segmentation can then be enhanced with instance-specific information to model complex interactions between objects, but extracting such information typically increases the computational load significan...

En la actualidad, las transformaciones en la sociedad han permeado a las instituciones del trabajo y la familia. Mediante una metodología mixta se buscó conocer los significados, que 105 personas que trabajan remuneradamente, atribuyen al "Trabajo" y la "Familia" en tiempos de emergencia sanitaria. Se utilizaron redes semánticas naturales, para exp...

In this study, we introduce an advanced method for the digital preservation of wood carvings, a significant component of our cultural heritage. By merging the U-Net model with 6G network technology, we’ve developed a precise and efficient 3D reconstruction process. The U-Net model achieved outstanding semantic segmentation with an average IoU of 0....

Remote sensing image building change detection aims to identify building changes that occur in remote sensing images of the same areas acquired at different times. In recent years, the development of deep learning has led to significant advancements in building change detection methods. However, these fully supervised methods require a large number...

Incremental anomaly detection sequentially recognizes abnormal regions in novel categories for dynamic industrial scenarios. This remains highly challenging due to knowledge overwriting and feature conflicts, leading to catastrophic forgetting. In this work, we propose ONER, an end-to-end ONline Experience Replay method, which efficiently mitigates...

Supervised 3D part segmentation models are tailored for a fixed set of objects and parts, limiting their transferability to open-set, real-world scenarios. Recent works have explored vision-language models (VLMs) as a promising alternative, using multi-view rendering and textual prompting to identify object parts. However, naively applying VLMs in...

The importance of mental health is increasingly emphasized in modern society. The assessment of mental health qualities among college and university students as the future workforce holds significant significance. Therefore, this study, aiming to streamline the process of writing quality evaluations and enhance the fairness of assessment comments,...

The main concern in image manipulation localization is the development of a feature representation that can effectively detect various manipulation techniques such as copy-move, removal, and splicing. However, many existing techniques focus on identifying specific tampering techniques, which limits their applicability in real-world scenarios. To ad...

International Journal of Intelligent Systems

Background: Over the past few decades, the process and methodology of automated question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models (LLMs...

Idiomatic expressions are an integral yet challenging aspect of language learning, often presenting difficulties due to their figurative nature and cultural specificity. This study explores the internal and external challenges learners face in understanding and using idioms, including issues of semantic opacity, cultural dependencies, and native la...

Language and consequently the ability to transmit and spread complex information is unique to the human species. The disruptive event of the introduction of large language models has shown that the ability to process language alone leads to incredible abilities and, to some extent, to intelligence. However, how language is processed in the human br...

Integrating watermarking into the generation process of latent diffusion models (LDMs) simplifies detection and attribution of generated content. Semantic watermarks, such as Tree-Rings and Gaussian Shading, represent a novel class of watermarking techniques that are easy to implement and highly robust against various perturbations. However, our wo...

Visual Anomaly Detection (VAD) aims to identify abnormal samples in images that deviate from normal patterns, covering multiple domains, including industrial, logical, and medical fields. Due to the domain gaps between these fields, existing VAD methods are typically tailored to each domain, with specialized detection techniques and model architect...

Since the seminal work by David Dowty, much inspired by the earlier ideas of Generative Semantics, a number of proposals have been developed accounting for the internal constitution and interpretation of accomplishment event predicates like ‘open the door’ or ‘break the window’. Current theories of accomplishment event structure vary along a number...

Zero-shot learning enables models to generalize to unseen classes by leveraging semantic information, bridging the gap between training and testing sets with non-overlapping classes. While much research has focused on zero-shot learning in computer vision, the application of these methods to environmental audio remains underexplored, with poor perf...

We introduce Generalizable 3D-Language Feature Fields (g3D-LF), a 3D representation model pre-trained on large-scale 3D-language dataset for embodied tasks. Our g3D-LF processes posed RGB-D images from agents to encode feature fields for: 1) Novel view representation predictions from any position in the 3D scene; 2) Generations of BEV maps centered...

We examine the text-free speech representations of raw audio obtained from a self-supervised learning (SSL) model by analyzing the synthesized speech using the SSL representations instead of conventional text representations. Since raw audio does not have paired speech representations as transcribed texts do, obtaining speech representations from u...

A conventional content‐based image retrieval system (CBIR) extracts image features from every pixel of the images, and its depiction of the feature is entirely different from human perception. Additionally, it takes a significant amount of time for retrieval. An optimal combination of appropriate image features is necessary to bridge the semantic g...

We present TokenFlow, a novel unified image tokenizer that bridges the long-standing gap between multimodal understanding and generation. Prior research attempt to employ a single reconstruction-targeted Vector Quantization (VQ) encoder for unifying these two tasks. We observe that understanding and generation require fundamentally different granul...

Natural scene text detection is a significant challenge in computer vision, with tremendous potential applications in multilingual, diverse, and complex text scenarios. A multilingual text detection model based on the Cascade Mask R-CNN is proposed to address the challenges of low accuracy and high difficulty in detecting multilingual text in natur...

Infrared small target detection technology has been widely applied in the defense sector, including applications such as precision targeting, alert systems, and naval monitoring. However, due to the small size of their targets and the extended imaging distance, accurately detecting drone targets in complex infrared environments remains a considerab...

CLIP has shown impressive results in aligning images and texts at scale. However, its ability to capture detailed visual features remains limited because CLIP matches images and texts at a global level. To address this issue, we propose FLAIR, Fine-grained Language-informed Image Representations, an approach that utilizes long and detailed image de...

El ensayo "La serpiente sagrada: un viaje a las raíces de la Medicina" analiza la confusión histórica entre el Caduceo de Mercurio, símbolo del comercio, y el Báculo de Asclepio, emblema legítimo de la medicina, explicando cómo un error originado en el siglo XVI, cuando un impresor alemán empleó el Caduceo en libros médicos, llevó a su adopción err...

Road asset management (RAM) is crucial in road construction and maintenance. Previous efforts have focused on the digitization of the physical state of road facilities, such as location and condition. However, the semantic information conveyed by these facilities, such as instructions, controls, and warnings, and the consistency of semantic informa...

The process of slur reclamation is a linguistic phenomenon whereby members of a targeted group begin to employ their own slur as a means of self-labelling, expressing pride, fostering camaraderie, and reversing the derogatory perspective of the slur. This action is designed to deprive racist and bigoted institutions of a means of perpetuating socia...

Exemplar-based semantic image synthesis aims to generate images aligned with given semantic content while preserving the appearance of an exemplar image. Conventional structure-guidance models, such as ControlNet, are limited in that they cannot directly utilize exemplar images as input, relying instead solely on text prompts to control appearance....

We propose an imperceptible multi-bit text watermark embedded by paraphrasing with LLMs. We fine-tune a pair of LLM paraphrasers that are designed to behave differently so that their paraphrasing difference reflected in the text semantics can be identified by a trained decoder. To embed our multi-bit watermark, we use two paraphrasers alternatively...

Video prediction, which is the task of predicting future video frames based on past observations, remains a challenging problem because of the complexity and high dimensionality of spatiotemporal dynamics. To address the problems associated with spatiotemporal prediction, which is an important decision-making tool in various fields, several deep le...

Uncertainty quantification in text-to-image (T2I) generative models is crucial for understanding model behavior and improving output reliability. In this paper, we are the first to quantify and evaluate the uncertainty of T2I models with respect to the prompt. Alongside adapting existing approaches designed to measure uncertainty in the image space...

Semantic correspondence, the task of determining relationships between different parts of images, underpins various applications including 3D reconstruction, image-to-image translation, object tracking, and visual place recognition. Recent studies have begun to explore representations learned in large generative image models for semantic correspond...

In his precritical period Kant developed a demonstration of the existence of God that he believed to be the only possible one. Whether this argument is valid is a much-disputed question. To give an answer to this question I will reconstruct Kant’s argument with the means of modern logic and semantics and show which are—in my view—it’s weak points....

Deep learning approaches, utilizing Bidirectional Encoder Representation from Transformers (BERT) and advanced fine-tuning techniques, have achieved state-of-the-art accuracies in the domain of term extraction from texts. However, BERT presents some limitations in that it primarily captures the semantic context relative to the surrounding text with...

RGB-D semantic segmentation utilizes both images and depth maps to classify pixels into different semantic classes. Currently, most methods rely on scale interaction within a single modality or the late fusion of dual-modal information, with little exploration of the correlation between two modalities at the same scale. There is also limited resear...

Traditional multimodal contrastive learning brings text and its corresponding image closer together as a positive pair, where the text typically consists of fixed sentence structures or specific descriptive statements, and the image features are generally global features (with some fine-grained work using local features). Similar to unimodal self-s...

We define a Kripke semantics for a conditional logic based on the propositional logic \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsf{N4}$$\end{document}, the p...

Logical reasoning tasks are more challenging than traditional machine reading comprehension tasks. The machine must recognize the logical relationships implicit in the text and use logical reasoning to derive an answer. Logical reasoning tasks currently face two major challenges. The first challenge is the difficulty of capturing the logical relati...

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. Recent research has predominantly focused on using LLMs to classify text as either human-written or machine-generated. In our study, we...

Recent advancements in large vision-language models (LVLM) have significantly enhanced their ability to comprehend visual inputs alongside natural language. However, a major challenge in their real-world application is hallucination, where LVLMs generate non-existent visual elements, eroding user trust. The underlying mechanism driving this multimo...

Colorectal polyps are structural abnormalities of the gastrointestinal tract that can potentially become cancerous in some cases. The study introduces a novel framework for colorectal polyp segmentation named the Multi-Scale and Multi-Path Cascaded Convolution Network (MMCC-Net), aimed at addressing the limitations of existing models, such as inade...

We study the localization properties of bipartite channels, whose action on a subsystem yields a unitary channel. In particular we show that, under such channel, the subsystem must evolve independent of its environment. This point of view is another way to verify certain well-known conservation laws of quantum information in a generalized way. A no...

The proposed paper aims to conduct a corpus-driven examination of the eighteenth-century English vocabulary used in various types of medical texts such as treatises, recipes, regimens, surgical texts, etc. It is argued that formulaicity in medical jargon depended on the text type. We focus on binomials, defined as "words or phrases belonging to the...

The “Naturalistic Free Recall” dataset provides transcribed verbal recollections of four spoken narratives collected from 229 participants. Each participant listened to two stories, varying in duration from approximately 8 to 13 minutes, recorded by different speakers. Subsequently, participants were tasked with verbally recalling the narrative con...

This paper discusses the representation of ontologies in the first-order logical environment FOLE. An ontology defines the primitives with which to model the knowledge resources for a community of discourse. These primitives consist of classes, relationships and properties. An ontology uses formal axioms to constrain the interpretation of these pri...

Adjectives with the borrowed head constituent like are a previously undescribed phenomenon in German. This corpus-based study shows that they occur frequently in certain text sources and analyses them as a productive word-formation pattern. The article describes the morphological, syntactic, graphemic, semantic, and pragmatic properties of these ad...

This paper discusses the representation of ontologies in the first-order logical environment FOLE. An ontology defines the primitives with which to model the knowledge resources for a community of discourse. These primitives consist of classes, relationships and properties. An ontology uses formal axioms to constrain the interpretation of these pri...

This paper discusses the representation of ontologies in the first-order logical environment FOLE (Kent [11]). An ontology defines the primitives with which to model the knowledge resources for a community of discourse (Gruber [7]). These primitives, consisting of classes, relationships and properties, are represented by the entity-relationship-att...

The fundamental task of zero-shot skeleton-based action recognition is to learn existing skeletal actions during the training phase and to accurately identify unseen actions during the inference phase. The key challenge lies in effectively unifying skeletal features and semantic features. Traditional zero-shot skeleton recognition methods often emp...