Hasil untuk "Style. Composition. Rhetoric"

L. Jansen

The present discussion examines the state of affairs with regard to Cassius Dio’s place in the Greek and Roman historiographical tradition. While Dio’s narrative composition and his political thought have been reevaluated as essential parts of his historiographical method, the study of literary aspects such as style, rhetoric, and intertextuality is still in its infancy. Closer attention to the way in which style and content are related is necessary in order to fully appreciate Dio’s intellectual project.

Mandar Marathe

Arabic Rhetoric is the field of Arabic linguistics which governs the art and science of conveying a message with greater beauty, impact and persuasiveness. The field is as ancient as the Arabic language itself and is found extensively in classical and contemporary Arabic poetry, free verse and prose. In practical terms, it is the intelligent use of word order, figurative speech and linguistic embellishments to enhance message delivery. Despite the volumes that have been written about it and the high status accorded to it, there is no way to objectively know whether a speaker or writer has used Arabic rhetoric in a given text, to what extent, and why. There is no objective way to compare the use of Arabic rhetoric across genres, authors or epochs. It is impossible to know which of pre-Islamic poetry, Andalucian Arabic poetry, or modern literary genres are richer in Arabic rhetoric. The aim of the current study was to devise a way to measure the density of the literary devices which constitute Arabic rhetoric in a given text, as a proxy marker for Arabic rhetoric itself. A comprehensive list of 84 of the commonest literary devices and their definitions was compiled. A system of identifying literary devices in texts was constructed. A method of calculating the density of literary devices based on the morpheme count of the text was utilised. Four electronic tools and an analogue tool were created to support the calculation of an Arabic text's rhetorical literary device density, including a website and online calculator. Additionally, a technique of reporting the distribution of literary devices used across the three sub-domains of Arabic rhetoric was created. The output of this project is a working tool which can accurately report the density of Arabic rhetoric in any Arabic text or speech.

Raghu Vamsi Chittersu, Yuvraj Singh Rathore, Pranav Adlinge et al.

Reference-based object composition methods fail when inserting real-world objects into stylized domains. This under-explored problem is currently split between practical "blenders" that lack generative fidelity and "generators" that require impractical, per-subject online finetuning. In this work, we introduce Insert In Style, the first zero-shot generative framework that is both practical and high-fidelity. Our core contribution is a unified framework with two key innovations: (i) a novel multi-stage training protocol that disentangles representations for identity, style, and composition, and (ii) a specialized masked-attention architecture that surgically enforces this disentanglement during generation. This approach prevents the concept interference common in general-purpose, unified-attention models. Our framework is trained on a new 100k sample dataset, curated from a novel data pipeline. This pipeline couples large-scale generation with a rigorous, two-stage filtering process to ensure both high-fidelity semantic identity and style coherence. Unlike prior work, our model is truly zero-shot and requires no text prompts. We also introduce a new public benchmark for stylized composition. We demonstrate state-of-the-art performance, significantly outperforming existing methods on both identity and style metrics, a result strongly corroborated by user studies.

Haowen Li, Zhenfeng Fan, Zhang Wen et al.

Image composition has advanced significantly with large-scale pre-trained T2I diffusion models. Despite progress in same-domain composition, cross-domain composition remains under-explored. The main challenges are the stochastic nature of diffusion models and the style gap between input images, leading to failures and artifacts. Additionally, heavy reliance on text prompts limits practical applications. This paper presents the first cross-domain image composition method that does not require text prompts, allowing natural stylization and seamless compositions. Our method is efficient and robust, preserving the diffusion prior, as it involves minor steps for backward inversion and forward denoising without training the diffuser. Our method also uses a simple multilayer perceptron network to integrate CLIP features from foreground and background, manipulating diffusion with a local cross-attention strategy. It effectively preserves foreground content while enabling stable stylization without a pre-stylization network. Finally, we create a benchmark dataset with diverse contents and styles for fair evaluation, addressing the lack of testing datasets for cross-domain image composition. Our method outperforms state-of-the-art techniques in both qualitative and quantitative evaluations, significantly improving the LPIPS score by 30.5% and the CSD metric by 18.1%. We believe our method will advance future research and applications. Code and benchmark at https://github.com/sherlhw/AIComposer.

Qiuyi Qi, Xin Li, Ming Kong et al.

Challenges such as the lack of high-quality annotations, long-tailed data distributions, and inconsistent staining styles pose significant obstacles to training neural networks to detect abnormal cells in cytopathology robustly. This paper proposes a style-aligned image composition (SAIC) method that composes high-fidelity and style-preserved pathological images to enhance the effectiveness and robustness of detection models. Without additional training, SAIC first selects an appropriate candidate from the abnormal cell bank based on attribute guidance. Then, it employs a high-frequency feature reconstruction to achieve a style-aligned and high-fidelity composition of abnormal cells and pathological backgrounds. Finally, it introduces a large vision-language model to filter high-quality synthesis images. Experimental results demonstrate that incorporating SAIC-synthesized images effectively enhances the performance and robustness of abnormal cell detection for tail categories and styles, thereby improving overall detection performance. The comprehensive quality evaluation further confirms the generalizability and practicality of SAIC in clinical application scenarios. Our code will be released at https://github.com/Joey-Qi/SAIC.

Sebastiano Taddei, Mattia Piccinini, Francesco Biral

In this work, we present a novel approach to bias the driving style of an artificial race driver (ARD) for online time-optimal trajectory planning. Our method leverages a nonlinear model predictive control (MPC) framework that combines time minimization with exit speed maximization at the end of the planning horizon. We introduce a new MPC terminal cost formulation based on the trajectory planned in the previous MPC step, enabling ARD to adapt its driving style from early to late apex maneuvers in real-time. Our approach is computationally efficient, allowing for low replan times and long planning horizons. We validate our method through simulations, comparing the results against offline minimum-lap-time (MLT) optimal control and online minimum-time MPC solutions. The results demonstrate that our new terminal cost enables ARD to bias its driving style, and achieve online lap times close to the MLT solution and faster than the minimum-time MPC solution. Our approach paves the way for a better understanding of the reasons behind human drivers' choice of early or late apex maneuvers.

Yaser Ali Hakçioğlu

The Holy Quran is the miraculous book that has left both humans and jinn in awe. It even challenged the Arabs, the masters of eloquence and rhetoric. This was due to its exceptional style, eloquent vocabulary, precise meanings, and beautiful composition, and diverse themes— qualities beyond human capability. One of the most remarkable aspects of the Quran’s miraculous nature is its unique style in presenting ideas and issues. The Quran’s style is harmonized with both reason and emotion, aligning with the context in which its speech is delivered. Its expressions perfectly match the situation for which the words were revealed. The styles of the Quran possess an extraordinary ability to express various states and circumstances, considering all contextual factors. This highlights its rhetorical inimitability, which even the most eloquent Arab poets and literary figures could not rival. The Quran’s styles vary depending on the context of the verses and the conditions of the audience. Sometimes, the situation necessitates the use of indefinite nouns or placing the predicate before the subject. In other instances, the conditions of the audience require definiteness, indefiniteness, omission, or the use of implicit references for the subject or predicate. This diversity in style is never arbitrary but is always guided by contextual indicators. This is why the Quran’s style is unique in its composition and profound in its presentation. Among the distinguished and eloquent styles found in the Quran is the rhetorical device of preposing (taqdim)—a stylistic choice that aligns with the intended meaning and the state of the audience. In the Quran, preposing only occurs when the intended meaning cannot be achieved without it. Similarly, postponement (ta’khir) occurs only when the intended meaning requires it. This stylistic technique is one of many found in the Quran, encompassing numerous rhetorical secrets and accompanying meanings. It is also present in both classical Arabic poetry and prose. In the Quran, this style appears in various contexts, carrying profound rhetorical and semantic significance. It often deviates from the conventional word order of Arabic sentences, serving specific rhetorical purposes. This stylistic feature is a mark of skilled literary expression, and writers and poets vary in their ability to employ it effectively. The Quran masterfully employs this technique as a means of unveiling specific meanings and rhetorical purposes that cannot be conveyed through any other structure. This study highlights the aesthetic value of this technique by examining its connection to context. There is a strong correlation between preposition in the Quran and the context in which it.

Clara Lechowski, Alexander Slotkin

This article introduces and explores a cultural rhetorics project created by Clara Lechowski, a then-senior English Education major, with guidance from Alexander Slotkin, an Assistant Professor of Rhetoric and Composition. Clara’s honors project—a zine-style cookbook—blends storytelling, family history, and culinary tradition, code-meshing Polish and English to reflect the author’s Polish American identity. We situate Clara’s work within the pedagogical framework of the course in which it originated and present her zine as a model for culturally responsive writing practices. Her zine not only showcases recipes from her community but also serves as a rhetorical space where cultural identity, memory, and writing intersect. By sharing this work, we invite educators and students to see writing as a means of honoring and engaging with their own home communities.

Roberto S. Leon

Abstract:This article adds to readings of Book Two of Desiderius Erasmus's De duplici copia rerum ac verborum commentarii duo that emphasize the relationship of the rationes locupletandi to style and invention by re-reading this text with an eye toward structural invention. In doing so, this paper explores Erasmus's use of the Rhetorica ad Herennium and Quintilian's Institutio oratoria, as well as observations by Erasmus's contemporaries, to consider the extent to which the composition of Book Two may have been influenced by structural invention.

Mahboubeh Moslemizadeh

Introduction One of the most prominent rhetorical techniques is metaphor, which is used not only in literary poetry and prose, but also in everyday speech, knowingly and unknowingly, and helps the elegance and beauty of speech. This technique, along with other rhetorical techniques, reached its peak in the 9th century A.H, the period of popularization of the Herat style, followed by the Hindi style. One of the authors and writers whose works have stylistic characteristics of this period is Molla Hossain Va'ez Kashifi. Badai' al-Afkar and 'Anwar-e Sohaili are among his most important works which are going to be analyzed in this article.  Methodology This study is based on the descriptive analysis method by using library research and studying Bada'i al-Afkar and Anwar Sohaili by Va'ez i Kashifi for analyzing different types of metaphors in these prominent works. Through this study, different definitions of metaphor are presented. Then the author and his works are introduced and a brief description of their content and features is given. This research attempts to answer the following questions:  What is Va'ez i Kashifi's innovation in metaphors? How has Va'ez i Kashifi combined different semantic areas in the form of his metaphors? The examples in this study are from these books: Bada'i al-Afkar and Anwar Sohaili. Discussion Bada'i al-Afkar fi Sanyaye' al-Ashaar, written by the famous 9th century scholar Kamaluddin Hossein Vaez Kashifi Sabzevari, is the most extensive and informative rhetorical book in Persian rhetoric; The value of Bada'i al-Afkar lies in the fact that the author has extensively studied the figures of speech in Persian literature and has explored more what was briefly mentioned in the previous books and has obtained new uses and examples in many of the figures. Also, in this book, we come across the figures of speech that are not mentioned in other rhetoric books, even the books at the same time. However, in writing these books, Va'ez Kashifi benefited from the previous works, especially from Shams Qais Razi's Al-Mu'ajm, and according to Zabihullah Safa, it is a re-writing of Shams Qais Razi's Al-Mu'ajm, except for the science of prosody.Anwar Sohaili is one of Kashifi's most famous works and a new writing of Kalila and Damna, which he composed in the name of Sheikh Ahmad Sohaili, one of the rulers of the reign of Sultan Hossein Mirzai Baiqara, in fourteen chapters and an introduction, and although Kashifi wanted to simplify its composition,but he couldn't. Kashifi's writing style, wherever is not under the influence of another text or translation or citation of Arabic language, is simple and fluent and is among the good works of the 9th century and the beginning of the 10th century A.H. In this rewriting, he made many changes in the content and even the title of Kalileh and Demaneh.By studying Badai' al-Afkar and Anwar Sohaili of Va'ez Kashifi, it is understood that Kashfi wanted to show something innovative and beyond the writings of his predecessors, and he was able to do so to some extent with the influence of the works he considered.This article aims to answer the following questions: What is Va'ez Kashifi's innovation in metaphors? How has Va'ez Kashefi combined different semantic fields in the form of his metaphors? Hypotheses are that Kashefi's innovation is the combination of multiple and different semantic fields; Kashefi has expanded different semantic fields in metaphors with hindsight towards metaphor and innovation in examples. Conclusion The findings show that Kashefi, despite modeling the writings of his predecessors, has made innovations in the use of metaphor by combining multiple and distant semantic fields, this means that the abstract noun is combined with a verb related to the concrete noun in order to make a subordinate metaphor to express "the passing of youth" and by simile and genitive metaphor, it mixes the distant meanings with the subordinate metaphor, personification, appositive and metaphorical genitives; On the other hand, by mixing metaphorical attribution genitive, metonymy, implied metaphor, personification, subordinate metaphor and semantic paradox, a complex network of metaphors and other figures of speech are interwoven with these semantic fields.

Michael A. Gilbert, Linda Carozza

Michael A. Gilbert a apporté une contribution significative à la théorie contemporaine de l’argumentation. Ses apports les plus remarquables résident dans sa théorie multimodale de l’argumentation et dans sa théorie de l’argumentation dite « coalescente », des modèles novateurs qu’il a développés pour étudier la façon dont les interlocuteurs discutent réellement dans la vie courante. Ses idées n’ont pas toujours été comprises, appréciées ou reconnues par l’ensemble de la communauté des spécialistes d’argumentation. Néanmoins, récemment, le Centre for Research in Reasoning, Argumentation and Rhetoric (en Ontario, au Canada) a reconnu l’importance de sa contribution en organisant un institut d’une semaine entière consacré à ses travaux. Aussi provocantes que puissent paraître ses théories, les spécialistes de la rhétorique n’en peuvent pas moins trouver un certain terrain d’entente avec ses travaux.

Verena Ingrid Prantl, Torsten Moeller, Laura Koesten

In contemporary discourse, logos (reason) and, more recently, ethos (credibility) in data communication have been discussed extensively. While the concept of Pathos has enjoyed great interest in the VIS community over the past few years, its connection to similar but relevant concepts like aesthetics and rhetoric remains unexplored. In this paper, we provide definitions of these terms and explore their overlaps and differences in light of their historical development. Examining the historical perspective offers a deeper understanding of how these approaches in science and philosophy have evolved over time, offering a more comprehensive embedding into the design process and its role within it. Drawing from Campbell's seven circumstances, we illustrate how pathos is being used as a rhetorical device in data visualizations today, at times inadvertently.

Tian Yu Liu, Aditya Golatkar, Stefano Soatto

We introduce Tangent Attention Fine-Tuning (TAFT), a method for fine-tuning linearized transformers obtained by computing a First-order Taylor Expansion around a pre-trained initialization. We show that the Jacobian-Vector Product resulting from linearization can be computed efficiently in a single forward pass, reducing training and inference cost to the same order of magnitude as its original non-linear counterpart, while using the same number of parameters. Furthermore, we show that, when applied to various downstream visual classification tasks, the resulting Tangent Transformer fine-tuned with TAFT can perform comparably with fine-tuning the original non-linear network. Since Tangent Transformers are linear with respect to the new set of weights, and the resulting fine-tuning loss is convex, we show that TAFT enjoys several advantages compared to non-linear fine-tuning when it comes to model composition, parallel training, machine unlearning, and differential privacy. Our code is available at: https://github.com/tianyu139/tangent-model-composition

Stephen Bothwell, Justin DeBenedetto, Theresa Crnkovich et al.

Rhetoric, both spoken and written, involves not only content but also style. One common stylistic tool is $\textit{parallelism}$: the juxtaposition of phrases which have the same sequence of linguistic ($\textit{e.g.}$, phonological, syntactic, semantic) features. Despite the ubiquity of parallelism, the field of natural language processing has seldom investigated it, missing a chance to better understand the nature of the structure, meaning, and intent that humans convey. To address this, we introduce the task of $\textit{rhetorical parallelism detection}$. We construct a formal definition of it; we provide one new Latin dataset and one adapted Chinese dataset for it; we establish a family of metrics to evaluate performance on it; and, lastly, we create baseline systems and novel sequence labeling schemes to capture it. On our strictest metric, we attain $F_{1}$ scores of $0.40$ and $0.43$ on our Latin and Chinese datasets, respectively.

Emma McKay

Doing quantum ethics properly will require detailed socio-political analysis of the technologies and the organizations trying to build them. In this paper, I contribute to this task by analysing the public rhetoric of American military stakeholders in the quantum industry. I look at Air Force Research Laboratory involvement in the 2020 Quantum 2 Business conference, where they were the main sponsor. A critical thematic analysis shows a focus on enacting the violence of war, maintaining narratives that the Air Force provides a secure future for Americans, and marrying quantum technology with the aesthetics of war. I contextualize this with anti-imperialist theory, arguing that this rhetoric and the desire for quantum arms aligns with the reproduction of existing violent power structures. Insights about this example of military involvement in quantum spaces should help orient nascent critical quantum ethics interventions.

Chen Chen, Zeju Li, Cheng Ouyang et al.

Convolutional neural networks (CNNs) have achieved remarkable segmentation accuracy on benchmark datasets where training and test sets are from the same domain, yet their performance can degrade significantly on unseen domains, which hinders the deployment of CNNs in many clinical scenarios. Most existing works improve model out-of-domain (OOD) robustness by collecting multi-domain datasets for training, which is expensive and may not always be feasible due to privacy and logistical issues. In this work, we focus on improving model robustness using a single-domain dataset only. We propose a novel data augmentation framework called MaxStyle, which maximizes the effectiveness of style augmentation for model OOD performance. It attaches an auxiliary style-augmented image decoder to a segmentation network for robust feature learning and data augmentation. Importantly, MaxStyle augments data with improved image style diversity and hardness, by expanding the style space with noise and searching for the worst-case style composition of latent features via adversarial training. With extensive experiments on multiple public cardiac and prostate MR datasets, we demonstrate that MaxStyle leads to significantly improved out-of-distribution robustness against unseen corruptions as well as common distribution shifts across multiple, different, unseen sites and unknown image sequences under both low- and high-training data settings. The code can be found at https://github.com/cherise215/MaxStyle.

Chiara Molinari, Geneviève Bernard Barbeau

In November 2019, Simon Jolin-Barrette, Quebec minister responsible for the French language, revisited a controversy that had taken place two years earlier concerning the bilingual greeting bonjour/hi used in Montreal businesses, considered by some to reflect the decline of the French language in Quebec. The minister stated that he intended to ban the greeting in favor of the French ritual bonjour. In a conflicted sociolinguistic context such as Quebec’s, such assertions cannot go unnoticed. The announcement of Jolin-Barrette resounded in the media, where it provoked strong reactions to such an extent that a new polemic broke out. The aim of this article is to show how the reactions provoked, especially online, contributed to the deconstruction of the minister’s discourse and to its inability to impose itself as a discourse of authority. Our analysis focusses on the (techno)discursive modalities through which Jolin-Barrette’s authority is diminished or denied.

Carolina Sthefany Estrada Sanchez

Susana Reisz es licenciada en Letras por la Universidad de Buenos Aires (UBA) y doctora en Filología Clásica por la Universidad de Heidelberg (Alemania). Entre sus principales publicaciones, destacan Teoría literaria. Una propuesta (1986), Teoría y Análisis del Texto Literario (1989) y Voces sexuadas. Género y poesía en Hispanoamérica (1996); asimismo, artículos suyos han aparecido en revistas nacionales e internacionales. Sus líneas de investigación son amplias, a saber: teoría literaria, estudios de género, literatura fantástica, cultural studies, literatura clásica, estudios queer, autoficción, poesía hispanoamericana escrita por mujeres, entre otros.

Felix Petersen, Bastian Goldluecke, Oliver Deussen et al.

Reconstructing the 3D geometry of an object from an image is a major challenge in computer vision. Recently introduced differentiable renderers can be leveraged to learn the 3D geometry of objects from 2D images, but those approaches require additional supervision to enable the renderer to produce an output that can be compared to the input image. This can be scene information or constraints such as object silhouettes, uniform backgrounds, material, texture, and lighting. In this paper, we propose an approach that enables a differentiable rendering-based learning of 3D objects from images with backgrounds without the need for silhouette supervision. Instead of trying to render an image close to the input, we propose an adversarial style-transfer and domain adaptation pipeline that allows to translate the input image domain to the rendered image domain. This allows us to directly compare between a translated image and the differentiable rendering of a 3D object reconstruction in order to train the 3D object reconstruction network. We show that the approach learns 3D geometry from images with backgrounds and provides a better performance than constrained methods for single-view 3D object reconstruction on this task.

Reza Goroue, P. Golizadeh, Mokhtar Ebrahimi