This paper mainly explores the cognitive renewal linguistic data science brings to linguistic inquiry and its theoretical connotations. Building on a concise overview of dataology and existing language data studies, this paper focuses on the discussion of five core issues concerning language data science: the theoretical nature of language data science as a subdiscipline, theoretical considerations underlying its disciplinary construction, the theoretical necessity of introducing this subdiscipline into the academic field, the cognitive renewal it introduces to linguistic inquiry, and its theoretical connotations. In brief, this paper primarily addresses two central issues: First, language data science reshapes modern linguistic understandings of the relationship between language and data, as well as the conceptual nature of “language data”. Second, grounded in a reconceptualization of “language data”, this paper outlines the major theoretical connotations of Language Data Science from five dimensions.

The Plain English Movement has prompted major English-speaking countries to introduce language policies advocating the simplification of legislative English. However, this corpus-based study shows that traditional linguistic features—such as archaic words, loanwords and redundant expressions—still persist to varying degrees in the legislative texts of these countries, indicating that the Plain English Movement has not fundamentally altered the opacity and complexity of legislative language. The English versions of Chinese legislative texts not only exhibit these features but do so with even greater frequency than those in English-speaking countries. This paper argues that the overseas dissemination of Chinese law should pursue genuine simplification so as to better meet the expectations of English-speaking audiences regarding legal language.

The interaction of grammar and pragmatics has long been a central concern in the field of linguistics. Among the various accounts, Ariel’s “code and inference” model of grammar-pragmatics interaction is rather representative and influential. This paper aims to elucidate and critically review her model by highlighting its three key theoretical contributions: (1) relying on one single criterion—code versus inference—to distinguish grammar and pragmatics, or to delineate their division of labour; 2) integrating both diachronic and synchronic dimensions to explain grammar-pragmatics interaction; (3) proposing three innovative concepts—grammatical pragmatics, truth-compatible inference, and privileged interactional interpretation—to capture the dynamics of how grammar interacts with pragmatics. However, Ariel’s model is found to be limited as well: the dichotomy of code and inference does not fully uncover the complexity of the grammar-pragmatics interactive relationship, the strict binary distinction or opposition between code and inference is too absolute, and tends to marginalize or even disregard the conventional dimension of pragmatic analysis. Therefore, we propose to moderately modify the code-inference dichotomy and replace it with conventionality and intentionality, which we argue provides a more nuanced and comprehensive explanation of the grammar-pragmatics interaction.

The study of ordinary audience reception has gained momentum due to the rise of international communication in the new media era. Social media amplify individuals’ voices, infused with emotions and sensitivity, making it essential to analyze audience reception through the lens of emotional analysis and to reconsider international communication from a reversed perspective. Based on comments about “Ne Zha” on digital platforms within the English-speaking world, this study finds that audiences generally provide highly positive evaluations, expressing a wide range of positive emotions and creating an enthusiastic public discourse centered on Chinese mythology, storylines, and the game characters of “Ne Zha”. However, it also reveals that translation issues affect the audience’s expectations for a linear and smooth experience and have emerged as a primary source of negative emotions among English-speaking audiences. The article further explores the impact of emotions on international communication through dimensions such as attention allocation, decision-making processes, and memory reinforcement. Analyzing audience reception from an emotional perspective not only enhances our understanding of ordinary people’s engagement in reception theory but also sheds significant light on promoting Chinese culture going abroad.

This study employs Fairclough’s three-dimensional discourse analysis model as its theoretical framework to examine 278 reports on the Belt and Road Initiative (BRI) published between 2013 and 2025 in Argentina’s mainstream media, including Clarín, La Nación, and Página 12. The analysis explores the reporting frameworks and tendencies regarding the BRI in the Argentine context. The findings indicate that, among the Spanish translations of the Belt and Road Initiative (BRI) in Argentine mainstream media, “la Franja y la Ruta” and “Nueva Ruta de la Seda” are the most frequently used; the Spanish translations of the BRI in Argentine media have gradually aligned with the official Chinese translation, “la Franja y la Ruta”, which has shown the highest growth rate in usage; the media primarily focuses on the BRI’s strategic objectives, economic vision, as well as its diplomatic and geopolitical implications; overall, Argentine media coverage of the BRI tends to be neutral and objective.

Drawing on the pioneering experience of foreign language studies in cultivating talents for country and region studies and grounded in systems theory, this study integrates a bottom-up literature analysis and expert interviews with a top-down deductive analysis to construct a “concave-convex” competency model for talents in country and region studies. The model encompasses six core competencies — linguistic competence, intercultural competence, academic research competence, interdisciplinary competence, international communication competence, and policy advisory competence — which are further elaborated into 16 sub-competencies and 48 qualitative indicators. Meanwhile, the study reveals the dynamic relationships within the “concave-convex” competency model across different structural dimensions, thereby providing theoretical reference and practical guidance for the cultivation of postgraduate students in country and region studies.

By means of the McGurk effect experiment, this study took native Chinese speakers, Arabic and Thai Chinese learners as research objects to explore the audiovisual perception performance of second language learners with different native language backgrounds. The results show that there are significant differences in the audiovisual perception tendencies of those with different native language backgrounds; the native phonetic categories of learners and the phonetic similarity between the native language and the second language will affect their responses to audiovisual stimuli and further influence the reported results of audiovisual perception. The audiovisual perception tendencies of second language learners are related to the clarity and reliability of auditory stimuli. This study will provide a new perspective for understanding the audiovisual perception effects under different native language backgrounds and the research on the relationship between second language acquisition production and perception.

This paper explores the potential applications of Large Language Models (LLMs) in college English teaching and aims to provide research references and practical insights. Five cross-scenarios of LLMs are demonstrated, namely, the optimization of vocabulary, grammar, reading, speaking, and writing teaching links, using Intermediate College English for New Era (Book 2) as a case study. It is found that LLMs enable dynamic categorization of thematic vocabulary and multimodal visualization to construct semantic fields, thereby reinforcing students’ associative vocabulary learning; through error-generation mechanisms and comparative text analysis, they facilitate targeted instruction of grammatical rules with hierarchical training adaptations; by implementing sentiment scale segmentation and implicit narrative tracking, they foster the development of critical thinking and empathetic reasoning competencies; when integrated with speech recognition technology, they permit objective evaluation of oral proficiency metrics; their generative revision mechanisms effectively enhance textual coherence in writing outputs. Leveraging deep semantic comprehension and generative capacities, LLMs significantly optimize the precision and efficiency of language knowledge acquisition and skill development in educational contexts.

This study employs two multi-million-word corpora of comparable translated and non-translated/original English texts to examine the “source language shining-through” effect. Utilizing machine learning techniques to analyze 96 linguistic features, it compares translations from various source languages across multiple registers. The results reveal that (1) translated English consistently differs from original English, regardless of source language; (2) language status exerts a greater influence on the shining-through effect than typological distance; and (3) language status and typological distance interact competitively across registers. These findings advance our understanding of translation universals and provide theoretical guidance for translators seeking to adapt effectively to source language typology, language status, and register-specific demands.

Drawing on Walter Benjamin’s early philosophy of translation as its theoretical framework, this paper examines how Paul Auster’s experience of translating French poetry and theoretical works profoundly shapes the composition of The New York Trilogy. Through the practice of translation, Auster develops a deepening awareness of the complex interplay among language, meaning, and silence, which gives rise to the distinctive linguistic consciousness and philosophical preoccupations that pervade his fiction. This paper illustrates how Auster’s dual identity as writer and translator contributes to the formation of his literary style, and argues for the intrinsic interconnectedness between translation and original creation. It ultimately demonstrates that translation serves as a crucial means through which Auster interrogates the nature of language itself and expands the possibilities of literary expression through his literary career.

The emergence of Generative Artificial Intelligence (GenAI) has reshaped the interpreting practice and imposed new demands on interpreter competence. Consequently, interpreter training in higher education requires systematic reform to meet the challenge. This paper first reviews the conceptual origins and core components of interpreter competence. On this basis, it identifies three key elements for upgraded interpreter competence: improved interpreting skills, expanded technological capabilities, and updated professional qualities. The paper then discusses how interpreter training in higher education can be reformed in light of the upgraded competence. It proposed the enrichment of curriculum design and teaching content, and the optimization of training progression and arrangements so as to reflect the complex and dynamic nature of interpreter competence. At the same time, greater emphasis should be placed on higher-order thinking abilities. This study aims to provide insights for interpreter training and the sustainable professional development of interpreters in the GenAI era.

This study investigates the impact of machine translation on the cognitive decision-making processes of translators from the perspective of information searching. The study has compared and analyzed the information searching process of machine translation post-editing and human translation. Key-logging tool Translog II and screen recording of BB FlashBack Pro 5 were used, supplemented with pre- and post-test questionnaires. The study focused on three dimensions: time allocation during processing, information search patterns, and translation quality. The findings show that: (1) machine translation post-editing saves translators’ time on information search but requires more time for the planning stage; (2) the number of information-searching instances in post-editing was lower than those in human translation, with search behaviors primarily focused on semantic retrieval of vocabulary; (3) the quality of post-editing quality is better than that of manual translation. Translation learners hold a positive attitude towards the use of machine translation, as machine translation helps in resolving vocabulary searching. The findings provide empirical support and useful reference points for optimizing information search in translation and advancing the reform of machine translation post-editing.

Through authentic book reviews as a source of humanism, an interactive AI-based application, capable of generating customized and personified evaluation, is thus produced focusing on multiple dimensions. According to comparative analysis with existing GenAI-based evaluation results, this study demonstrates that by assigning a human-like “evaluator” role to artificial intelligence, the application-centered assessment model developed in this study creates translation evaluations that are aligned to human readers’ preferences, thereby exhibiting distinctive humanistic appeal compared to traditional models. This research aims to improve the translation quality of Internet literature in English and provide linguistic support for its international dissemination.