Hasil untuk "Languages and literature of Eastern Asia, Africa, Oceania"

Indrambarya, Kitima

This study investigates how Thai speakers of different ages use the passive sentences with positive and negative verbs in adversative and non-adversative situations and shows the tendency of language variation in passive markers among speakers of different ages. Online questionnaires were collected from four age groups, namely, youths, early and late middle-aged speakers, and elderly. One of the results of the study shows that thùuk is the most frequent passive marker in Thai for speakers of all ages and confirms Prasithrathsint (2001)’s claim that thùuk is the generic passive marker and that doon is the adversative passive marker in Thai. The passive marker dâyráp, on the other hand, is limited in its use to passive sentences with favorable meanings. While the elderly Thai speakers in the study tend to maintain dâyráp in positive situations, the youths prefer thùuk for positive verbs and doon for negative verbs. In negative verbs with adversative situations, speakers of all age groups in the study prefer thùuk, except for the youths. The data for this study also suggests that the degrees of positivity and adversity of verbs in passive constructions could affect the choice of passive markers. Verbs with a higher degree of positivity have a higher tendency to occur with dâyráp, while verbs with a higher degree of adversity have a higher tendency to appear with the passive marker doon. The use of dâyráp and thùuk in speakers of different ages could reflect tendencies of language change, while the use of doon could point to age-grading.

Lucas C. Cordeiro, Matthew L. Daggitt, Julien Girard-Satabin et al.

Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while proper support from the programming language perspective has been considered secondary or unimportant. Yet, there is mounting evidence that insights from the programming language community may make a difference in the future development of this domain. In this paper, we formulate neural network verification challenges as programming language challenges and suggest possible future solutions.

Marcelo Arenas, Pablo Barceló, Luis Cofré et al.

Kleinberg and Mullainathan showed that language generation in the limit is always possible at the level of computability: given enough positive examples, a learner can eventually generate data indistinguishable from a target language. However, such existence results do not address feasibility. We study the sample complexity of language generation in the limit for several canonical classes of formal languages. Our results show that infeasibility already appears for context-free and regular languages, and persists even for strict subclasses such as locally threshold testable languages, as well as for incomparable classes such as non-erasing pattern languages, a well-studied class in the theory of language identification. Overall, our results establish a clear gap between the theoretical possibility of language generation in the limit and its computational feasibility.

Sampoorna Poria, Xiaolei Huang

Rapid developments of large language models have revolutionized many NLP tasks for English data. Unfortunately, the models and their evaluations for low-resource languages are being overlooked, especially for languages in South Asia. Although there are more than 650 languages in South Asia, many of them either have very limited computational resources or are missing from existing language models. Thus, a concrete question to be answered is: Can we assess the current stage and challenges to inform our NLP community and facilitate model developments for South Asian languages? In this survey, we have comprehensively examined current efforts and challenges of NLP models for South Asian languages by retrieving studies since 2020, with a focus on transformer-based models, such as BERT, T5, & GPT. We present advances and gaps across 3 essential aspects: data, models, & tasks, such as available data sources, fine-tuning strategies, & domain applications. Our findings highlight substantial issues, including missing data in critical domains (e.g., health), code-mixing, and lack of standardized evaluation benchmarks. Our survey aims to raise awareness within the NLP community for more targeted data curation, unify benchmarks tailored to cultural and linguistic nuances of South Asia, and encourage an equitable representation of South Asian languages. The complete list of resources is available at: https://github.com/trust-nlp/LM4SouthAsia-Survey.

Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz et al.

Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often results in artificial intelligence (AI) models that fail to capture SEA cultural nuances. To fill this gap, we present SEA-VL, an open-source initiative dedicated to developing high-quality, culturally relevant data for SEA languages. By involving contributors from SEA countries, SEA-VL aims to ensure better cultural relevance and diversity, fostering greater inclusivity of underrepresented languages in VL research. Beyond crowdsourcing, our initiative goes one step further in the exploration of the automatic collection of culturally relevant images through crawling and image generation. First, we find that image crawling achieves approximately ~85% cultural relevance while being more cost- and time-efficient than crowdsourcing. Second, despite the substantial progress in generative vision models, synthetic images remain unreliable in accurately reflecting SEA cultures. The generated images often fail to reflect the nuanced traditions and cultural contexts of the region. Collectively, we gather 1.28M SEA culturally-relevant images, more than 50 times larger than other existing datasets. Through SEA-VL, we aim to bridge the representation gap in SEA, fostering the development of more inclusive AI systems that authentically represent diverse cultures across SEA.

Jesus Alvarez C, Daua D. Karajeanes, Ashley Celeste Prado et al.

The digital exclusion of endangered languages remains a critical challenge in NLP, limiting both linguistic research and revitalization efforts. This study introduces the first computational investigation of Comanche, an Uto-Aztecan language on the verge of extinction, demonstrating how minimal-cost, community-informed NLP interventions can support language preservation. We present a manually curated dataset of 412 phrases, a synthetic data generation pipeline, and an empirical evaluation of GPT-4o and GPT-4o-mini for language identification. Our experiments reveal that while LLMs struggle with Comanche in zero-shot settings, few-shot prompting significantly improves performance, achieving near-perfect accuracy with just five examples. Our findings highlight the potential of targeted NLP methodologies in low-resource contexts and emphasize that visibility is the first step toward inclusion. By establishing a foundation for Comanche in NLP, we advocate for computational approaches that prioritize accessibility, cultural sensitivity, and community engagement.

Rafiu Adekoya Badekale, Adewale Akinfaderin

Climate policy scenario generation and evaluation have traditionally relied on integrated assessment models (IAMs) and expert-driven qualitative analysis. These methods enable stakeholders, such as policymakers and researchers, to anticipate impacts, plan governance strategies, and develop mitigation measures. However, traditional methods are often time-intensive, reliant on simple extrapolations of past trends, and limited in capturing the complex and interconnected nature of energy and climate issues. With the advent of artificial intelligence (AI), particularly generative AI models trained on vast datasets, these limitations can be addressed, ensuring robustness even under limited data conditions. In this work, we explore the novel method that employs generative AI, specifically large language models (LLMs), to simulate climate policy scenarios for Sub-Saharan Africa. These scenarios focus on energy transition themes derived from the historical United Nations Climate Change Conference (COP) documents. By leveraging generative models, the project aims to create plausible and diverse policy scenarios that align with regional climate goals and energy challenges. Given limited access to human evaluators, automated techniques were employed for scenario evaluation. We generated policy scenarios using the llama3.2-3B model. Of the 34 generated responses, 30 (88%) passed expert validation, accurately reflecting the intended impacts provided in the corresponding prompts. We compared these validated responses against assessments from a human climate expert and two additional LLMs (gemma2-2B and mistral-7B). Our structured, embedding-based evaluation framework shows that generative AI effectively generate scenarios that are coherent, relevant, plausible, and diverse. This approach offers a transformative tool for climate policy planning in data-constrained regions.

Ahmad Afandi, Muhammad Fadhlan, Ahmad Fikri et al.

The study aimed to explain the application of the Direct Method in Nahwu learning at the State University of Malang. It analyzed the supporting and inhibiting factors of the Direct Method in Nahwu learning at the State University of Malang and described student applications in Nahwu learning at the State University of Malang. This study used a descriptive design with a quantitative and qualitative approach to describe the application, supporting, and inhibiting factors of the Direct Method in Nahwu learning. The population in this study was the entire 5th-semester academic community (lecturers and students) of the Arabic language education study program, Faculty of Letters, State University of Malang. The sample in this study was selected using Purposive Sampling, with specific criteria for sampling. The model in this study was a student of the class of 2021 Arabic language education study program, Faculty of Letters, State University of Malang, who was taking the application Nahwu Tsanawi course. This lecturer taught the application Nahwu Tsanawi course. The results of this study showed that: 1) Student interest in learning Nahwu in the Arabic study program at the State University of Malang increased with the learning steps applied by lecturers, such as the delivery of themes, objectives, and learning materials by linking the new material to the previous material; 2) the innovation of the Direct Method used by teachers in Nahwu learning had a positive impact on students' understanding of Nahwu; 3) the use of the Direct Method in Nahwu learning was categorized as good, evidenced by the percentage of success reaching an average score of 83.3%; 4) the use of learning media by lecturers in Nahwu learning at the Arabic Language Education study program, State University of Malang, increased student interest in learning Nahwu. Based on the findings above, it is concluded that the innovation of the direct Method has a positive impact on students in learning Nahwu in the Arabic Language Study Program State University of Malang.

Ismaila Temitayo Sanusi, Fitsum Gizachew Deriba

Noticeably, Africa is underrepresented in the computing education research (CER) community. However, there has been some effort from the researchers in the region to contribute to the growing need for computing for all. To understand the body of works that emerged from the global south region and their area of focus in computing education, we conducted a systematic review of the literature. This research investigates the prominent CER journals and conferences to discern the kind of research that has been published and how much contribution they have made to the growing field. Of the 68 selected studies, 45 papers were from South Africa. The prominent aspect of computing in the literature is programming, which accounts for 43%. We identified open areas for research in the context and discussed the implication of our findings for the development of CER in Africa.

Angela Kluge

This paper describes serial verb constructions in Papuan Malay, an eastern Malay language, spoken in coastal West Papua, on the island of New Guinea. Papuan Malay employs serial verb constructions to encode complex events by means of verb sequences, or to express grammatical categories. However, the identification of Papuan Malay verb sequences as monoclausal serial verb constructions is often less than straightforward. This is due to the structure of Papuan Malay which is characterized by little productive morphology, no inflectional morphology, and the pervasive use of syntactic argument elision. In consequence, Papuan Malay multiverb constructions often have an indeterminate status; they could be interpreted as monoclausal serial verb constructions or as multiclausal chaining constructions with elided subject arguments. It is suggested here that the interpretation of such indeterminate verb sequences needs to be pragmatically inferred.

Paul Soulos, Sudha Rao, Caitlin Smith et al.

Machine translation has seen rapid progress with the advent of Transformer-based models. These models have no explicit linguistic structure built into them, yet they may still implicitly learn structured relationships by attending to relevant tokens. We hypothesize that this structural learning could be made more robust by explicitly endowing Transformers with a structural bias, and we investigate two methods for building in such a bias. One method, the TP-Transformer, augments the traditional Transformer architecture to include an additional component to represent structure. The second method imbues structure at the data level by segmenting the data with morphological tokenization. We test these methods on translating from English into morphologically rich languages, Turkish and Inuktitut, and consider both automatic metrics and human evaluations. We find that each of these two approaches allows the network to achieve better performance, but this improvement is dependent on the size of the dataset. In sum, structural encoding methods make Transformers more sample-efficient, enabling them to perform better from smaller amounts of data.

Joachim Tilsted Kristensen, Robin Kaarsgaard, Michael Kirkedal Thomsen

Algorithms are ways of mapping problems to solutions. An algorithm is invertible precisely when this mapping is injective, such that the initial problem can be uniquely inferred from its solution. While invertible algorithms can be described in general-purpose languages, no guarantees are generally made by such languages as regards invertibility, so ensuring invertibility requires additional (and often non-trivial) proof. On the other hand, while reversible programming languages guarantee that their programs are invertible by restricting the permissible operations to those which are locally invertible, writing programs in the reversible style can be cumbersome, and may differ significantly from conventional implementations even when the implemented algorithm is, in fact, invertible. In this paper we introduce Jeopardy, a functional programming language that guarantees program invertibility without imposing local reversibility. In particular, Jeopardy allows the limited use of uninvertible -- and even nondeterministic! -- operations, provided that they are used in a way that can be statically determined to be invertible. To this end, we outline an \emph{implicitly available arguments analysis} and three further approaches that can give a partial static guarantee to the (generally difficult) problem of guaranteeing invertibility.

I. L. Timonina

The socio-economic consequences of regional unevenness remain one of the major problems of Japan’s development in the 21st century. Despite some success in regional economic policy, the main quantitative indicators of territorial-economic proportions or lack thereof have changed little over the past 30 years despite certain successes of regional economic policy. However, a number of internal and external factors have made it necessary to adjust approaches to regional strategic planning. These include globalization and the changing positioning of Japan in the world market, the partial loss of competitive positions in Asian markets, and increased competition between “international” cities for foreign investment. Internal factors include the decline of the Japanese population at a rate higher than previously expected, changes in people’s lifestyles and shifts in their value system, the increasing importance of such of its components as stability, security, favorable environmental conditions, attractive landscapes, and diversification of lifestyles. The new strategy of the 21st century is based on the idea of creating a multilayered “compact and networked territorial structure”, which should ensure the availability of social services for residents of all localities by optimizing the social infrastructure and forming “new urban cores”. The economic development of regions should focus on the development of industries that rely on local resources and take into account local specifics, as well as the creation of “ecosystems” of innovations. Along with vitalizing regional and rural economy, Japan’s New Spatial Strategy also aims to adjust the excessive concentration of population and economic potential of large megacities (primarily Tokyo) and at the same time strengthen their global competitiveness. As necessary conditions for achieving the ambitious goals, the Spatial Development Strategy calls for achieving economic growth, increasing industrial productivity, building innovation through regional resources and interregional cooperation, increasing the participation of women and senior persons in work and public life, using modern “smart” technologies, and sharing economy formats. The traditional imperative in formulating Japan’s spatial development strategy remains the obvious desire to solve the problems of territorial unevenness in conjunction with solving other socio-economic problems of the country, in particular, the problems of environment and demographic decline (which is especially noticeable in the regions), issues of upgrading economic and social infrastructure.

Logan Emlet

Lidia Wojtczak

The Winding Ways of Poetry: Ratnaśrījñāna on Daṇḍin’s mārgas One of the earliest Sanskrit poeticians, Daṇḍin, dedicates an entire chapter of his Kāvyādarśa to the investigation of mārgas or the ‘ways’ of poetry. These are based on adaptable configurations of poetic qualities and faults and, although there seems to be an infinite number of ‘ways’, Daṇḍin characterises only two, Vaidarbha and Gauḍīya. In this paper, I show how the earliest known commentator of the Kāvyādarśa, Ratnaśrījñāna, uses philosophical discussions and archetypes to expand on Daṇḍin’s rather cursory engagement with the methodology of the ‘ways’ to create a truly śāstric schema.

Hiroshi Hasebe

The two figures who stood at the vanguard of the Japanese theatre world and maintained an international status during the 31 years of the Heisei era (1989-2018) are Ninagawa Yukio and Noda Hideki. Ninagawa Yukio was the most internationally successful of all the theatre directors who emerged during the post-war years. Ninagawa‘s productions were acclaimed not on account of their “Japonistic” and Orientalist tendencies, but precisely because of their lack of any clear national identity. The blend of heterogeneous cultures transcending differences between East and West introduced a universal dimension into the Shakespearean narrative. This was a deliberate strategy on Ninagawa’s part aimed at creating a global production. Noda Hideki showed much interest in performing overseas from early on in his career. He determined to surmount cultural barriers by not incorporating the Japanese language into the drama at any stage from the writing of the script to the stage presentation, with everything being conducted through the medium of English language. The European understanding of contemporary Japanese culture is becoming dominated by the concept of “Cool Japan”. This has brought the essence of Japanese culture as it was conceived prior to the introduction into Europe of animation and Japanese cuisine such as sushi back to the surface. By basing his work on the Nō theatre, with its origins in medieval times, Noda was striving to convey how the traditional Japanese aesthetic as typified by the concepts of yūgen, wabi and sabi has been handed down to present-day Japan.

K. R. Chowdhary

This paper attempts to connects the evolution of computer languages with the evolution of life, where the later has been dictated by \emph{theory of evolution of species}, and tries to give supportive evidence that the new languages are more robust than the previous, carry-over the mixed features of older languages, such that strong features gets added into them and weak features of older languages gets removed. In addition, an analysis of most prominent programming languages is presented, emphasizing on how the features of existing languages have influenced the development of new programming languages. At the end, it suggests a set of experimental languages, which may rule the world of programming languages in the time of new multi-core architectures. Index terms- Programming languages' evolution, classifications of languages, future languages, scripting-languages.

Armin Moin, Stephan Rössler, Marouane Sayih et al.

In this paper, we illustrate how to enhance an existing state-of-the-art modeling language and tool for the Internet of Things (IoT), called ThingML, to support machine learning on the modeling level. To this aim, we extend the Domain-Specific Language (DSL) of ThingML, as well as its code generation framework. Our DSL allows one to define things, which are in charge of carrying out data analytics. Further, our code generators can automatically produce the complete implementation in Java and Python. The generated Python code is responsible for data analytics and employs APIs of machine learning libraries, such as Keras, Tensorflow and Scikit Learn. Our prototype is available as open source software on Github.

Shem Miller

Ian Gibson

In Nepal’s public discourse, Christianity is often described as a divisive force, perhaps a plot by foreign powers to undermine the cohesion of Nepali society. In this article, I present ethnographic material from Bhaktapur suggesting that, at least with respect to family life, the social effects of conversion may often differ from this stereotypical picture. In Bhaktapur, I argue, conversion is more frequently a consequence of pre-existing conflicts within families than a source of new ones. Furthermore, in some contexts, the social, ethical, and ritual practices of Bhaktapurian churches can bring reconciliation to troubled families. In other contexts, conversion can heighten intrafamilial tensions, in particular through the commitment it brings to exclusivist theology. I explore how converts negotiate the conversion process and the tensions that precipitate and result from it, describing how familial power dynamics influence such negotiations. To give the reader a fleshed-out sense of the lived experience of Christian and part-Christian families in Bhaktapur, I give thick descriptions of the conversions of one church minister and his family, and of a church house fellowship in which post-conversion family tensions are discussed. Connecting this ethnography with wider research on Bhaktapurian Christianity, I delineate the competing forces at work in converts’ family lives. In light of the rapid growth of Christianity in Nepal, and the heated and sometimes violent nature of political responses to this, ethnographic research is urgently needed to examine not just the causes but also the longterm effects of Christian conversion; this will help to clarify whether patterns found in Bhaktapur are replicated elsewhere in the country.