A Nightmare on LLM s Street: On the Importance of Cultural Awareness in Text Adaptation for LRL s (2025)

Abstract: Large Language Models (LLMs) have revolutionized how we generate, interact with, and process language. Still, these models are biased toward WEIRD (Western, Educated, Industrialized, Rich, and Democratic) values. This bias is not merely linguistic but also cultural. Sociocultural contexts influence how people express ideas, interpret meaning, and communicate. In low-resource language settings, where data and cultural representation are limited, this issue becomes even more pronounced when models are applied without cultural adaptation, often leading to outputs that are irrelevant, inaccessible, or even harmful. In this paper, we argue for the importance of incorporating sociocultural context into LLMs. We review existing frameworks that explore culture in Natural Language Processing (NLP), and examine some work aimed at culturally aligning language models. As an illustrative scenario, we analyze the case of Guinea-Bissau. In this linguistically and culturally diverse country, Portuguese is the official language but not the primary means of communication for most of the population, highlighting the urgent need to adapt educational materials to the local sociocultural context. Finally, we propose a revised framework to address the challenge of adapting educational materials to diverse contexts, aiming to improve both the relevance and pedagogical impact of text adaptation.

## introduction large language models (llms) have revolutionized natural language processing (nlp), enabling widespread and seemingly universal interaction with artificial intelligence (ai) systems -perhaps for the first time. the abilities of llms to understand language rely not only on linguistic and factual knowledge, but also on an awareness of cultural nuances that shape human lives. however, these models are mostly trained on online data that is deeply rooted in a weird (western, educated, industrialized, rich, and democratic) worldview @xcite . because the majority of users who access these systems share, or are aligned with, that worldview, this creates a misleading impression that the models adequately represent and understand the world's linguistic and cultural diversity. in reality, a large portion of the world's population lives in profoundly different sociocultural contexts, with customs, norms, values, and shared knowledge that are not reflected in the data used to train these models. these elements, essential for contextual understanding, vary across cultural groups and are often not captured when nlp is built upon universalist assumptions. the problem is amplified when it comes to low-resource languages (lrls), whose cultural contexts are often overlooked, for which very few linguistic resources, annotated data, or corpora exist. it is estimated that there are over 7,000 languages in the world 1 , but only a small fraction are covered by llms. in light of this, although significant progress has been made in nlp, culture remains among the most challenging aspects of language that llms still struggle to handle effectively @xcite . a key difficulty lies in the absence of a shared definition of culture, which further complicates efforts to evaluate progress in this area @xcite . guinea-bissau represents a paradigmatic case of a country left behind in the global access to technology and quality education. this is exacerbated by two key factors. first, portuguese is the official language and the language of instruction in schools, yet only a minority of the population speaks it fluently. second, most people communicate in guinea-bissau creole, the lingua franca used in everyday life, which lacks official status and a standardized orthography. this paper sets out to argue for the urgent need to address the lack of cultural awareness in llms, identifying their limitations. it advocates for a more context-sensitive approach and explores how tackling these issues can help reduce social and linguistic inequalities in the case of guinea-bissau, by enabling the creation and adaptation of content that is both culturally relevant and linguistically appropriate. this paper should be understood as a position paper grounded in interdisciplinary perspectives from nlp, education, sociolinguistics, and cultural studies. our aim is not to present experimental results, but to outline conceptual and methodological directions for the culturally informed adaptation of texts in lrls settings. ## background and motivation our culture and our social relations shape everything we do. the way we present information, the style and tone we use, the context, and the common knowledge we share, among many other subtleties, are essential to effective communication. all of these are based on cultural knowledge. for the purpose of this paper, we adopt the definition of culture proposed by liu et al. @xcite , according to which culture encompasses: "the collective ideas, shared language, and social practices that emerge from and evolve through human social interactions within a society". messages that are not culturally adapted can be misinterpreted, and language technologies must account for cultural context to avoid potential harm @xcite . given its crucial role in making llms safer, fairer, and more inclusive, the concept of culture is receiving increasing attention in current research. one of the most important decisions when adapting texts, especially in translation, is deciding whether to aim for literalism or adaptation @xcite . cross-cultural translation and adaptation highlight this complexity, when the same literal meaning in one culture may be inappropriate in another, regardless of fluency @xcite , or when a direct counterpart in the target culture may not exist. when no direct counterpart exists in the target culture, appositives can be employed to provide contextual explanations. for example, the portuguese sentence "encontraram-se na queima das fitas" could be translated to english as "they met at the queima das fitas, a traditional portuguese academic celebration", where the appositive clarifies a culturally specific term that may be unfamiliar to the target audience. while many llms are capable of performing cultural adaptations effectively within weird contexts, they often exhibit biases that hinder their applicability in more culturally diverse settings. certain cultural variations can be identified through sociocultural elements, such as culture-specific items (csis) -including aspects of ecology (flora, fauna, climate, . . . ), material culture (food, clothing, housing, transportation, . . . ), emotions, and socially sensitive or taboo topics @xcite . yet, such categorizations are insufficient, particularly because culture is not a static inventory of features, but a dynamic and evolving construct. moreover, every communicative act is situated within a relational structure involving an emitter, a receiver, the medium through which the message is conveyed, and the broader sociocultural context in which it occurs -all of which shape the interpretation and appropriateness of the message. despite this growing awareness, many current approaches rely on language or national borders as proxies for cultural identity. however, this is problematic because significant cultural variation can exist within the same country or among countries that share a common language. for example, portugal and brazil speak the same language but differ considerably in cultural norms, values, and communicative practices. similarly, treating entire countries as culturally homogeneous units oversimplifies internal diversity. such categorical division risks minimizing cultural distinctions under a single label. although there is no common definition of culturally aware nlp, most works in this area share common goals. zhou et al. @xcite define the goals of culturally aware nlp as systems that are: adaptive: sensitive to specific cultural contexts when generating their outputs. discerning: not perpetuating reductive stereotypes. inclusive: perform well across a large number of cultures. nuanced: achieve depth through more granular and extensive cultural understanding. these four goals share common ground and, according to the authors, can be grouped into two distinct spaces. the first space combines the "adaptive" and "discerning" goals and reflects how systems should respond and when it is appropriate to do so. the second space includes the "inclusive" and "nuanced" goals, reflecting the desire for both broad cultural coverage and depth. for each of these spaces, there is often a trade-off. ## research on culturally aware nlp in this section, we first present key frameworks that aim to conceptualize culture in nlp. we then use the taxonomy proposed by liu et al. @xcite to organize and analyze recent research, highlighting how different cultural dimensions have been explored in the literature. ## contextual motivation: cultural adaptation of portuguese texts for guinea-bissau as discussed in the previous sections, llms face significant challenges when dealing with relevant cultural nuances -not only in identifying its presence, but also in reasoning about it and adapting content to culturally diverse contexts. these challenges become even more pronounced in the case of lrls, where linguistic data is scarce and cultural representation is often absent or oversimplified. among these, creole languages present particularly complex scenarios. when speakers of different languages need to communicate to carry out practical tasks but do not have the opportunity to learn one another's language, they develop a makeshift jargon called a pidgin @xcite . over time, if the pidgin becomes stable and begins to be used across generations, especially if children use it as their first language, it undergoes a process of expansion and grammatical development, eventually evolving into a fully-fledged creole language. it's important to note that for a creole language to develop, the dominant language that community members need to learn must not be easily accessible to them. despite their importance, little attention has been given to creoles in nlp @xcite . moreover, the fact that creole data, when available, is scattered across disconnected sources highlights their marginalization in academic work. guinea-bissau presents a unique sociolinguistic landscape where portuguese serves as the official language and the medium of instruc-tion in schools, yet only around 20% of the population understands it. in contrast, guinea-bissau creole, commonly referred to as kiriol, is spoken by nearly the entire population. for historical reasons, creole communities are almost always multilingual @xcite . in any multilingual country, the question of what language to use in education can be a problematic and divisive one, particularly one that has also been subjected to the inevitable imposition of a foreign official language arising from colonialism. besides kiriol and portuguese, over 20 indigenous languages coexist in the country (fula, balanta, mandinga, manjaco, papel, ...). in this context, kiriol functions as the lingua franca. kiriol is part of the upper guinea branch of portuguesebased creoles and is identified by the iso 639-3 code as pov foot_1 . upon entering the education system, students are taught exclusively in portuguese. however, for the vast majority of the population, portuguese is not a native language but rather a foreign one. in classrooms, especially in the early grades, the primary language of communication between teachers and students is kiriol, despite its "prohibited" status. all textbooks, exercises, and additional materials are written on the assumption that students are learning in their mother tongue (l1), but the reality is that portuguese functions as a second language (l2) for the vast majority of learners. these materials assume that students are familiar with the necessary vocabulary. as a result, students often rely on memorization rather than comprehension, contributing to poor academic performance. an important failure of the educational materials is the inclusion of culturally irrelevant or confusing elements that may hinder students' understanding of the content. for example, consider the following excerpts of a question of the 2023 second-phase final exam for mathematics applied to social sciences (11th grade) 3 : o josé e a irmã pediram uma pizza enquanto desfrutavam da piscina do navio de cruzeiro. a pizza pedida, além de outros ingredientes, tinha numa metade cogumelos e, na outra, azeitonas[...] admita que o preço da pizza é 42 euros. [...] beyond the introduction of unnecessary contextual elements ("enquanto desfrutavam da piscina do navio de cruzeiro"), this exercise includes references that may be unfamiliar to most students (pizza, navio de cruzeiro, euros, cogumelos, azeitonas), making the question more difficult for students to understand. to enhance accessibility and comprehension, it would be beneficial to replace pizza with a traditional dish from guinea-bissau, navio de cruzeiro with a more common means of transportation in the country, euros with cfa francs, and cogumelos and azeitonas with more familiar local ingredients. some proposed adaptations are illustrated in llms require enormous amounts of data. however, to date, no comprehensive corpus for kiriol exists. one of the very few datasets is available in rowe et al. @xcite . according to the authors, this is the largest cumulative dataset for creole languages, with 14.5m unique creole sentences with parallel translations. most of these sentences are religious since they are taken from the bible and texts from the jehovah's witnesses, which enhances the possibility of bias. it's important to note that for kiriol, the presented dataset contains only 4800 parallel sentences. another important consideration is that creoles are absent from most multilingual lms @xcite , and in google translate foot_3 only three creoles are considered: haitian creole, mauritian creole, and seychelles creole. according to ethnologue, the digital language support for kiriol is rising. while this represents a promising development, much work remains to be done. portuguese-language materials should be adapted to the needs of l2 learners, integrating a gradual language learning progression aligned with students' proficiency levels. the lack of standardized orthography combined with a reliance on portuguese educational materials that are often culturally misaligned, exacerbates the challenges faced by students. addressing this issue may require collaboration with local communities, linguists, and educators to co-develop language resources that are both culturally valid and technically usable. ## challenges and open questions cultural adaptation in text rewriting presents a wide array of challenges. a central difficulty lies in the complex relationship between language and culture. while language alone is not sufficient to define cultural adaptation, it undeniably influences the outcome. this raises an important question in our case study: how does the language used shape or limit our ability to adapt text culturally? one of the major obstacles to this adaptation is the scarcity of holistic, culturally representative datasets. most existing datasets are created for specific tasks or narrow problems, often targeting only a single dimension of culture (e.g., artifacts, values, . . . ). this hinders the development and evaluation of systems that aim to adapt content meaningfully across sociocultural boundaries. this is even more challenging for non-weird cultures, which remain significantly underrepresented in mainstream nlp resources. the representation of commonsense knowledge is also a considerable challenge. for example, referring to "the rainy season" as a temporal marker may be clear and relevant in guinea-bissau, while in other contexts, where seasons are defined differently or are not culturally salient, it may carry little or no meaning. more work is needed to account for such culturally grounded forms of shared knowledge @xcite . some researchers have argued that creole languages may exhibit distinctive patterns in language model training @xcite . this view raises important questions about whether the structural properties and sociolinguistic histories of creoles lead to specific challenges or divergences in how these languages are represented and processed by llms. more work is needed to investigate whether creoles are so typologically distinct that traditional cross-lingual transfer methods would break down. beyond identifying cultural references, capturing variations in responses and communication styles across cultures, such as making apologies or requests, and integrating these into lm responses, is also challenging @xcite . similarly, the representation of shared knowledge among cultures and how to define them is also a problem that has received limited attention @xcite . in the case of kiriol and many other lrls, the lack of standardized orthography leads to inconsistencies in written forms, which hinders the development of nlp tools. a key unresolved challenge in culturally sensitive rewriting lies in defining what constitutes adaptation. as singh et al. @xcite point out, it is important to ask what is being changed during adaptation, and for what purpose. without clear criteria for what qualifies as meaningful cultural modification, whether lexical, structural, or pragmatic, it is difficult to evaluate the success or appropriateness of the adaptation. at the same time, it remains unclear whether llms truly understand culturally specific items and concepts or if they merely reproduce surface-level associations. achieving genuine cultural adaptation re-quires more than substituting isolated terms; it demands deeper cultural reasoning and contextual awareness-capabilities that current models still struggle to demonstrate. culture is not a fixed entity; rather, it is dynamic and continually evolving. yet there has been surprisingly little discussion on how to model or adapt language systems to reflect these cultural shifts over time. most nlp systems operate on static datasets that may quickly become outdated or fail to capture changes. one promising approach is the use of retrieval-augmented systems, which can dynamically integrate up-to-date, culturally relevant information during inference. this enables models to remain aligned with contemporary cultural practices and discourses, enhancing both accuracy and cultural sensitivity in real-time applications @xcite . the lack of dynamism in current evaluation practices results in static cultural benchmarks that do not evolve alongside the cultures they aim to represent, limiting their long-term validity and usefulness @xcite . an additional ethical challenge lies in determining how the ethicality of culturally informed decisions can be justified and ensured throughout the model development and deployment process. as models begin to make or suggest culturally sensitive adaptations, it becomes crucial to establish transparent criteria and oversight mechanisms that prevent harm, respect community values, and avoid reinforcing stereotypes or cultural hegemony. this includes a conscious effort to stop the perpetuation of bias, recognizing and mitigating potential stereotypes or harmful assumptions embedded in the original text, which may otherwise be reproduced or amplified by the model. ## position and proposed direction given what we previously discussed, adapting educational texts for lrl contexts is a highly complex task. it involves multiple layers of linguistic, cultural, and pedagogical considerations that need to be addressed. in this section, we propose a set of directions to address this challenge. we build on the taxonomy by liu et al. @xcite , expanding it with new elements-including a fourth dimension, adaptation-that aim to better reflect the needs of multilingual and multicultural l2 education settings (figure 1 ). specifically, we propose the following addition: ## conclusions we live in times of polarization, in which imaginary lines are drawn to divide communities and reinforce boundaries. one of the most recurrent of these lines is culture. in a world where ai is becoming increasingly influential, communication must be both effective and capable of building bridges between people, between cultures. although adapting educational texts for lrls poses challenges, we believe that integrating nlp, especially llms, with cultural awareness can effectively improve the accessibility and relevance of educational materials in multicultural settings. no communication exists in a vacuum. every act of communication presupposes the presence of at least two entities. in this work, we were particularly interested in cases where one end of the communication is an llm. we examined in detail the importance of frameworks, although they were conceived from a human perspective. how interesting it would be if a framework also existed for what happens "under the hood", particularly in interactions involving multiple llms. so far, there is no shortage of examples showing how llms fail to understand language, yet language is one of the most human aspects of who we are. if one day llms truly understand language, they will be very close to our humanity. the sapir-whorf hypothesis states that people's thoughts are shaped by the linguistic resources available to them, influencing how they perceive and conceptualize the world. while llms do not possess thoughts or culture, they operate entirely through language and are thus inevitably shaped by the linguistic and cultural biases present in their training data. for now, addressing all the issues discussed in this paper remains a daunting task. and unlike in the movie "a nightmare on elm street", this is a nightmare we cannot afford to sleep through -we must wake up, because there is still much work to be done.