Culture-expressions, such as idioms, slang, and culture-specific items (CSIs), are pervasive in natural language and encode meanings that go beyond literal linguistic form. Accurately translating such expressions remains challenging for machine translation systems. Despite this, existing benchmarks remain fragmented and do not provide a systematic framework for evaluating translation performance on culture-loaded expressions. To address this gap, we introduce CulT-Eval, a benchmark designed to evaluate how models handle different types of culturally grounded expressions. CulT-Eval comprises over 7,959 carefully curated instances spanning multiple types of culturally grounded expressions, with a comprehensive error taxonomy covering culturally grounded expressions. Through extensive evaluation of large language models and detailed analysis, we identify recurring and systematic failure modes that are not adequately captured by existing automatic metrics. Accordingly, we propose a complementary evaluation metric that targets culturally induced meaning deviations overlooked by standard MT metrics. The results indicate that current models struggle to preserve culturally grounded meaning
Vishaps, or dragon stones, are prehistoric stelae discovered in the high-altitude mountainous regions of modern-day Armenia and adjacent regions. The first statistical analysis of their elevation distribution and size reveals that their construction was intentionally labor-intensive rather than arbitrary. The findings support the hypothesis that vishaps were closely associated with an ancient water cult, as they are predominantly situated near water sources, including high-altitude springs and discovered prehistoric irrigation systems. Furthermore, the unexpected bimodal distribution of their altitudes suggests specific placement patterns, potentially linked to seasonal human activities or ritual practices. These findings contribute to a deeper understanding of the symbolic and functional significance of vishap stelae within the framework of prehistoric social and religious systems.
Software development is currently under a paradigm shift in which artificial intelligence and generative software reuse are taking the center stage in software creation. Consequently, earlier software reuse practices and methods are rapidly being replaced by AI-assisted approaches in which developers place their trust on code that has been generated by artificial intelligence. This is leading to a new form of software reuse that is conceptually not all that different from cargo cult development. In this paper we discuss the implications of AI-assisted generative software reuse in the context of emerging "AI native" software engineering, bring forth relevant questions, and define a tentative research agenda and call to action for tackling some of the central issues associated with this approach.
We introduce CULT (Continual Unsupervised Representation Learning with Typicality-Based Environment Detection), a new algorithm for continual unsupervised learning with variational auto-encoders. CULT uses a simple typicality metric in the latent space of a VAE to detect distributional shifts in the environment, which is used in conjunction with generative replay and an auxiliary environmental classifier to limit catastrophic forgetting in unsupervised representation learning. In our experiments, CULT significantly outperforms baseline continual unsupervised learning approaches. Code for this paper can be found here: https://github.com/oliveradk/cult
Linked Data is used in various fields as a new way of structuring and connecting data. Cultural heritage institutions have been using linked data to improve archival descriptions and facilitate the discovery of information. Most archival records have digital representations of physical artifacts in the form of scanned images that are non-machine-readable. Optical Character Recognition (OCR) recognizes text in images and translates it into machine-encoded text. This paper evaluates the impact of image processing methods and parameter tuning in OCR applied to typewritten cultural heritage documents. The approach uses a multi-objective problem formulation to minimize Levenshtein edit distance and maximize the number of words correctly identified with a non-dominated sorting genetic algorithm (NSGA-II) to tune the methods' parameters. Evaluation results show that parameterization by digital representation typology benefits the performance of image pre-processing algorithms in OCR. Furthermore, our findings suggest that employing image pre-processing algorithms in OCR might be more suitable for typologies where the text recognition task without pre-processing does not produce good resul
The bird-man cult remains the main secret of Easter Island (Rapa Nui), a remote plot of land in the Pacific. This paper includes not only necessary ethnological data, but also some results on the archaeoastronomy. The research of some lines marked on a stone calendar from the Mataveri area, an archaic zone of the bird-man cult, allows to insist that the natives watched at least the stars Canopus and Aldebaran. There are strong grounds for believing that, among others, the Sun, the Moon as well as Beta and Alpha Centauri were the matter for quasi-scientific enquiry. Several astronomical and calendar records in the rock art and in the script have been decoded.
In the framework of applying econophysics ideas in religious topics, the finances of the Antoinist religious movement organized in Belgium between 1920 and 2000 are studied. The interest of investigating financial aspects of such a, sometimes called, sect stems in finding characteristics of conditions and mechanisms under which definitely growth AND decay features of communities can be understood. The legally reported yearly income and expenses between 1920 and 2000 are studied. A three wave asymmetric regime is observed over a trend among marked fluctuations at time of crises. The data analysis leads to propose a general mechanistic model taking into account an average GDP growth, an oscillatory monetary inflation and a logistic population drift.
Quantum Federated Learning (QFL) inherits the core vulnerability of federated optimization to malicious clients, while also introducing an attack surface from variational circuit training and measurement-driven gradients. This work proposes a novel CircUit-Level backdoor Threat (CULT) model that formalizes four stealthy attacks by exploiting quantum-aware mechanisms, including Grover, Pauli, Bit-flip, and Sign-flip. By enabling malicious clients on both in-training and post-training surfaces, these attacks can critically undermine the learning process. We establish a rigorous theoretical foundation to demonstrate attack stealthiness under standard smoothness assumptions. Experiments on the MNIST and CIFAR-10 datasets with non-IID splits and varying fractions of malicious clients show that even a single malicious client can induce severe accuracy degradation under FedAvg aggregation. While popular defenses, including Krum, Multi-Krum, FoolsGold, FLGuardian, and Mud-HoG, reduce degradation in many regimes, they fail to eliminate worst-case failure cases, where accuracy drops up to 50\%. The experimental analysis further reveals that under the CULT model, malicious updates effectively
Joint rendering and deformation of mesh and 3D Gaussian Splatting (3DGS) have significant value as both representa tions offer complementary advantages for graphics applica tions. However, due to differences in representation and ren dering pipelines, existing studies render meshes and 3DGS separately, making it difficult to accurately handle occlusions and transparency. Moreover, the deformed 3DGS still suffers from visual artifacts due to the sensitivity to the topology quality of the proxy mesh. These issues pose serious obsta cles to the joint use of 3DGS and meshes, making it diffi cult to adapt 3DGS to conventional mesh-oriented graphics pipelines. We propose UniMGS, the first unified framework for rasterizing mesh and 3DGS in a single-pass anti-aliased manner, with a novel binding strategy for 3DGS deformation based on proxy mesh. Our key insight is to blend the col ors of both triangle and Gaussian fragments by anti-aliased α-blending in a single pass, achieving visually coherent re sults with precise handling of occlusion and transparency. To improve the visual appearance of the deformed 3DGS, our Gaussian-centric binding strategy employs a proxy mesh and spatially associa
Vishaps -- dragon stones -- discovered in the Armenian Highlands convey a remarkable message about the spiritual and social character of their epoch, c. 4000 BC. The unexpected bimodal distribution of their elevations indicates the deliberate, labor-intensive placement of these massive stones -- some weighing up to 7--9 tons -- in locations where the period suitable for construction activities at high altitudes was extremely limited. Their positions, correlated with nodes of previously identified prehistoric irrigation systems, support the interpretation that they were dedicated to a cult of water. This evidence points to the existence of an organized and unified society capable of sustaining and maintaining such a resource-intensive cult.
Recent Large Reasoning Models trained via reinforcement learning exhibit a "natural" alignment with human cognitive costs. However, we show that the prevailing paradigm of reasoning distillation -- training student models to mimic these traces via Supervised Fine-Tuning (SFT) -- fails to transmit this cognitive structure. Testing the "Hán Dān Xué Bù" (Superficial Mimicry) hypothesis across 14 models, we find that distillation induces a "Functional Alignment Collapse": while teacher models mirror human difficulty scaling ($\bar{r}=0.64$), distilled students significantly degrade this alignment ($\bar{r}=0.34$), often underperforming their own pre-distillation baselines ("Negative Transfer"). Our analysis suggests that SFT induces a "Cargo Cult" effect, where students ritualistically replicate the linguistic form of reasoning (verbosity) without internalizing the teacher's dynamic resource allocation policy. Consequently, reasoning distillation decouples computational cost from cognitive demand, revealing that human-like cognition is an emergent property of active reinforcement, not passive imitation.
Software development is currently under a paradigm shift in which artificial intelligence and generative software reuse are taking the center stage in software creation. Earlier opportunistic software reuse practices and organic software development methods are rapidly being replaced by "AI Native" approaches in which developers place their trust on code that has been generated by artificial intelligence. This is leading to a new form of software reuse that is conceptually not all that different from cargo cult development. In this paper we discuss the implications of AI-assisted generative software reuse, bring forth relevant questions, and define a research agenda for tackling the central issues associated with this emerging approach.
Flamenco, recognized by UNESCO as part of the Intangible Cultural Heritage of Humanity, is a profound expression of cultural identity rooted in Andalusia, Spain. However, there is a lack of quantitative studies that help identify characteristic patterns in this long-lived music tradition. In this work, we present a computational analysis of Flamenco lyrics, employing natural language processing and machine learning to categorize over 2000 lyrics into their respective Flamenco genres, termed as $\textit{palos}$. Using a Multinomial Naive Bayes classifier, we find that lexical variation across styles enables to accurately identify distinct $\textit{palos}$. More importantly, from an automatic method of word usage, we obtain the semantic fields that characterize each style. Further, applying a metric that quantifies the inter-genre distance we perform a network analysis that sheds light on the relationship between Flamenco styles. Remarkably, our results suggest historical connections and $\textit{palo}$ evolutions. Overall, our work illuminates the intricate relationships and cultural significance embedded within Flamenco lyrics, complementing previous qualitative discussions with qu
The wave mechanics theory of microwave absorption challenges the long-standing impedance-matching and quarter-wavelength paradigms by demonstrating that conventional models mistakenly conflate bulk material parameters with thin-film phenomena. Drawing on a corpus of 35 peer-reviewed papers and preprints, the study performs a citation-pattern analysis and a logical audit of established theory. Results reveal a striking asymmetry in scholarly engagement, only a handful of supportive or neutral citations appear amid widespread silence, alongside critical logical flaws in impedance matching, notably its inconsistent treatment of penetration, reflection, and absorption from film. By re-framing absorption as a wave-mechanics process governed by interference at parallel interfaces, the wave mechanics framework restores energy-conservation consistency and provides experimentally verified design rules for film thickness, phase response, and broadband performance. The paper further situates the citation neglect within broader issues of peer-review bias and paradigm inertia, illustrating how cargo-cult scientific practices can impede theoretical progress. Recommendations are offered for resea
Stimela2 is a new-generation framework for developing data reduction workflows. It is designed for radio astronomy data but can be adapted for other data processing applications. Stimela2 aims at the middle ground between ease of development, human readability, and enabling robust, scalable and reproducible workflows. It represents workflows by linear, concise and intuitive YAML-format "recipes". Atomic data reduction tasks (binary executables, Python functions and code, and CASA tasks) are described by YAML-format "cab definitions" detailing each task's "schema" (inputs and outputs). Stimela2 provides a rich syntax for chaining tasks together, and encourages a high degree of modularity: recipes may be nested into other recipes, and configuration is cleanly separated from recipe logic. Tasks can be executed natively or in isolated environments using containerization technologies such as Apptainer. The container images are open-source and maintained through a companion package called cult-cargo. This enables the development of system-agnostic and fully reproducible workflows. Stimela2 facilitates the deployment of scalable, distributed workflows by interfacing with the Slurm schedul
In this article, we present and discuss a user-study prototype, developed for Bakkehuset historic house museum in Copenhagen. We examine how the prototype - a digital sound installation - can expand visitors' experiences of the house and offer encounters with immaterial cultural heritage. Historic house museums often hold back on utilizing digital communication tools inside the houses, since a central purpose of this type of museum is to preserve an original environment. Digital communication tools however hold great potential for facilitating rich encounters with cultural heritage and in particular with the immaterial aspects of museum collections and their histories. In this article we present our design steps and choices, aiming at subtly and seamlessly adding a digital dimension to a historic house. Based on qualitative interviews, we evaluate how the sound installation at Bakkehuset is sensed, interpreted, and used by visitors as part of their museum experience. In turn, we shed light on the historic house museum as a distinct design context for designing hybrid visitor experiences and point to the potentials of digital communication tools in this context.
Archives are facing numerous challenges. On the one hand, archival assets are evolving to encompass digitized documents and increasing quantities of born-digital information in diverse formats. On the other hand, the audience is changing along with how it wishes to access archival material. Moreover, the interoperability requirements of cultural heritage repositories are growing. In this context, the Portuguese Archives started an ambitious program aiming to evolve its data model, migrate existing records, and build a new archival management system appropriate to both archival tasks and public access. The overall goal is to have a fine-grained and flexible description, more machine-actionable than the current one. This work describes ArchOnto, a linked open data model for archives, and rules for its automatic population from existing records. ArchOnto adopts a semantic web approach and encompasses the CIDOC Conceptual Reference Model and additional ontologies, envisioning interoperability with datasets curated by multiple communities of practice. Existing ISAD(G)-conforming descriptions are being migrated to the new model using the direct mappings provided here. We used a sample of
With the rapid development of technology and its place in our lives, so too has the idea of needing to grow up faster, do more, be more and more as we are exposed to so many of our betters billboarding their successes and achievements that very often we can experience burnout, depression, feeling of inadequacy and worse. All because we cannot keep up with their tempos in life, and in this chaos, we often lose the very important fact and truth, our life should be lived at the tempo that fits our actual wants, our capabilities and opportunities. In recent years, since the mid 2010s, video games have entered the mainstream even more than before as a media platform that provides a more interactive experience than others like it. Where the players actions have consequences, outcomes both good and bad, and the experience of the player is highly linked to their capabilities. Based on the type of video game, be it single player or multiplayer, often the solution to the problem the player is facing will vary. With the increase popularity of both buying and creating games, more and more personal stories, talented teams and individuals, unique takes and ideas are being tried and often for the
This paper pursues the scopes of joining the economical characteristics of Italian cities with a relevant sociological aspect: the cult of the catholic Saints. Indeed, more than in other Countries, a high percentage of Italian cities has a toponym coming from the name of specific Saints (hagiotoponym). The assessment of the historical origin of each hagiotoponym is out of the scopes of the present paper, but the link with the religious sense of Italians seems to be clear. The statistical analysis of the economic contributions that each hagiotoponym city provides to the Italian GDP is here performed. Such an analysis is also based on the comparison with the overall Italian data, and it is carried out through the computation of the Theil, Gini and Herfindahl-Hirschman indices.
Watchings of Canopus as a herald of the winter were important duties of ancient priests-astronomers on Easter Island. All the analysed data witness that this star was observed during the first and second voyages from Mangareva to the island. The names of king Hotu-Matua (Anua-Motua) and his father Tara tahi have been decoded. Several rongorongo records from the Esteban Atan manuscript have been deciphered advantageously. The new view at a painted barkcloth figurine connected with the bird-man cult has been offered. Some data about watchings of Aldebaran, the Pleiades, the sun, the moon, Venus and Mars have been collected as well.