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arXiv:2604.13047v1 Announce Type: new Abstract: In recent years, the spread of fake news has triggered a growing interest in Information Disorders (ID) on social media, a phenomenon that has become a focal point of research across fields ranging from complexity theory and computer science to cognitive sciences. Overall, such a body of research can be traced back to two main approaches. On the one hand, there are works focused on exploiting data mining to analyze the content of […]

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arXiv:2604.13046v1 Announce Type: new Abstract: Data-driven systems depend on task-relevant data, yet data collection pipelines remain passive and indiscriminate. Continuous logging of multimodal sensor streams incurs high storage costs and captures irrelevant data. This paper proposes a declarative framework for intent-driven, on-device data collection that enables selective collection of multimodal sensor data based on high-level user requests. The framework combines natural language interaction with a formally specified domain-specific language (DSL). Large language models translate user-defined requirements into verifiable […]

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arXiv:2604.13045v1 Announce Type: new Abstract: Natural Language to MongoDB Query Language (NL2MQL) is essential for democratizing access to modern document-centric databases. Unlike Text-to-SQL, NL2MQL faces unique challenges from MQL’s procedural aggregation pipelines, deeply nested schemas, and ambiguous value grounding. Existing approaches use static prompting or one-shot refinement, which inadequately model these complex contexts and fail to systematically leverage execution feedback for persistent improvement. We propose EvoMQL, a self-evolved framework that unifies evidence-grounded context construction with execution-driven learning through […]

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arXiv:2604.13044v1 Announce Type: new Abstract: This paper presents a detailed analysis of the environmental impact of Chia Network (Chia for short), a green-claimed blockchain, which uses a Proof of Space and Time (PoST) consensus mechanism. While Chia claims to be a sustainable alternative to Proof-of-Work-based blockchains, our results show that its resource-intensive initialization phase and ongoing operations lead to carbon emissions 18x higher than claimed (0.88 MtCO2/year), exceeding mainstream “green” blockchains by orders of magnitude. We combine experimental […]

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arXiv:2604.13042v1 Announce Type: new Abstract: Semantic data harmonisation is a central requirement in the ILIAD project, where heterogeneous environmental data must be harmonised according to the Ocean Information Model (OIM), a modular family of ontologies for enabling the implementation of interoperable Digital Twins of the Ocean. Existing approaches to Semantic Data Harmonisation, such as RML and OTTR, offer valuable abstractions but require extensive knowledge of the technical intricacies of the OIM and the Semantic Web standards, including namespaces, […]

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arXiv:2604.13041v1 Announce Type: new Abstract: Table Structure Recognition (TSR) requires the logical reasoning ability of large language models (LLMs) to handle complex table layouts, but current datasets are limited in scale and quality, hindering effective use of this reasoning capacity. We thus present TableNet dataset, a new table structure recognition dataset collected and generated through multiple sources. Central to our approach is the first LLM-powered autonomous table generation and recognition multi-agent system that we developed. The generation part […]

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arXiv:2604.13040v1 Announce Type: new Abstract: The process of decomposing databases into smaller datasets, with the objective of extrapolating the information obtained in the smaller ones to the original database, represents a relevant and complex challenge in real applications. It is particularly relevant in the context of fuzzy formal concept analysis, where the complexities of knowledge extraction from datasets characterized by incomplete and imperfect data are considerable. This paper will analyze a mechanism and different properties for detecting independent […]

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arXiv:2604.13039v1 Announce Type: new Abstract: The decomposition of datasets is a useful mechanism in the processing of large datasets and it is required in many cases. In formal concept analysis (FCA), the dataset is interpreted as a context and the notion of independent context is relevant in the decomposition of a context. In this paper, we have introduced a formal definition of independent context within the multi-adjoint concept lattice framework, which can be translated to other fuzzy approaches. […]

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arXiv:2604.13037v1 Announce Type: new Abstract: Mining multiple longest common subsequences (textit{MLCS}) from a set of sequences of three or more over a finite alphabet $Sigma$ (a classical NP-hard problem) is an important task in a wide variety of application fields. Unfortunately, there is still no exact textit{MLCS} algorithm/tool that can handle long (length $ge$ 1,000) or big (length $ge$ 10,000) sequences, which seriously hinders the development and utilization of massive long or big sequences from various application fields […]

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Accurate temperature estimation of pouch cells with indirect liquid cooling is essential for optimizing battery thermal management systems for transportation electrification. However, it is challenging due to the computational expense of finite element simulations and the limitations of data-driven models. This paper presents a physics-informed machine learning (PIML) framework for the efficient and reliable estimation of steady-state temperature profiles. The PIML approach integrates the governing heat transfer equations directly into the neural network’s loss function, enabling high-fidelity predictions […]

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