arXiv subjects

Miguel Marques

Publications and source records attributed to Miguel Marques.

12 recordsLinked to original sources

arXiv2026

Progressing beyond Art Masterpieces or Touristic Clich\'es: how to assess your LLMs for cultural alignment?

Although the cultural (mis)alignment of Large Language Models (LLMs) has attracted increasing attention -- often framed in terms of cultural bias -- until recently there has been limited work on the design and development of datasets for cultural assessment. Here, we review existing approaches to such datasets and identify their main limitations. To address these issues, we propose design guidelines for annotators and report on the construction of a dataset built according to these principles. We further present a series of contrastive experiments conducted with this dataset. The results demonstrate that our design yields test sets with greater discriminative power, effectively distinguishing between models specialized for a given culture and those that are not, ceteris paribus.

cs.CL↗

arXiv2026

CitiLink-Summ: Summarization of Discussion Subjects in European Portuguese Municipal Meeting Minutes

Municipal meeting minutes are formal records documenting the discussions and decisions of local government, yet their content is often lengthy, dense, and difficult for citizens to navigate. Automatic summarization can help address this challenge by producing concise summaries for each discussion subject. Despite its potential, research on summarizing discussion subjects in municipal meeting minutes remains largely unexplored, especially in low-resource languages, where the inherent complexity of these documents adds further challenges. A major bottleneck is the scarcity of datasets containing high-quality, manually crafted summaries, which limits the development and evaluation of effective summarization models for this domain. In this paper, we present CitiLink-Summ, a new corpus of European Portuguese municipal meeting minutes, comprising 100 documents and 2,322 manually hand-written summaries, each corresponding to a distinct discussion subject. Leveraging this dataset, we establish baseline results for automatic summarization in this domain, employing state-of-the-art generative models (e.g., BART, PRIMERA) as well as large language models (LLMs), evaluated with both lexical and semantic metrics such as ROUGE, BLEU, METEOR, and BERTScore. CitiLink-Summ provides the first benchmark for municipal-domain summarization in European Portuguese, offering a valuable resource for advancing NLP research on complex administrative texts.

cs.CL↗

arXiv2026

CitiLink-Minutes: A Multilayer Annotated Dataset of Municipal Meeting Minutes

City councils play a crucial role in local governance, directly influencing citizens' daily lives through decisions made during municipal meetings. These deliberations are formally documented in meeting minutes, which serve as official records of discussions, decisions, and voting outcomes. Despite their importance, municipal meeting records have received little attention in Information Retrieval (IR) and Natural Language Processing (NLP), largely due to the lack of annotated datasets, which ultimately limit the development of computational models. To address this gap, we introduce CitiLink-Minutes, a multilayer dataset of 120 European Portuguese municipal meeting minutes from six municipalities. Unlike prior annotated datasets of parliamentary or video records, CitiLink-Minutes provides multilayer annotations and structured linkage of official written minutes. The dataset contains over one million tokens, with all personal identifiers de-identified. Each minute was manually annotated by two trained annotators and curated by an experienced linguist across three complementary dimensions: (1) metadata, (2) subjects of discussion, and (3) voting outcomes, totaling over 38,000 individual annotations. Released under FAIR principles and accompanied by baseline results on metadata extraction, topic classification, and vote labeling, CitiLink-Minutes demonstrates its potential for downstream NLP and IR tasks, while promoting transparent access to municipal decisions.

cs.CL↗

arXiv2026

NLP for Local Governance Meeting Records: A Focus Article on Tasks, Datasets, Metrics and Benchmark

Local governance meeting records are official documents, in the form of minutes or transcripts, documenting how proposals, discussions, and procedural actions unfold during institutional meetings. While generally structured, these documents are often dense, bureaucratic, and highly heterogeneous across municipalities, exhibiting significant variation in language, terminology, structure, and overall organization. This heterogeneity makes them difficult for non-experts to interpret and challenging for intelligent automated systems to process, limiting public transparency and civic engagement. To address these challenges, computational methods can be employed to structure and interpret such complex documents. In particular, Natural Language Processing (NLP) offers well-established methods that can enhance the accessibility and interpretability of governmental records. In this focus article, we review foundational NLP tasks that support the structuring of local governance meeting documents. Specifically, we review three core tasks: document segmentation, domain-specific entity extraction and automatic text summarization, which are essential for navigating lengthy deliberations, identifying political actors and personal information, and generating concise representations of complex decision-making processes. In reviewing these tasks, we discuss methodological approaches, evaluation metrics, and publicly available resources, while highlighting domain-specific challenges such as data scarcity, privacy constraints, and source variability. By synthesizing existing work across these foundational tasks, this article provides a structured overview of how NLP can enhance the structuring and accessibility of local governance meeting records.

cs.CL↗

arXiv2026

CitiLink: Enhancing Municipal Transparency and Citizen Engagement through Searchable Meeting Minutes

City council minutes are typically lengthy and formal documents with a bureaucratic writing style. Although publicly available, their structure often makes it difficult for citizens or journalists to efficiently find information. In this demo, we present CitiLink, a platform designed to transform unstructured municipal meeting minutes into structured and searchable data, demonstrating how NLP and IR can enhance the accessibility and transparency of local government. The system employs LLMs to extract metadata, discussed subjects, and voting outcomes, which are then indexed in a database to support full-text search with BM25 ranking and faceted filtering through a user-friendly interface. The developed system was built over a collection of 120 minutes made available by six Portuguese municipalities. To assess its usability, CitiLink was tested through guided sessions with municipal personnel, providing insights into how real users interact with the system. In addition, we evaluated Gemini's performance in extracting relevant information from the minutes, highlighting its effectiveness in data extraction.

cs.CL↗

arXiv2024

Floralens: a Deep Learning Model for the Portuguese Native Flora

Machine-learning techniques, especially deep convolutional neural networks, are pivotal for image-based identification of biological species in many Citizen Science platforms. In this paper, we describe the construction of a dataset for the Portuguese native flora based on publicly available research-grade datasets, and the derivation of a high-accuracy model from it using off-the-shelf deep convolutional neural networks. We anchored the dataset in high-quality data provided by Sociedade Portuguesa de Bot\^anica and added further sampled data from research-grade datasets available from GBIF. We find that with a careful dataset design, off-the-shelf machine-learning cloud services such as Google's AutoML Vision produce accurate models, with results comparable to those of Pl@ntNet, a state-of-the-art citizen science platform. The best model we derived, dubbed Floralens, has been integrated into the public website of Project Biolens, where we gather models for other taxa as well. The dataset used to train the model is also publicly available on Zenodo.

cs.CV↗

arXiv2022

Machine Learning guided high-throughput search of non-oxide garnets

Garnets, known since the early stages of human civilization, have found important applications in modern technologies including magnetorestriction, spintronics, lithium batteries, etc. The overwhelming majority of experimentally known garnets are oxides, while explorations (experimental or theoretical) for the rest of the chemical space have been limited in scope. A key issue is that the garnet structure has a large primitive unit cell, requiring an enormous amount of computational resources. To perform a comprehensive search of the complete chemical space for new garnets,we combine recent progress in graph neural networks with high-throughput calculations. We apply the machine learning model to identify the potential (meta-)stable garnet systems before systematic density-functional calculations to validate the predictions. In this way, we discover more than 600 ternary garnets with distances to the convex hull below 100~meV/atom with a variety of physical and chemical properties. This includes sulfide, nitride and halide garnets. For these, we analyze the electronic structure and discuss the connection between the value of the electronic band gap and charge balance.

cond-mat.mtrl-sci↗

arXiv2021

Dynamic Page Placement on Real Persistent Memory Systems

As persistent memory (PM) technologies emerge, hybrid memory architectures combining DRAM with PM bring the potential to provide a tiered, byte-addressable main memory of unprecedented capacity. Nearly a decade after the first proposals for these hybrid architectures, the real technology has finally reached commercial availability with Intel Optane(TM) DC Persistent Memory (DCPMM). This raises the challenge of designing systems that realize this potential in practice, namely through effective approaches that dynamically decide at which memory tier should pages be placed. In this paper, we are the first, to our knowledge, to systematically analyze tiered page placement on real DCPMM-based systems. To this end, we start by revisiting the assumptions of state-of-the-art proposals, and confronting them with the idiosyncrasies of today's off-the-shelf DCPMM-equipped architectures. This empirical study reveals that some of the key design choices in the literature rely on important assumptions that are not verified in present-day DRAM-DCPMM memory architectures. Based on the lessons from this study, we design and implement HyPlacer, a tool for tiered page placement in off-the-shelf Linux-based systems equipped with DRAM+DCPMM. In contrast to previous proposals, HyPlacer follows an approach guided by two main practicality principles: 1) it is tailored to the performance idiosyncrasies of off-theshelf DRAM+DCPMM systems; and 2) it can be seamlessly integrated into Linux with minimal kernel-mode components, while ensuring extensibility to other HMAs and other data placement policies. Our experimental evaluation of HyPlacer shows that it outperforms both solutions proposed in past literature and placement options that are currently available in off-the-shelf DCPMM-equipped Linux systems, reaching an improvement of up to 11x when compared to the default memory policy in Linux.

cs.DC↗

arXiv2020

Validation of pseudopotential calculations for the electronic band gap of solids

Nowadays pseudopotential density-functional theory calculations constitute the standard approach to tackle solid-state electronic problems. These rely on distributed pseudopotential tables that were built from all-electron atomic calculations using few popular semi-local exchange-correlation functionals, while pseudopotentials based on more modern functionals, like meta-GGA and hybrid functionals, or for many-body methods, such as $GW$, are often not available. Because of this, employing pseudopotentials created with inconsistent exchange-correlation functionals has become a common practice. Our aim is to quantify systematically the error in the determination of the electronic band gap when cross-functional pseudopotential calculations are performed. To this end we compare band gaps obtained with norm-conserving pseudopotentials or the projector-augmented wave method with all-electron calculations for a large dataset of 473 solids. We focus in particular on density functionals that were designed specifically for band-gap calculations. On average, the absolute error is about 0.1 eV, yielding absolute relative errors in the 5-10\% range. Considering that typical errors stemming from the choice of the functional are usually larger, we conclude that the effect of choosing an inconsistent pseudopotential is rather harmless for most applications. However, we find specific cases where absolute errors can be larger than 1 eV, or others where relative errors can amount to a large fraction of the band gap.

physics.comp-ph↗

arXiv2019

Rotating neutron stars with non-barotropic thermal profile

Neutron stars provide an excellent laboratory for physics under the most extreme conditions. Up to now, models of axisymmetric, stationary, differentially rotating neutron stars were constructed under the strong assumption of barotropicity, where a one-to-one relation between all thermodynamic quantities exists. This implies that the specific angular momentum of a matter element depends only on its angular velocity. The physical conditions in the early stages of neutron stars, however, are determined by their violent birth processes, typically a supernova or in some cases the merger of two neutron stars, and detailed numerical models show that the resulting stars are by no means barotropic. Here, we construct models for stationary, differentially rotating, non-barotropic neutron stars, where the equation of state and the specific angular momentum depend on more than one independent variable. We show that the potential formulation of the relativistic Euler equation can be extended to the non-barotropic case, which, to the best of our knowledge, is a new result even for the Newtonian case. We implement the new method into the XNS code and construct equilibrium configurations for non-barotropic equations of state. We scrutinize the resulting configurations by evolving them dynamically with the numerical relativity code BAM, thereby demonstrating that the new method indeed produces stationary, differentially rotating, non-barotropic neutron star configurations.

gr-qc↗

arXiv2017

A new temperature dependent hyperonic equation of state: application to rotating neutron star models and I-Q-relations

In this work we present a newly constructed equation of state (EoS) --applicable to stellar core collapse and neutron star mergers--, including the entire baryon octet. Our EoS is compatible with the main constraints from nuclear physics and, in particular, with a maximum mass for cold beta-equilibrated neutron stars of 2 solar masses in agreement with recent observations. As an application of our new EoS, we compute numerical stationary models for rapidly (rigidly) rotating hot neutron stars. We consider maximum masses of hot stars, such as proto-neutron stars or hypermassive neutron stars in the post-merger phase of binary neutron star coalescence. The universality of I-Q-relations at nonzero temperature for fast rotating models, comparing a purely nuclear EoS with its counterparts containing Lambda-hyperons or the entire baryon octet, respectively, is discussed, too. We find that the I-Q universality is broken when thermal effects become important, whatever the value of entropy gradients in our models. Thus, the use of I-Q relations for the analysis of proto-neutron stars or merger remnant data, including gravitational wave signals from the last stages of binary neutron star mergers, should be regarded with care.

nucl-th↗

arXiv2009

On the instability of Reissner-Nordstrom black holes in de Sitter backgrounds

Recent numerical investigations have uncovered a surprising result: Reissner-Nordstrom-de Sitter black holes are unstable for spacetime dimensions larger than 6. Here we prove the existence of such instability analytically, and we compute the timescale in the near-extremal limit. We find very good agreement with the previous numerical results. Our results may me helpful in shedding some light on the nature of the instability.

gr-qc↗