Efficiently supporting sound gradual typing in a language with structural types is challenging. To date, the Grift compiler is the only close-to-the-metal implementation of gradual typing in this sett...

En la última década, el crimen organizado ha dejado de ser un fenómeno localizado para convertirse en una amenaza estructural a las democracias de América Latina. Redes criminales diversificadas y...

Abstract The age at puberty onset varies greatly between individuals and ethnic populations, with significant health implications. Early menarche increases risk for breast cancer, cardiovascular disea...

Automata learning has many applications in artificial intelligence and software engineering. Central to these applications is the $L^*$ algorithm, introduced by Angluin. The $L^*$ algorithm learns det...

Large Language Models (LLMs) can generate realistic text resembling human-produced content. However, the ability of these models to simulate conversations on social media is still less explored. To in...

When query evaluation produces too many tuples, a new approach in query answering is to retrieve a diverse subset of them. The standard approach for measuring the diversity of a set of tuples is to us...

We developed a theoretical framework that encompasses a broad family of misfit functions between real and simulated seismogram data, including well-known examples such as the least-squares criterion. ...

There is rising momentum within the fields of communication, media studies and (digital) journalism studies to enhance diversity of scholarship, away from a Western-centric gaze, and to be more inclus...

Abstract Background Large language models (LLMs) such as GPT-4o have the potential to transform clinical decision-making, patient education, and medical research. Despite impressive performance in gen...

Abstract Artificial intelligence (AI) is transforming survey research, offering powerful tools like large language models (LLMs) to analyze human beliefs, opinions, and behaviors. As researchers incre...

In this paper, we present a comprehensive comparison between specialized Lexical Semantic Change Detection (LSCD) models and Large Language Models (LLMs) for the LSCD task. In addition to comparing mo...

Temporal video grounding is a fundamental task in computer vision, aiming to localize a natural language query in a long, untrimmed video. It has a key role in the scientific community, in part due to...

This paper addresses two central dimensions of legislative behavior: ideological position and voting cohesion. Although both approaches have been widely used to analyze legislative behavior, no unifie...

Graph databases have become an important data management technology across various domains, including biology, sociology, industry (e.g. fraud detection, supply chain management, financial services), ...

Certified programming, as carried out in proof assistants and dependently-typed programming languages, ensures that a software meets its requirements by supporting the definition of both specification...

Abstract Leapfrog Triejoin (LTJ) is arguably the most practical and popular worst-case-optimal (wco) algorithm for solving basic graph patterns in graph databases. Its main drawback is that it needs t...

Decision support systems enhanced by Artificial Intelligence (AI) are increasingly being used in high-stakes scenarios where errors or biased outcomes can have significant consequences. In this work, ...

When query evaluation produces too many tuples, a new approach in query answering is to retrieve a diverse subset of them. The standard approach for measuring the diversity of a set of tuples is to us...

Problematic information, such as mis- and disinformation, circulating in fragmented news ecosystems, has contributed to mistrust and information fatigue. Using survey data ( N = 2,117) and two focus g...

Partial retrieval is a long-standing problem in the 3D Object Retrieval community. Its main difficulties arise from how to define 3D local descriptors in a way that makes them effective for partial re...

Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artificial intelligence a...

A high-level précis of this Technical Paper can be found in the Summary for Policymakers report, Artificial Intelligence for Peacebuilding: Promises and Pitfalls. Artificial intelligence (AI) is rapi...

Background Cerebellar atrophy is a known feature of ataxia-telangiectasia (A-T). However, basal ganglia dysfunction contributing to extrapyramidal movement disorders in A-T remains understudied. Objec...

Program slicing aims to simplify programs by identifying and removing non-essential parts while preserving program behavior. It is widely used for program understanding, debugging, and software mainte...

Abstract Large-alphabet strings, prevalent in information retrieval and natural language processing, pose unique storage and processing challenges. This paper explores the efficient implementation of ...

Formal XAI (explainable AI) is a growing area that focuses on computing explanations with mathematical guarantees for the decisions made by ML models. Inside formal XAI, one of the most studied cases ...

The \(r\) -index (Gagie et al., JACM 2020) represented a breakthrough in compressed indexing of repetitive text collections, outperforming its alternatives by orders of magnitude in query time. Its sp...

By sharing our prompts and code, we aim to help other institutions and countries extract crucial information from free text to a controlled vocabulary of ILO. Future work includes the analysis of comm...

Personal Informatics (PI) systems, such as apps and wearables that help users track physical activity, sleep, heart rate, or stress, have become critical tools for self-monitoring and health research....

Generative image models have achieved remarkable progress in both natural and medical imaging. In the medical context, these techniques offer a potential solution to data scarcity-especially for low-p...

Gradual typing has long been advocated as a means to bridge the gap between static and dynamic typing disciplines, enabling a range of use cases such as the gradual migration of existing dynamically t...

The evaluation of open-ended questions is typically performed by human instructors using predefined criteria to uphold academic standards. However, manual grading presents challenges, including high c...

This article addresses the growing global assault on academic freedom—a cornerstone of democratic societies now under increasing threat from authoritarian regimes. It highlights a global decline in ...

This study introduces a novel method that merges propagation-based transfer learning with word embeddings for rumor detection. This approach aims to use data from languages with abundant resources to ...

Although graph query languages such as Cypher, SQL/PGQ, and GQL take inspiration from theoretical languages such as conjunctive regular path queries (CRPQs), their pattern matching facilities are sign...

From the moment of their inception, languages for relational data have been described as sublanguages embedded in a host programming language. Rel is a new relational language whose key design goal is...

Complex Event Recognition (CER) refers to the activity of analyzing streams of continuously arriving event data, to recognize collections of events that satisfy user-defined patterns. CER is known to ...

This editorial celebrates the first issue of the Information Retrieval Research Journal, IRRJ.

Abstract Urban transportation networks are recognized for their pivotal role in forecasting city indicators and facilitating efficient planning and management. However, despite the increase of methodo...

Despite promising developments in Explainable Artificial Intelligence, the practical value of XAI methods remains under-explored and insufficiently validated in real-world settings. Robust and context...

Complex Event Recognition (CER) establishes a relevant solution for processing streams of events, giving users timely information. CER systems detect patterns in real-time, producing complex events an...

Despite the wide use of k -Nearest Neighbors as classification models, their explainability properties remain poorly understood from a theoretical perspective. While nearest neighbors classifiers offe...

Wikipedia is powered by MediaWiki, a free and open-source software that is also the infrastructure for many other wiki-based online encyclopedias. These include the recently launched website Ruwiki, w...

High-resolution seafloor mapping continues to be challenging, primarily due to the high costs and complexity of traditional sensors. Laser scanners offer a more affordable alternative, using a monocul...

Large Language Models (LLMs) have demonstrated strong performance on English-language medical exams, but their effectiveness in non-English, high-stakes environments is less understood. This study ben...

A high-level précis of this Synthesis Report can be found in the Summary for Policymakers report, Facts, Fakes, and Climate Science. The human response to the climate crisis is being obstructed and d...

This Summary for Policymakers provides a high-level précis of the Synthesis Report, Information Integrity about Climate Science: A Systematic Review. The human response to the climate crisis is being...

ABSTRACT Introduction While operations rank and select on static bitvectors can be supported in constant time, lower bounds show that this is impossible when supporting updates; practical implementati...

This article presents an exploration of the use of pre-trained Large Language Models (LLMs) for crisis classification to address labeled data dependency issues. We present a methodology that enhances ...

This study examines the communication mechanisms that shape the formation of digitally-enabled mobilization networks. Informed by the logic of connective action, we postulate that the emergence of net...

Abstract The origin of the variability in accretion disks of active galactic nuclei (AGN) is still unknown, but its behavior can be characterized by modeling the time series of optical wavelength flux...

Extracting key information from news articles is crucial for advancing search systems.Historically, the 5W1H framework, which organises information based on 'Who', 'What', 'When', 'Where', 'Why', and ...

Abstract Background Large language models (LLMs) like GPT-4o have shown promise in advancing medical decision-making and education. However, their performance in Spanish-language medical contexts rema...

Abstract Practical SQL engines differ in subtle ways in their handling of typing constraints and implicit type casts. These issues, usually not considered in formal accounts of SQL, directly affect th...

A high-level précis of the Technical Paper can be found in the Summary for Policymakers report, Generative AI in Electoral Campaigns: Mapping Global Patterns. GenAI is being deployed in many ways dur...

This Summary for Policymakers provides a high-level précis of the Technical Paper, The Role of Generative AI Use in 2024 Elections Worldwide. GenAI is being deployed in many ways during elections, ra...

[This corrects the article DOI: 10.1371/journal.pone.0306521.].

Spatial data play an important role in many applications built over knowledge graphs, and are frequently referenced in queries posed to public query services, such as that of Wikidata.Querying for spa...

Formal XAI is an emerging field that focuses on providing explanations with mathematical guarantees for the decisions made by machine learning models. A significant amount of work in this area is cent...

This work studies Complex Event Recognition (CER) under time constraints regarding its query language, computational models, and streaming evaluation algorithms. We start by introducing an extension o...

The global spread of political misinformation poses serious challenges to democracies, eroding trust and distorting public discourse. However, research has largely focused on WEIRD countries—Western...

By conducting a content analysis of 331 news stories, this study observed how six news organizations covered Chile's new school admission system (SAE) for enrolling in K-12 schools. To identify the pr...

Different attribution scores have been proposed to quantify the relevance of database tuples for query answering in databases; e.g. Causal Responsibility, the Shapley Value, the Banzhaf Power-Index, a...

Graph neural networks are prominent models for representation learning over graph-structured data. While the capabilities and limitations of these models are well-understood for simple graphs, our und...

Identity is a crucial force in every facet of contemporary politics, but political communication research has too often addressed it only superficially, excluded it from the subfield’s primary f...

Abstract Background Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has ...

In e-commerce, customers often struggle to find relevant items when their needs involve subjective properties characterized by personal or collective perception, tastes, and opinions, which are typica...

We study the problem of enumerating results from a query over a compressed document. The model we use for compression are straight-line programs (SLPs), which are defined by a context-free grammar tha...

Knowledge Graph Foundation Models (KGFMs) are at the frontier for deep learning on knowledge graphs (KGs), as they can generalize to completely novel knowledge graphs with different relational vocabul...

Machine learning applications in high-stakes scenarios should always operate under human oversight. Developing an optimal combination of human and machine intelligence requires an understanding of the...

In the realm of news consumption, individuals often establish recurrent patterns, integrating diverse sources into distinct repertoires. However, these patterns can change during unprecedented events ...

We analyze and propose a solution for the exposure of vulnerable users to harmful content during their interaction with contact recommender systems in social platforms. Our approach is dedicated to ma...

Digital Journalism has an important role to play in encouraging and publishing research with societal relevance that advances digital journalism studies as a field. In this article we discuss the mult...

The Causal Effect (CE) is a numerical measure of causal influence of variables on observed results. Despite being widely used in many areas, only preliminary attempts have been made to use CE as an at...

These results demonstrate the feasibility of implementing natural language processing tools in the routine of a cancer center to extract and code valuable information from pathology reports. Our recom...

A high-level précis of the Synthesis Report can be found in the Summary for Policymakers Recommendations for a Global AI Auditing Framework: Summary of Standards and Features. The growing integration...

Computer-Using Agents (CUA) enable users to automate increasingly-complex tasks using graphical interfaces such as browsers. As many potential tasks require personal data, we propose Computer-Using Pe...

Compositionality and compositional generalization--the ability to understand novel combinations of known concepts--are central characteristics of human language and are hypothesized to be essential fo...

The International Semantic Web Research School (ISWS) is a week-long intensive program designed to immerse participants in the field. This document reports a collaborative effort performed by ten team...

This study demonstrates the use of GPT-4 and variants, advanced language models readily accessible to many social scientists, in extracting political networks from text. This approach showcases the no...

The origin of the variability in accretion disks of active galactic nuclei (AGN) is still unknown, but its behavior can be characterized by modeling the time series of optical wavelength fluxes coming...

Explainable artificial intelligence (XAI) and fair learning have made significant strides in various application domains, including criminal recidivism predictions, healthcare settings, toxic comment ...

The notion of rank of a Boolean function has been a cornerstone in the theory of PAC learning, enabling quasipolynomial-time learning algorithms for polynomial-size decision trees. We present a novel ...

This paper combines two significant areas of political science research: measuring individual ideological position and cohesion. Although both approaches help analyze legislative behaviors, no unified...

The digitalization of public administration has advanced significantly on a global scale. Many governments now view digital platforms as essential for improving the delivery of public services and fos...

This study investigates the concept of frames in the realm of online polarization, with a focus on social media platforms. The research extends the understanding of how frames–emerging, complex, and...

As I supposed everyone else did when asked by Tamer to write an article with Advice to Mid-Career Researchers, I read all the previous articles in this series to understand what this paper should be a...

Despite the wide use of $k$-Nearest Neighbors as classification models, their explainability properties remain poorly understood from a theoretical perspective. While nearest neighbors classifiers off...

Proof assistants based on dependent type theory, such as Coq, Lean and Agda, use different universes to classify types, typically combining a predicative hierarchy of universes for computationally-rel...

This data collection contains diachronic Word Usage Graphs (WUGs) for Spanish. Find a description of the data format, code to process the data and further datasets on the WUGsite. Please find more inf...

Feature attribution methods have become essential for explaining machine learning models. Many popular approaches, such as SHAP and Banzhaf values, are grounded in power indices from cooperative game ...

Abstract We present a joint analysis of transit timing variations (TTVs) and Doppler data for the transiting exoplanet system TOI-4504. TOI-4504 c is a warm Jupiter-mass planet that exhibits the large...

Let 𝓓 be a collection of D strings of total length n over an alphabet of size σ. We consider the so-called top-k document retrieval problem: given a short string P and an integer k, list the ident...

Cypher has so far been the most commonly used query language for property graphs, and served as the foundation of the recently standardized graph query language GQL. In designing the features of GQL, ...

The variety of goods obtained from root crops, particularly cassava and sweet potatoes, is getting low, thereby affecting their sustainability. The researcher has produced a syrup by combining cassava...

We study the problem of evaluating a Monadic Second Order (MSO) query over strings under updates in the setting of direct access. We present an algorithm that, given an MSO query with first-order free...

The growing need for sustainable waste management calls for more efficient and accessible recycling systems. This paper introduces SmartBottle+, an artificial intelligence (AI) powered recycling rewar...

A database D may be inconsistent wrt a given set IC of integrity constraints. Consistent Query Answering (CQA) is the problem of computing from D the answers to a query that are consistent wrt IC . Co...

We present a design and implementation of an in-memory object graph store, dubbed εStore. Our key innovation is a storage model - epsilon store - that equates an object on the heap to a node in a gra...

Reading acquisition is one the main keys for school success and a crucial component for empowering individuals to participate meaningfully in society. Yet, it is still a challenging skill to acquire f...

We present a theoretical framework for the extraction and transformation of text documents. We propose to use a two-phase process where the first phase extracts span-tuples from a document, and the se...

The FM-index is a fundamental data structure used in bioinformatics to efficiently search for strings and index genomes. However, the FM-index can pose computational challenges, particularly in the co...

Breast cancer remains a significant health concern for women at various stages of life, impacting both productivity and reproductive health. Recent advancements in deep learning (DL) have enabled subs...