article stringlengths 507 295k | abstract stringlengths 417 1.92k | category listlengths 1 6 |
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# 1 Introduction
Relational databases serve as the foundation for data management, supported by decades of mature infrastructure development and a wide array of sophisticated analytical tools. However, much of today’s data exists as raw, unstructured text – such as academic articles, medical records, and business repo... | Relational databases are central to modern data management, yet most data exists in unstructured forms like text documents. To bridge this gap, we leverage large language models (LLMs) to automatically synthesize a relational database by generating its schema and populating its tables from raw text. We introduce SQUiD,... | [
"cs.DB",
"cs.CL"
] |
# 1 Introduction
Low-Rank Adaptation (LoRA) [20] is a widely-used parameter-efficient finetuning technique for large-scale pretrained models which enables finetuning billion-scale Large Language Models (LLMs) on a single consumer-grade GPU. This has made it the go-to method for finetuning LLMs in settings with limited... | Bayesian methods have recently been used to improve LoRA finetuning and, although they improve calibration, their effect on other metrics (such as accuracy) is marginal and can sometimes even be detrimental. Moreover, Bayesian methods also increase computational overheads and require additional tricks for them to work ... | [
"cs.LG",
"cs.AI",
"cs.CL",
"stat.ML"
] |
# 1 Introduction
The global optimization of black-box objective functions under expensive, black-box constraints— where both are only accessible via costly point-wise evaluations—is a fundamental problem in fields such as machine learning (ML), engineering design, robotics, and natural sciences. For instance, in autom... | Bayesian optimization is a powerful tool for solving real-world optimization tasks under tight evaluation budgets, making it well-suited for applications involving costly simulations or experiments. However, many of these tasks are also characterized by the presence of expensive constraints whose analytical formulation... | [
"cs.LG"
] |
# 1 Introduction
LLMs have demonstrated remarkable prowess in various tasks [90, 7], yet their applications to finance [40, 78, 75] require the continual push of the limits of model capabilities [80]. Although there are already several specialized benchmarks [76, 36, 5] that evaluate LLM in core financial tasks, they ... | Recent advances in large language models (LLMs) have accelerated progress in financial NLP and applications, yet existing benchmarks remain limited to monolingual and unimodal settings, often over-relying on simple tasks and failing to reflect the complexity of real-world financial communication. We introduce MultiFinB... | [
"cs.CL"
] |
# I. INTRODUCTION
researchers and engineers today, offering a framework for understanding how simple, decentralized agents can collectively produce complex, emergent behaviors. Traditional swarms, as observed in nature—–such as flocks of birds, schools of fish, or colonies of ants—–are characterized by local interacti... | Swarm intelligence traditionally refers to systems of simple, decentralized agents whose local interactions lead to emergent, collective behavior. Recently, the term 'swarm' has been extended to describe AI systems like OpenAI's Swarm, where large language models (LLMs) act as collaborative agents. This paper contrasts... | [
"cs.AI"
] |
# I. INTRODUCTION
Smartphones and scanners are used to capture images of documents containing tables with vital information. Manual extraction is time-consuming. However, a shortage of annotated datasets has made developing effective deep learning models for table detection challenging.
Data augmentation has been rec... | Document pages captured by smartphones or scanners often contain tables, yet manual extraction is slow and error-prone. We introduce an automated LaTeX-based pipeline that synthesizes realistic two-column pages with visually diverse table layouts and aligned ground-truth masks. The generated corpus augments the real-wo... | [
"cs.CV",
"cs.AI"
] |
# 1 Introduction
Concurrent accesses to databases are typically grouped in transactions which define units of work that should be isolated from other concurrent computations and resilient to failures. Modern databases provide different levels of isolation for transactions with different trade-offs between consistency ... | Concurrent accesses to databases are typically grouped in transactions which define units of work that should be isolated from other concurrent computations and resilient to failures. Modern databases provide different levels of isolation for transactions that correspond to different trade-offs between consistency and ... | [
"cs.DB",
"cs.PL"
] |
# 1 Introduction
Software testing is a critical activity throughout the software development life cycle, playing a key role in early defect detection and compliance with requirements [14, 30]. In particular, testing driven by requirements is conducted to validate systems before their deployment [13]. This is especiall... | As software systems evolve, test suites tend to grow in size and often contain redundant test cases. Such redundancy increases testing effort, time, and cost. Test suite minimization (TSM) aims to eliminate such redundancy while preserving key properties such as requirement coverage and fault detection capability. In t... | [
"cs.SE"
] |
# 1 Introduction
The 2023- Israel-Hamas War (the war) began following a surprise attack on Israeli military targets and civilians by Palestinian militant groups operating from within the Gaza Strip on October 7, 2023. Over 1,200 Israeli civilians, military personnel, and internationals were killed and another 254 Isra... | Aerial bombardment of the Gaza Strip beginning October 7, 2023 is one of the most intense bombing campaigns of the twenty-first century, driving widespread urban damage. Characterizing damage over a geographically dynamic and protracted armed conflict requires active monitoring. Synthetic aperture radar (SAR) has prece... | [
"cs.CV"
] |
# 1. Introduction
Cell profiling aims to create meaningful representations of cells, which can be utilized for validating compounds in drug discovery and understanding disease mechanisms [8]. Among various cell profiling methods, image-based profiling using microscope images is the most cost-effective approach for gen... | Image-based cell profiling aims to create informative representations of cell images. This technique is critical in drug discovery and has greatly advanced with recent improvements in computer vision. Inspired by recent developments in non-contrastive Self-Supervised Learning (SSL), this paper provides an initial explo... | [
"cs.CV"
] |
# 1 Introduction
With the rapid development of generative models in recent years [1, 2, 3, 4], image composition has received increasing attention owing to its capacity for controlled generation [5, 6, 7]. However, since the implanted foreground and the new background originate from different sources, this discrepancy... | We introduce a model named DreamLight for universal image relighting in this work, which can seamlessly composite subjects into a new background while maintaining aesthetic uniformity in terms of lighting and color tone. The background can be specified by natural images (image-based relighting) or generated from unlimi... | [
"cs.CV"
] |
# I. INTRODUCTION
Robust 3D perception is a cornerstone of intelligent systems, enabling a wide range of capabilities from autonomous navigation [1], [2] and manipulation in robotics to augmented reality and scene understanding in consumer devices [3]. Specifically in robotics, accurate and efficient depth estimation ... | Depth estimation is crucial for intelligent systems, enabling applications from autonomous navigation to augmented reality. While traditional stereo and active depth sensors have limitations in cost, power, and robustness, dual-pixel (DP) technology, ubiquitous in modern cameras, offers a compelling alternative. This p... | [
"cs.CV",
"cs.RO"
] |
# 1 Introduction
Local consistency is an important concept in various areas such as Bayesian statistics, relational databases and quantum foundations. In broad terms, local consistency refers to a family of partial structures (such as marginal distributions or projections) that agree on their overlapping parts. Local ... | Local consistency arises in diverse areas, including Bayesian statistics, relational databases, and quantum foundations. Likewise, the notion of functional dependence arises in all of these areas. We adopt a general approach to study logical inference in a setting that enables both global inconsistency and local consis... | [
"quant-ph",
"cs.DB"
] |
# 1. Introduction
Climaborough12 is a research project, co-funded by the European Union and CINEA, aimed at bridging the gap between the design and implementation of urban innovations, tackling climate change and its consequential need for rapid adaptation and mitigation. Specifically, it aims to overcome the bottlene... | The EU-funded Climaborough project supports European cities to achieve carbon neutrality by 2030. Eleven cities in nine countries will deploy in real conditions products and services fostering climate transition in their local environment. The Climaborough City Platform is being developed to monitor the cities' overall... | [
"cs.SE",
"cs.AI",
"cs.CY"
] |
# I. INTRODUCTION
Formally specifying software has remained one of the challenging tasks in software engineering. The challenges are apparent: the specifications must be well-defined, unambiguous, complete, consistent, and aligned with the stakeholder needs. Being mostly human-centric, developing more formal specifica... | Like any other discipline, Large Language Models (LLMs) have significantly impacted software engineering by helping developers generate the required artifacts across various phases of software development. This paper presents a case study comparing the performance of popular LLMs GPT, Claude, Gemini, and DeepSeek in ge... | [
"cs.SE",
"cs.AI"
] |
# 1 Introduction
With global economic integration and increasing air transport demand, the aviation industry faces dual pressures from accelerated technological advancement and rising safety standards. Aviation theory training serves as the core foundation for aviation safety operations, providing essential theoretica... | Aviation training is a core link in ensuring flight safety, improving industry efficiency and promoting sustainable development. It not only involves flight simulation but also requires the learning of a great deal of professional aviation theory knowledge. In the existing training system, the knowledge is mainly impar... | [
"cs.AI"
] |
# 1 Introduction
Multimodal Large Language Models (MLLMs)[22, 30, 1, 8] excel at cross-modal tasks such as image captioning[19] and visual question answering [3, 39]. Owing to their high computational cost, they are typically offered via cloud service (e.g. GPT-4o [22], Gemini [30]). This setup, while convenient, expo... | Multimodal Large Language Models (MLLMs) have shown great promise but require substantial computational resources during inference. Attackers can exploit this by inducing excessive output, leading to resource exhaustion and service degradation. Prior energy-latency attacks aim to increase generation time by broadly shi... | [
"cs.CL",
"cs.CR"
] |
# 1 Introduction
By the developments of MLLMs [41, 79, 2, 71, 74, 75, 53, 23, 48, 60, 78], vision-based perception tasks have evolved toward a more comprehensive and interleaved understanding. Among these tasks, dense understanding, characterized by space-aware semantic interpretations of the physical world, has becom... | Multimodal Large Language Models (MLLMs) require comprehensive visual inputs to achieve dense understanding of the physical world. While existing MLLMs demonstrate impressive world understanding capabilities through limited field-of-view (FOV) visual inputs (e.g., 70 degree), we take the first step toward dense underst... | [
"cs.CV"
] |
# 1 Introduction
In today’s rapidly evolving information landscape, distinguishing fact from misinformation is becoming more challenging, especially with the rise of AI-generated content. Robust claim verification systems, leveraging NLP methods to automatically assess the veracity of claims (Glockner et al., 2022a,b;... | Integrating knowledge graphs (KGs) to enhance the reasoning capabilities of large language models (LLMs) is an emerging research challenge in claim verification. While KGs provide structured, semantically rich representations well-suited for reasoning, most existing verification methods rely on unstructured text corpor... | [
"cs.CL",
"cs.AI",
"cs.DB"
] |
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