Knowledge catalogue
arXiv:2604.25432v1 Announce Type: new Abstract: Shadows are a prevalent problem in remote sensing imagery (RSI), degrading visual quality and severely limiting the performance of downstream tasks like
arXiv:2604.23045v1 Announce Type: new Abstract: Systematic biases in Global Circulation Model (GCM) outputs limit their direct applicability in regional planning, necessitating bias correction. Correc
arXiv:2512.03915v3 Announce Type: replace-cross Abstract: In large-scale AI training, Sparse Mixture-of-Experts (s-MoE) layers enable scaling by activating only a small subset of experts per token. An
arXiv:2603.03555v2 Announce Type: replace-cross Abstract: As multi-agent Large Language Model (LLM) systems scale, evaluating their emergent coordination dynamics becomes increasingly critical. Howeve
arXiv:2511.10161v2 Announce Type: replace Abstract: In the Data-Centric Artificial Intelligence (AI) paradigm, improving data quality is essential for robust machine learning. However, many denoising
arXiv:2604.23728v1 Announce Type: cross Abstract: Recent advances in autonomous driving have motivated research on pedestrian intention prediction, which aims to infer future crossing decisions and ac
arXiv:2604.23947v1 Announce Type: new Abstract: We introduce GameDAI, a hierarchical multi-agent framework that transforms instructor-provided questions into fully playable, pedagogically grounded edu
arXiv:2511.15197v2 Announce Type: replace Abstract: Reference-based object composition involves integrating foreground reference image with background scene to produce harmonious fused image. This tas
arXiv:2604.24031v1 Announce Type: new Abstract: The encoder-decoder framework has become widely popular nowadays. In this model, the encoder extracts informative visual features from an input image, a
arXiv:2604.23435v1 Announce Type: cross Abstract: Radiographic grading of knee osteoarthritis (KOA) with the Kellgren-Lawrence (KL) system is limited by inter-reader variability and the opacity of cur
arXiv:2604.23938v1 Announce Type: new Abstract: Target Safety Assessment (TSA) requires systematic integration of heterogeneous evidence, including genetic, transcriptomic, target homology, pharmacolo
arXiv:2604.24326v1 Announce Type: cross Abstract: The decentralization of modern energy systems is transforming consumers into prosumers who continuously exchange data with aggregators, peers, and mar
arXiv:2604.21936v1 Announce Type: new Abstract: Medical imaging research is increasingly shifting from controlled benchmark evaluation toward real-world clinical deployment. In such settings, applying
arXiv:2604.22220v1 Announce Type: new Abstract: Digital image watermarking has advanced rapidly for copyright protection of generative AI, yet the comparatively limited progress in watermark attack te
arXiv:2604.22597v1 Announce Type: new Abstract: Recent advancements in large language models have led to significant improvements across various tasks, including mathematical reasoning, which is used
Russell Contreras / Axios: How the Vatican is moving faster than most legacy institutions to shape AI rules and guardrails, with an AI framework, banning use of AI to write homilies, more — The Vatica
arXiv:2604.21028v1 Announce Type: cross Abstract: The increasing frequency and severity of global flood events highlights the need for the development of rapid and reliable flood prediction tools. Thi
arXiv:2601.18491v2 Announce Type: replace Abstract: The rise of AI agents introduces complex safety and security challenges arising from autonomous tool use and environmental interactions. Current gua
arXiv:2603.18677v2 Announce Type: replace-cross Abstract: Artificial intelligence is increasingly embedded in human decision making. In some cases, it enhances human reasoning. In others, it fosters e
arXiv:2510.04371v2 Announce Type: replace Abstract: AI agents are increasingly deployed in complex, interactive environments, yet their runtime remains a major bottleneck for training, evaluation, and
arXiv:2603.24111v3 Announce Type: replace-cross Abstract: The Industrial Internet of Things (IIoT) introduces significant security challenges as resource-constrained devices become increasingly integr
arXiv:2604.21193v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable fluency and versatility across a wide range of NLP tasks, yet they remain prone to factual ina
arXiv:2604.21471v1 Announce Type: new Abstract: Infrastructure-based localization enhances road safety and traffic management by providing state estimates of road users. Development is hindered by fra
arXiv:2604.19903v1 Announce Type: cross Abstract: Cement production is among the largest contributors to industrial air pollution, emitting ~3 Mt NOx/year. The industry-standard mitigation approach, s
arXiv:2604.20134v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) increasingly encounter difficulties in correlating heterogeneous alerts, interpreting multi-stage attack progressio
arXiv:2604.20651v1 Announce Type: new Abstract: Understanding the intricate dynamics of online discourse depends on large-scale deliberation data, a resource that remains scarce across interactive web
arXiv:2604.20288v1 Announce Type: new Abstract: Flight diversions are rare but high-impact events in aviation, making their reliable prediction vital for both safety and operational efficiency. Howeve
arXiv:2604.20714v1 Announce Type: new Abstract: Designing and optimizing multi-agent systems (MAS) is a complex, labor-intensive process of 'Agent Engineering.' Existing automatic optimization methods
arXiv:2604.20764v1 Announce Type: cross Abstract: This paper presents a personalized Battery Electric Vehicle (BEV) energy consumption estimation framework that integrates map-based contextual feature
arXiv:2604.19768v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit systematic miscalibration with rhetorical intensity not proportionate to epistemic grounding. This study tests th
arXiv:2509.15174v3 Announce Type: replace-cross Abstract: WARNING: This paper contains examples of offensive materials. To address the proliferation of toxic content on social media, we introduce SMAR
arXiv:2308.00513v2 Announce Type: replace Abstract: This paper introduces UVIO, a multi-sensor framework that leverages Ultra Wide Band (UWB) technology and Visual-Inertial Odometry (VIO) to provide r
arXiv:2506.22174v2 Announce Type: replace-cross Abstract: The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway
arXiv:2512.19302v2 Announce Type: replace Abstract: Large Vision--Language Models (LVLMs) hold great promise for advancing optical remote sensing (RS) analysis, yet existing reasoning segmentation fra
arXiv:2604.19658v1 Announce Type: new Abstract: Damage identification is a core task in structural health monitoring. In practice, however, its reliability is often compromised by confounding non-dama
arXiv:2604.19652v1 Announce Type: cross Abstract: In this paper, we propose a deep-learning framework for environmental sound deepfake detection (ESDD) -- the task of identifying whether the sound sce
arXiv:2604.18803v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed in settings where reliable visual grounding carries operational consequences, yet their behavi
arXiv:2505.11765v3 Announce Type: replace-cross Abstract: Agents powered by advanced large language models (LLMs) have demonstrated impressive capabilities across diverse complex applications. Recentl
arXiv:2604.18919v1 Announce Type: new Abstract: Analyzing topics extracted from text data in relation to external outcomes is important across fields such as computational social science and organizat
arXiv:2602.08129v2 Announce Type: replace-cross Abstract: Predicting interdependent load values in multiport scatterers is challenging due to high dimensionality and complex dependence between impedan
arXiv:2604.18467v1 Announce Type: new Abstract: Motivation: Peptide-protein interactions (PepPIs) are central to cellular regulation and peptide therapeutics, but experimental characterization remains
another interesting part of the hermes architecture is how it integrates with the atropos framework. the hermes agent runtime lives inside an atropos compatible environment where multi-turn tool use,
arXiv:2512.12022v2 Announce Type: replace Abstract: Decentralized federated learning (DFL) has emerged as a promising paradigm that enables multiple clients to collaboratively train machine learning m
arXiv:2604.17110v1 Announce Type: new Abstract: Clinical AI development has traditionally followed a collaborative paradigm that depends on close interaction between clinicians and specialized AI team
arXiv:2604.17745v1 Announce Type: new Abstract: Recent advances in large language models have highlighted their potential to automate computational research, particularly reproducing experimental resu
arXiv:2507.09025v4 Announce Type: replace Abstract: We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into subquadratic architectur
arXiv:2604.16379v1 Announce Type: cross Abstract: Industrial B2B applications (e.g., construction site risk prediction, material procurement) face extreme data sparsity yet feature rich textual intera
arXiv:2407.09514v3 Announce Type: replace-cross Abstract: Recently, metal-organic frameworks (MOFs) have demonstrated their potential as solid-state electrolytes in proton exchange membrane fuel cells
arXiv:2604.16234v1 Announce Type: cross Abstract: Academic integrity continues to face the persistent challenge of examination cheating. Traditional invigilation relies on human observation, which is
arXiv:2604.16205v1 Announce Type: cross Abstract: Computational X-ray absorption near-edge structure (XANES) is widely used to probe local coordination environments, oxidation states, and electronic s
arXiv:2511.14791v2 Announce Type: replace-cross Abstract: Early detection of faults in district heating substations is imperative to reduce return temperatures and enhance efficiency. However, progres
arXiv:2509.13590v3 Announce Type: replace-cross Abstract: The rapid advancement of artificial intelligence (AI) in healthcare imaging has revolutionized diagnostic medicine and clinical decision-makin
arXiv:2604.15830v1 Announce Type: new Abstract: Reinforcement learning has become a powerful approach for enhancing large language model reasoning, but faces a fundamental dilemma: training on easy pr
arXiv:2508.16739v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles (UAVs) have become increasingly important in disaster emergency response by facilitating aerial video analysis. Due to the
arXiv:2510.27617v2 Announce Type: replace Abstract: Automation of Register Transfer Level (RTL) design can help developers meet increasing computational demands. Large Language Models (LLMs) show prom
Maria Deutscher / SiliconANGLE: Expo, which develops an eponymous React Native framework and provides cloud services for building cross-platform apps, raised a 45M Series B led by Georgian — Expo, the
Great paper on self-improving agents. Why? We need to think more deeply about AI agent system design. The protocol specifies a framework for proposing, assessing, and committing improvements with audi
arXiv:2604.13101v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into aviation safety decision-making represents a significant technological advancement, yet their sta
arXiv:2604.14691v1 Announce Type: cross Abstract: LLM-empowered agent simulations are increasingly used to study social emergence, yet the micro-to-macro causal mechanisms behind macro outcomes often
arXiv:2603.22564v2 Announce Type: replace Abstract: Understanding cellular trajectories via time-resolved single-cell transcriptomics is vital for studying development, regeneration, and disease. A ke