Knowledge catalogue
arXiv:2606.00676v1 Announce Type: new Abstract: This work presents a configurable pipeline for generating semantic-segmentation-ready agricultural datasets from Sentinel-2 imagery and EuroCrops parcel
arXiv:2606.00016v1 Announce Type: cross Abstract: Detecting AI-generated text is becoming increasingly challenging as modern language models approach human-level fluency and can evade detectors that r
arXiv:2606.01258v1 Announce Type: cross Abstract: Standard positional encodings for transformers - sinusoidal and rotary (RoPE) - treat every position as equally local: they encode where a token is, b
arXiv:2602.12972v2 Announce Type: replace-cross Abstract: In online advertising, marketing interventions such as coupons introduce significant confounding bias into Click-Through Rate (CTR) prediction
arXiv:2606.00910v1 Announce Type: new Abstract: Composed Video Retrieval (CoVR) seeks the target video that results from applying a free-form textual modification to a reference video. We address the
arXiv:2601.22202v2 Announce Type: replace-cross Abstract: Semantic communication (SemCom) emerges as a transformative paradigm for traffic-intensive visual data transmission, shifting focus from raw d
arXiv:2605.30836v1 Announce Type: new Abstract: Recent SVD based compression methods for large language models like SVD LLM and Basis Sharing can be unified under one optimization problem. While mathe
arXiv:2602.01173v3 Announce Type: replace Abstract: Understanding the multi-dimensional attributes and intensity nuances of image-evoked emotions is pivotal for advancing machine empathy and empowerin
arXiv:2603.09453v3 Announce Type: replace-cross Abstract: Foundation models are increasingly being deployed in contexts where understanding the uncertainty of their outputs is critical to ensuring res
arXiv:2605.30103v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as generators in iterative neural architecture search (NAS), yet no formal convergence theory exists
arXiv:2605.29695v1 Announce Type: new Abstract: Approximately 10% of newborns require assistance to initiate breathing at birth, and around 5% need ventilation support. Fetal heart rate (FHR) monitori
arXiv:2508.08677v2 Announce Type: replace-cross Abstract: Online Class-Incremental Learning (OCIL) enables models to learn continuously from non-i.i.d. data streams. Since samples of the data streams
arXiv:2601.07525v2 Announce Type: replace-cross Abstract: Natural generation allows Large Language Models (LLMs) to produce free-form responses with rich reasoning, yet the lack of structure makes out
arXiv:2605.28420v1 Announce Type: new Abstract: While machine learning (ML) architectures have evolved rapidly to account for complex data, loss functions like cross-entropy remain mostly structure-ag
arXiv:2605.24481v2 Announce Type: replace Abstract: The 1st Cross-Domain EgoCross Challenge at EgoVis, CVPR 2026 evaluates whether multimodal large language models can reason over egocentric videos ac
arXiv:2605.27287v1 Announce Type: new Abstract: Multilevel Image thresholding is an important preprocessing algorithm in computer vision applications nowadays. Since most common thresholding methods t
arXiv:2605.26956v1 Announce Type: new Abstract: Entity linking is a key component of many downstream NLP systems, yet existing approaches are often tied to the specific target knowledge bases and doma
arXiv:2605.26741v1 Announce Type: cross Abstract: Inverse design of materials has significantly advanced target-driven formulation optimization, yet existing materials machine learning benchmarks rema
arXiv:2508.02806v3 Announce Type: replace Abstract: Recently, a significant improvement in the accuracy of 3D human pose estimation has been achieved by combining convolutional neural networks (CNNs)
arXiv:2605.24406v1 Announce Type: new Abstract: Optimizing HVAC (Heating, Ventilation and Air Conditioning) can enhance a building's energy efficiency while providing comfort levels for its occupants.
arXiv:2605.24038v1 Announce Type: cross Abstract: Forecasting aurora borealis visibility matters for space weather research and aurora tourism. Visibility at a site and night depends on two distinct f
arXiv:2605.24458v1 Announce Type: cross Abstract: The integration of fairness and privacy in centralized data-driven applications is critical, especially as these systems increasingly influence sector
arXiv:2605.24418v1 Announce Type: new Abstract: Federated learning is used in medical imaging where privacy prohibits centralizing data. Standard federated algorithms assume homogeneous hardware, iden
arXiv:2605.23970v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as automatic judges for summarization and dialogue evaluation. Prior work has documented biases such
arXiv:2501.19389v4 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) on resource-constrained clients remains a challenging problem. Recent works have fused low-rank adaptation
arXiv:2605.24192v1 Announce Type: cross Abstract: The neural-network denoising functions which form the backbone of image diffusion models are remarkably consistent in their generalization behaviour a
arXiv:2605.25030v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems offer a promising approach to reduce hallucinations and improve answer accuracy in large language models (L
arXiv:2510.12787v4 Announce Type: replace Abstract: We present Ax-Prover, a multi-agent system for automated theorem proving in Lean that can solve problems across diverse scientific domains and opera
arXiv:2512.15767v2 Announce Type: replace-cross Abstract: Simulating complex unsteady physical phenomena relies on detailed mathematical models, simulated for instance by using the Finite Element Meth
arXiv:2605.23412v1 Announce Type: new Abstract: While social media platforms, such as Twitter, provide a medium for large-scale opinion sharing during news events, it is manually impossible for indivi
arXiv:2510.08945v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) has emerged as a promising paradigm for improving factual accuracy in large language models (LLMs). We introduc
arXiv:2605.22874v1 Announce Type: new Abstract: Effectively translating between natural language (NL) and formal logics like Linear Temporal Logic (LTL) requires expertise that limits formal verificat
arXiv:2605.21542v1 Announce Type: new Abstract: Country-level temporal panels are widely used in empirical analysis. Researchers often need to audit how different entities respond to historical signal
arXiv:2603.22508v2 Announce Type: replace Abstract: Mapping is essential in robotics and autonomous systems because it provides the spatial foundation for path planning. Efficient mapping enables plan
arXiv:2605.21352v1 Announce Type: new Abstract: The growing use of fast-switching power electronics has made partial discharge (PD) analysis under switching-voltage excitation increasingly important,
arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,
arXiv:2605.19855v1 Announce Type: cross Abstract: Concept-based Explainable Artificial Intelligence (XAI) interprets deep learning models using human-understandable visual features (e.g., textures or
arXiv:2603.13609v2 Announce Type: replace Abstract: Despite progress in deep learning for shared micromobility demand prediction, the systematic design and statistical validation of temporal input str
arXiv:2603.15411v2 Announce Type: replace Abstract: Accurate prediction of crop states (e.g., phenology stages and cold hardiness) is essential for timely farm management decisions such as irrigation,
arXiv:2605.20033v1 Announce Type: new Abstract: Multimodal large language models often generate reasoning chains containing subtle errors that lead to incorrect answers. Current verification approache
arXiv:2601.05391v2 Announce Type: replace Abstract: Accurate multistep forecasting of node-level attributes on dynamic graphs is critical for applications ranging from financial trust networks to biol
arXiv:2605.17611v1 Announce Type: cross Abstract: Software fault prediction (SFP) is a critical task in software engineering, enabling early identification of faults in modules to improve software qua
arXiv:2605.17151v1 Announce Type: new Abstract: In sales and marketing, customer segmentation is an important tool for formulating strategies for customer treatment and supply chain management. Most s
arXiv:2605.17921v1 Announce Type: new Abstract: Streaming video requires handling dynamic information density under strict latency budgets. Yet, existing methods typically employ static strategies, su
arXiv:2605.16908v1 Announce Type: cross Abstract: Security systems demand continuous, cryptograph- ically robust identity verification without requiring subjects to carry physical tokens, smart cards,
arXiv:2605.17684v1 Announce Type: new Abstract: While increasing research focuses on the emotional well-being of agile team members, a significant gap remains in emotion monitoring studies for Scrum M
arXiv:2605.17969v1 Announce Type: new Abstract: Despite rapid advances in text-to-image generation, faithfully realizing user intent remains challenging, often requiring manual multi-turn trial and er
arXiv:2605.17364v1 Announce Type: new Abstract: Media bias detection has predominantly been framed as a classification task: assign a political label to an article or outlet. We argue this framing is
arXiv:2605.18082v1 Announce Type: new Abstract: pyforce is a Python package implementing Data-Driven Reduced Order Modelling techniques for applications to multi-physics problems, mainly set in the Nu
arXiv:2605.16454v1 Announce Type: new Abstract: Seismic prediction remains challenging due to the highly nonlinear and chaotic dynamics of earthquake signals. While classical deep learning models such
arXiv:2605.17566v1 Announce Type: new Abstract: With the rapid progress of multimodal foundation models and predictive pre-training, an important open question is how to equip 3D point clouds with a p
arXiv:2605.16232v1 Announce Type: cross Abstract: The accelerating convergence of smart metering, generative artificial intelligence, and quantum-inspired combinatorial optimisation is reshaping how e
arXiv:2605.16076v1 Announce Type: cross Abstract: Plant disease detection is still largely manual in Bangladesh, where extension workers eyeball leaf samples across millions of smallholdings. We built
arXiv:2605.15984v1 Announce Type: cross Abstract: Toxic speech detection has become a crucial challenge in maintaining safe online communication environments. However, existing approaches to toxic spe
arXiv:2511.05159v2 Announce Type: replace-cross Abstract: Convex clustering is a well-regarded clustering method, resembling the similar centroid-based approach of Lloyd's k-means, without requiring a
arXiv:2605.14266v1 Announce Type: new Abstract: Integration of artificial intelligent (AI) agents in higher education is transforming teaching, learning and administrative processes. Although existing
arXiv:2605.14606v1 Announce Type: new Abstract: Accurate precipitation nowcasting over extended horizons (0-3 hours) is essential for disaster mitigation and operational decision-making, yet remains a
arXiv:2603.23129v2 Announce Type: replace Abstract: Godel agent realize recursive self-improvement: an agent inspects its own policy and traces and then modifies that policy in a tested loop. We intro
arXiv:2605.14651v1 Announce Type: new Abstract: Urban vegetation monitoring plays a vital role in understanding environmental changes, yet comprehensive datasets for this purpose remain limited. To ad
arXiv:2605.14224v1 Announce Type: cross Abstract: We present an in-depth analysis of the Koopman semigroup via wavelet transform. Towards this goal, we start by introducing the wavelet-based observabl