Knowledge catalogue
arXiv:2606.17467v3 Announce Type: replace-cross Abstract: Prompt injection defenses evaluated on synthetic benchmarks do not generalize to real enterprise documents, which are longer, denser, and inte
arXiv:2609.14591v1 Announce Type: new Abstract: Participation in federated learning (FL) comes at a cost. Clients trade off privacy, communication, and compute costs for potentially greater gains in m
arXiv:2609.14703v1 Announce Type: new Abstract: Dental caries and endodontic disease are among the most common health conditions worldwide, and intraoral periapical radiographs are central to their de
arXiv:2609.13734v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in real-world high-stakes applications, effective governance has become essential. Existing
arXiv:2609.13523v1 Announce Type: cross Abstract: We develop a conceptual and operational account of Positive Topology starting from a basic relation between points or models and observable properties
arXiv:2507.19738v2 Announce Type: replace Abstract: While accurate LiDAR depth has been shown to improve stereo matching, high-end LiDAR remains costly and difficult to deploy at scale, motivating gui
arXiv:2609.15950v1 Announce Type: new Abstract: Record-level differential privacy exposes a structural misalignment in personalized federated learning when client-specific variation is low-dimensional
arXiv:2609.15292v1 Announce Type: new Abstract: Automatic Item Generation (AIG) is pivotal for personalized education, yet guaranteeing the pedagogical value of generated items remains a bottleneck. E
arXiv:2609.13340v1 Announce Type: cross Abstract: Breast ultrasound imaging plays an important role in the early detection and diagnosis of breast cancer, particularly for patients with dense breast t
arXiv:2609.14473v1 Announce Type: new Abstract: Personal AI assistants hold the potential to evolve from digital interfaces into embodied companions capable of guiding users through complex physical a
arXiv:2503.09197v2 Announce Type: replace Abstract: Image quality scoring and interpreting are two fundamental components of Image Quality Assessment (IQA). The former quantifies image quality, while
arXiv:2609.14036v1 Announce Type: cross Abstract: Fresh fruits and vegetables (FFVs) are highly perishable, and cold-chain breaks contribute significantly to global food waste. While Machine Learning
arXiv:2609.15379v1 Announce Type: new Abstract: Machine learning can be crucial to help scale complex signal processing applications in scenarios such as healthcare. However, these machine learning mo
arXiv:2609.13389v1 Announce Type: new Abstract: Mapping textual specifications into formal representations is essential for ensuring the correctness of protocol designs and implementations. LLM-genera
arXiv:2609.14589v1 Announce Type: new Abstract: Imposing explicit trajectory constraints in robot visual servoing remains challenging. Existing tracking methods achieve fast responses by mapping visua
arXiv:2609.15361v1 Announce Type: cross Abstract: Effective communication is a cornerstone of distributed intelligence in Multi-Agent Reinforcement Learning (MARL), yet ensuring that generated message
arXiv:2609.15488v1 Announce Type: new Abstract: Machine learning models process large amounts of data, and Principal Component Analysis (PCA) is a widely used technique to reduce the dimensionality of
arXiv:2609.13545v1 Announce Type: cross Abstract: Learning-based adaptive control of robotic manipulators with non-observable friction memory has been addressed by attention- based meta-controllers wh
arXiv:2609.15915v1 Announce Type: new Abstract: Meta-reinforcement learning (meta-RL) enables agents to adapt to unseen tasks with limited experience. Despite its promise, the application of meta-RL i
arXiv:2609.13657v1 Announce Type: new Abstract: Traditional recommender systems are typically trained to predict what item users will interact with next, but not why. However, offering personalized ev
arXiv:2609.15022v1 Announce Type: new Abstract: Defense is a knowledge-intensive domain that requires precise understanding of specialized terminology, doctrinal concepts, operational procedures, and
arXiv:2609.15498v1 Announce Type: new Abstract: Recurrent Transformers reusing their weights rather than stacking L distinct layers are becoming widely adopted due to their parameter efficiency [1,2,3
arXiv:2609.13721v1 Announce Type: new Abstract: Quantum Natural Language Processing (QNLP) uses pregroup grammars to translate grammatical structure into diagrammatic representations and quantum circu
arXiv:2609.14634v1 Announce Type: new Abstract: Recently, 3D Gaussian Splatting SLAM (3DGS-SLAM) has gained significant momentum in simultaneous localization and 3DGS scene reconstruction. In real-wor
arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why i
arXiv:2609.13823v1 Announce Type: new Abstract: Point cloud data face serious semantic privacy risks during acquisition, transmission, and cross-institutional sharing. Existing methods mostly rely on
arXiv:2609.13856v1 Announce Type: new Abstract: Enterprise customer support systems must answer customer questions correctly, retrieve the right policy information, use customer context, and pass diff
arXiv:2609.13245v1 Announce Type: new Abstract: Speculative Jacobi Decoding (SJD) is an important approach for accelerating autoregressive image generation. Although SJD has shown superior performance
arXiv:2609.14278v1 Announce Type: cross Abstract: Accurate sperm detection is essential for computer-assisted semen analysis, yet it remains challenging in microscopic images due to dense distribution
arXiv:2609.13776v1 Announce Type: new Abstract: Integrating heterogeneous relational databases into a centralized ontology remains a persistent challenge in enterprise knowledge representation, primar
arXiv:2608.25536v2 Announce Type: replace-cross Abstract: In this work, we propose a view on electronic Neuromorphic Design Automation (eNDA), which we see as a design automation flow that bridges com
arXiv:2402.18945v5 Announce Type: replace-cross Abstract: Although pre-training achieves remarkable performance, it suffers from task-agnostic backdoor attacks due to vulnerabilities in data and train
arXiv:2609.15503v1 Announce Type: new Abstract: Deep learning models have become the standard tool for document rectification and illumination correction, yet their performance is fundamentally bound
arXiv:2609.14118v1 Announce Type: cross Abstract: Online understanding of who is talking to the camera wearer is a key capability for egocentric social interaction. However, existing talk-to-me (TTM)
arXiv:2609.15082v1 Announce Type: cross Abstract: Passive counterweights are simple gravity compensators, but a counterweight selected from a single pose is not generally optimal for the configuration
arXiv:2609.15205v1 Announce Type: cross Abstract: Table extraction from texts is an important task for information systems, and recent approaches that prompt large language models (LLMs) with instruct
arXiv:2505.20132v2 Announce Type: replace-cross Abstract: Tensorizing a neural network involves reshaping some or all of its dense weight matrices into higher-order tensors and approximating them usin
arXiv:2609.13334v1 Announce Type: cross Abstract: Enterprise AI agents often succeed in a demonstration and then stall once they must operate day after day. An industry report estimates that most pilo
arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate storie
arXiv:2510.17714v3 Announce Type: replace-cross Abstract: Novel Markov Chain Monte Carlo (MCMC) methods have enabled the generation of large ensembles of redistricting plans modeled as a graph partiti
arXiv:2502.09192v3 Announce Type: replace Abstract: Anthropomorphism, or the attribution of human traits to technology, is an automatic and unconscious response that occurs even in those with advanced
arXiv:2609.13151v1 Announce Type: new Abstract: Leading multilingual speech recognition models like Whisper transcribe diverse, low-resource languages without language-specific training but are comput
arXiv:2609.14817v1 Announce Type: new Abstract: In Yoruba, pitch alone separates oko (husband, Mid), okd{o (vehicle, Low), and okd{o (hoe, High) -- the diacritics ARE the tone marks. Yet character err
arXiv:2609.13552v1 Announce Type: new Abstract: Generative AI is increasingly being used informally in Air Traffic Management (ATM) for tasks such as flight plan generation, trajectory interpretation,
arXiv:2609.13547v1 Announce Type: new Abstract: We study switching regret in adversarial multi-armed bandits, where the learner competes with an arm sequence that changes at most S times. When S is kn
arXiv:2411.04319v1 Announce Type: cross Abstract: Text-to-SQL enables users to interact with databases through natural language, simplifying access to structured data. Although highly capable large la
arXiv:2607.10436v3 Announce Type: replace-cross Abstract: Input--output feedback linearization fails at decoupling singularities, where the decoupling matrix loses rank, the relative degree is lost, a
arXiv:2607.22365v2 Announce Type: replace Abstract: High-complexity operational environments require methods that characterize temporally distributed patterns rather than classify isolated events. Thi
arXiv:2309.05955v5 Announce Type: replace Abstract: Accurate disturbance estimation is essential for safe robot operations. The recently proposed neural moving horizon estimation (NeuroMHE), which use
arXiv:2609.13872v1 Announce Type: cross Abstract: As 6G networks transition from theoretical frameworks into operational realities, artificial intelligence (AI) evolves from an add-on optimization too
arXiv:2607.17632v2 Announce Type: replace-cross Abstract: Time series data play a pivotal role across numerous domains, including healthcare and manufacturing. In real-world environments, models must
arXiv:2609.13849v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) often struggle with complex mathematical visual reasoning primarily due to a lack of fine-grained perception, c
arXiv:2602.19202v3 Announce Type: replace Abstract: Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity
arXiv:2603.19502v2 Announce Type: replace-cross Abstract: We study unlabeled MRMP for unit-disk robots in a polygonal environment. Although the problem is hard in general, polynomial-time solutions ex
arXiv:2505.17763v2 Announce Type: replace Abstract: The widespread use of sensors in modern power grids has led to the accumulation of large amounts of voltage and current waveform data, especially du
arXiv:2609.13899v1 Announce Type: cross Abstract: The BabyLM challenge measures how much language a model can learn from developmentally-plausible, child-scale data rather than internet-scale corpora,
arXiv:2603.19896v2 Announce Type: replace Abstract: Tool-using large language model (LLM) agents often face a fundamental tension between answer quality and execution cost. Fixed workflows are stable
arXiv:2609.15964v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted for clinical question answering (QA). Current systems can attach citations to their answers, but t
arXiv:2504.06532v2 Announce Type: replace-cross Abstract: Wind direction forecasting plays a crucial role in optimizing wind energy production, but faces significant challenges due to the circular nat
arXiv:2609.15293v1 Announce Type: new Abstract: When Emergence World placed frontier LLM agents in an unsupervised multi-agent simulation, the results were alarming: agents committed crimes, starved,