Knowledge catalogue
arXiv:2603.29895v2 Announce Type: replace-cross Abstract: We present a new theory of categorization based on an information-theoretic rational analysis. To evaluate this theory, we investigate how wel
arXiv:2605.00926v1 Announce Type: new Abstract: The Receiver Operating Characteristic (ROC) curve of a binary classifier has often been utilized to measure the performance of the classifier. The area
arXiv:2605.02838v1 Announce Type: cross Abstract: Retraction-free approaches offer attractive low-cost alternatives to Riemannian methods on the Stiefel manifold, but they are often first-order, which
arXiv:2605.02525v1 Announce Type: new Abstract: Autonomous indoor mobile robots can navigate reliably to metric coordinates using established frameworks such as ROS 2 Navigation 2, yet they lack the a
arXiv:2605.01775v1 Announce Type: cross Abstract: We consider the problem of two-sample testing in a semi-supervised setting with abundant unlabeled covariate data. Standard two-sample tests neglect c
arXiv:2605.01170v1 Announce Type: cross Abstract: Reliable real-time 3D shape sensing is essential for robust control and interpretation of deformable systems during motion. Existing vision-based appr
arXiv:2605.00063v1 Announce Type: cross Abstract: Reasoning-Intensive Retrieval (RIR) targets retrieval settings where relevance is mediated by latent inferential links between a query and supporting
arXiv:2603.18066v2 Announce Type: replace-cross Abstract: Backpropagation has enabled modern deep learning but is difficult to realize as an online, fully distributed hardware learning system due to g
arXiv:2605.02270v1 Announce Type: new Abstract: This paper presents the first comprehensive comparative analysis of modern machine learning architectures for transliteration between Tajik (Cyrillic sc
arXiv:2605.01065v1 Announce Type: new Abstract: The goal of differentially private text obfuscation is to obfuscate, or 'perturb', input texts with Differential Privacy (DP) guarantees, such that the
arXiv:2605.01034v1 Announce Type: new Abstract: As large language models grow increasingly capable, concerns about their safe deployment have intensified. While numerous alignment strategies aim to re
arXiv:2605.01172v1 Announce Type: new Abstract: We present a non-asymptotic theory of generalization in deep learning where the empirical neural tangent kernel partitions the output space. In directio
arXiv:2605.01288v1 Announce Type: new Abstract: In deep networks with small initialization, training exhibits long plateaus separated by sharp feature-acquisition transitions. Whereas shallow nonlinea
arXiv:2403.11782v5 Announce Type: replace Abstract: Preference modelling lies at the intersection of economics, decision theory, machine learning and statistics. By understanding individuals' preferen
arXiv:2511.18088v2 Announce Type: replace Abstract: Tendon-driven continuum robots offer intrinsically safe and contact-rich interactions owing to their kinematic redundancy and structural compliance.
arXiv:2605.00963v1 Announce Type: new Abstract: This manuscript extends our previous multimodal human-robot interaction system by introducing a controlled ablation study of the three modules that most
arXiv:2605.00909v1 Announce Type: cross Abstract: The time-consuming formation process critically impacts the longevity of sodium-ion coin cells and End Of Life (EOL) performance. This study aims to o
arXiv:2605.02472v1 Announce Type: new Abstract: Legal texts often contain computational legal clauses--provisions whose understanding requires complex logic. While frontier Large Reasoning Models (LRM
arXiv:2411.03926v3 Announce Type: replace Abstract: Federated learning (FL) is widely used in Internet-of-Things (IoT) systems, but its distributed training process also exposes it to backdoor attacks
arXiv:2605.01657v1 Announce Type: new Abstract: Vision-Language Models (VLMs) typically rely on static initial frames for video reasoning, restricting their ability to incorporate essential dynamic in
arXiv:2510.18232v2 Announce Type: replace Abstract: Generating high-quality synthetic text under differential privacy (DP) is critical for training and evaluating language models without compromising
arXiv:2605.01477v1 Announce Type: new Abstract: We present Action Agent, a two-stage framework that unifies agentic navigation video generation with flow-constrained diffusion control for multi-embodi
arXiv:2605.01255v1 Announce Type: new Abstract: Training large language models (LLMs) is highly memory-intensive, as training must store not only weights and optimizer states but also intermediate act
arXiv:2605.02458v1 Announce Type: cross Abstract: In this work, we formulate a new multi-task active learning setting in which the learner's goal is to solve multiple matrix completion problems simult
arXiv:2605.01345v1 Announce Type: new Abstract: Visual perception in modern Vision-Language Models (VLMs) is constrained by a fundamental perceptual bandwidth bottleneck: a broad field of view inevita
arXiv:2605.02849v1 Announce Type: new Abstract: Diffusion models provide a powerful generative prior for perceptual reconstruction at ultra-low bitrates, but effective video compression requires contr
arXiv:2605.01968v1 Announce Type: new Abstract: Offline reinforcement learning (RL) can fail spectacularly when bootstrapped temporal-difference (TD) updates amplify their own errors, driving the crit
arXiv:2605.00462v1 Announce Type: cross Abstract: Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for s
arXiv:2506.08849v4 Announce Type: replace Abstract: Vision-Language Foundation Models (VLFMs) exhibit remarkable generalization, yet their direct application to medical ultrasound is severely hindered
arXiv:2605.00838v1 Announce Type: cross Abstract: In mobile telecommunications, alarms act as early warning signals. They are triggered when a cell, the basic unit of radio coverage, shuts down or beh
arXiv:2605.01907v1 Announce Type: cross Abstract: We study clustered multitask learning in a semiparametric setting where tasks share a latent cluster structure in their target parameters but exhibit
arXiv:2605.02513v1 Announce Type: new Abstract: Lower limb exoskeletons (LLEs) present the potential to make motor-impaired individuals walk again. Their application in real-world environments is stil
arXiv:2505.08392v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting trades inference speed for reasoning accuracy. Existing compressors force a compromise as static gradient technique
arXiv:2605.02742v1 Announce Type: cross Abstract: Motion in-betweening is one of the most artistically demanding and time consuming stages of 3D animation, where the expressivity and rhythm of motion
arXiv:2605.01642v1 Announce Type: new Abstract: Prevailing alignment methods target a fixed set of preferences and therefore risk forcing value lock-in as societal norms evolve over time. We introduce
arXiv:2605.01741v1 Announce Type: new Abstract: Cone Beam Computed Tomography (CBCT) is pivotal for 3D diagnostic imaging in dentistry. However, the development of robust AI models for volumetric anal
arXiv:2605.01292v1 Announce Type: new Abstract: The growing spread of misinformation in digital media highlights the need for reliable fake news detection systems, yet progress in under-resourced lang
arXiv:2602.00074v2 Announce Type: replace-cross Abstract: While large language models (LLMs) can support clinical documentation needs, standalone tools struggle with 'workflow friction' from manual da
arXiv:2605.00880v1 Announce Type: new Abstract: Autonomous driving (AD) is evolving towards end-to-end (E2E) frameworks through two primary paradigms: monolithic models exemplified by Vision-Language-
arXiv:2605.01778v1 Announce Type: new Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network a
arXiv:2605.02110v1 Announce Type: new Abstract: Federated learning (FL) is vulnerable to poisoning attacks, where malicious clients upload manipulated updates to degrade the performance of the global
arXiv:2605.00425v1 Announce Type: new Abstract: Reinforcement learning (RL) has significantly advanced the ability of large language model (LLM) agents to interact with environments and solve multi-tu
arXiv:2602.07264v2 Announce Type: replace Abstract: Unmanned aerial vehicles are rapidly transforming multiple applications, from agricultural and infrastructure monitoring to logistics and defense. I
arXiv:2605.01888v1 Announce Type: new Abstract: Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything
arXiv:2605.00276v1 Announce Type: new Abstract: Trip planning for intelligent vehicles increasingly requires selecting optimal routes rather than merely producing feasible itineraries, as interacting
arXiv:2511.21678v2 Announce Type: replace-cross Abstract: MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo -- solving each problem independently and often repeating the sam
arXiv:2605.00833v1 Announce Type: new Abstract: Agentopic is a novel agent-based workflow for explainable topic modeling that leverages the reasoning capabilities of Large Language Models (LLMs). Exis
arXiv:2605.00073v1 Announce Type: new Abstract: Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security audi
arXiv:2602.05353v3 Announce Type: replace-cross Abstract: Large Language Models have shown strong capabilities in complex problem solving, yet many agentic systems remain difficult to interpret and co
arXiv:2605.01355v1 Announce Type: new Abstract: Automated leaf disease classification is critical for early disease detection in resource-constrained field environments. Vision Transformers (ViTs) pro
arXiv:2605.00343v1 Announce Type: cross Abstract: The study examines the adoption of artificial intelligence (AI) tools in education by analyzing the roles of institutional support, teacher confidence
arXiv:2605.01643v1 Announce Type: new Abstract: We study AI alignment through the lens of law-and-economics models of deterrence and enforcement. In these models, misconduct is not treated as an exter
arXiv:2512.09169v2 Announce Type: replace-cross Abstract: We present a novel multi-stage workflow for computational materials discovery that achieves a 99% success rate in identifying compounds within
arXiv:2605.00582v1 Announce Type: cross Abstract: Expectations about the support of artificial intelligence (AI) may influence interaction outcomes similar to placebos. Such expectations may result fr
arXiv:2605.02892v1 Announce Type: new Abstract: Personalized image completion aims to restore occluded regions in personal photos while preserving identity and appearance. Existing methods either rely
arXiv:2511.21075v3 Announce Type: replace Abstract: Engineering LLMs to accelerate life sciences research requires a robust alignment with biomedical knowledge. We observe that biomedical text exhibit
arXiv:2509.09723v3 Announce Type: replace Abstract: Psychological measurement is critical to many disciplines. Despite advances in measurement, building nomological networks, theoretical maps of how c
arXiv:2605.01098v1 Announce Type: cross Abstract: Adversarial examples in machine learning are typically generated using gradients, obtained either directly through access to the model or approximated
arXiv:2605.00055v1 Announce Type: cross Abstract: We report a safety incident in a deployed multi-agent research system in which a primary AI agent installed 107 unauthorized software components, over
arXiv:2605.00860v1 Announce Type: cross Abstract: The reconstruction of ocean subsurface temperature (OST) using satellite remote sensing data holds significant scientific value for advancing the unde