Knowledge catalogue
arXiv:2603.21393v2 Announce Type: replace Abstract: The widespread use of AI and ML models in sensitive areas raises significant concerns about fairness. While the research community has introduced va
arXiv:2607.13354v1 Announce Type: new Abstract: Autonomous racing demands planning algorithms that balance vehicle dynamics at the limits of handling with strategic decision-making in competitive mult
arXiv:2607.13178v1 Announce Type: new Abstract: Automated visual inspection of steel surface defects is a recurring quality control task in which labeled defect data is scarce and costly to obtain, wh
arXiv:2607.13319v1 Announce Type: cross Abstract: High-speed off-road autonomy requires precise closed-loop control for a target vehicle while remaining robust across changing terrains. Recent forward
arXiv:2510.15824v2 Announce Type: replace-cross Abstract: This article considers an online version of conformal inference, called adaptive conformal inference [ACI] and introduced by Gibbs and Candes
arXiv:2607.13453v1 Announce Type: cross Abstract: Artificial Intelligence (AI), especially Generative AI (GenAI), adoption has increased in industries significantly in recent years. However, the use o
arXiv:2607.11707v2 Announce Type: replace-cross Abstract: Following the rapid progress of generative Artificial Intelligence, there is a growing threat posed by conversational scams. These scams often
arXiv:2607.13738v1 Announce Type: cross Abstract: Background and Objective: Deep video models estimate left-ventricular ejection fraction (EF) from echocardiography with near-expert accuracy, and post
arXiv:2607.13696v1 Announce Type: new Abstract: Robots operating in human-robot collaboration must communicate not only their intended actions but also uncertainty arising from incomplete or ambiguous
arXiv:2607.13043v1 Announce Type: cross Abstract: Deep learning models achieve state-of-the-art image classification but face deployment challenges due to computational costs and energy demands. We pr
arXiv:2607.10188v2 Announce Type: replace Abstract: Breast cancer remains the most commonly diagnosed malignancy among women worldwide, yet accurate detection and characterization of breast masses in
arXiv:2607.13125v1 Announce Type: cross Abstract: We introduce Boogu-Image-0.1, an open-source unified multimodal understanding and generation model family, comprising Base, Turbo, Edit, and Edit-Turb
arXiv:2607.13508v1 Announce Type: new Abstract: Quantifying directional influence between node populations is a fundamental problem in graph-based modeling, particularly in spatial biological systems
arXiv:2607.13437v1 Announce Type: new Abstract: Recent vision models such as CLIP and SAM enable training-free segmentation and semantic encoding for fine-grained classification. A common approach is
arXiv:2607.13120v1 Announce Type: cross Abstract: Inferring gene regulatory networks (GRNs) from single-cell transcriptomic data is crucial for biological discovery, yet existing approaches suffer fro
arXiv:2607.13524v1 Announce Type: new Abstract: Active 3D reconstruction requires selecting informative viewpoints under limited sensing budgets. In multi-agent settings, coordination inefficiencies s
arXiv:2607.13071v1 Announce Type: cross Abstract: Agentic LLM coding tools compress long session histories into compaction summaries that subsequent sessions inherit as ground truth. This paper docume
arXiv:2607.13188v1 Announce Type: new Abstract: Human cognition does not separate understanding and generation. A teacher at a whiteboard speaks and draws extit{together}, each modality reshapes the o
arXiv:2607.13475v1 Announce Type: cross Abstract: Surgical tissue retraction requires effective manipulation planning under partial and noisy perception. We study state estimation for deformable tissu
arXiv:2607.13431v1 Announce Type: cross Abstract: Discrete denoising diffusion models (DDMs) have recently emerged as a compelling alternative to autoregressive (AR) modeling for discrete data, offeri
arXiv:2607.13449v1 Announce Type: new Abstract: 6-DoF pose estimation is a critical task in autonomous rendezvous and proximity operations. In the case of an unknown target, this task becomes challeng
arXiv:2607.13515v1 Announce Type: new Abstract: The continuous growth in cross-border mobility places increasing pressure on existing border control infrastructures, motivating on-the-move biometric a
arXiv:2607.13093v1 Announce Type: cross Abstract: On-device LLM inference faces a trilemma of response latency, limited hardware resources and user privacy. Full cloud inference delivers strong comput
arXiv:2607.13330v1 Announce Type: cross Abstract: Diffusion-based text-to-audio generative models such as AudioLDM achieve high perceptual quality and strong semantic consistency; however, their pract
arXiv:2607.13472v1 Announce Type: cross Abstract: Deploying humanoid robots in unstructured terrain remains an open problem. While classic reinforcement learning struggles with the sheer complexity of
arXiv:2405.17366v3 Announce Type: replace Abstract: We present a novel machine-learning (ML) approach (EM-GANSim) for real-time electromagnetic (EM) propagation that is used for wireless communication
arXiv:2607.13469v1 Announce Type: cross Abstract: The banking sector increasingly relies on automated systems to monitor electronic transactions for signs of fraud, yet conventional rule-based approac
arXiv:2607.13655v1 Announce Type: new Abstract: Explainable Reinforcement Learning (XRL) seeks to make Reinforcement Learning (RL) policies more transparent and interpretable, a key requirement in saf
arXiv:2607.13303v1 Announce Type: cross Abstract: Formal contracts are essential for software testing and verification, yet writing them remains labor-intensive and error-prone. LLMs offer a promising
arXiv:2603.19063v2 Announce Type: replace Abstract: Most existing robot simulators prioritize rigid-body dynamics and photorealistic rendering, but largely neglect the thermally and optically complex
arXiv:2607.13035v1 Announce Type: cross Abstract: Cloud services experience frequent incidents that require rapid diagnosis and resolution. Troubleshooting guides help engineers respond consistently,
arXiv:2607.13553v1 Announce Type: cross Abstract: Autonomous robotic navigation in nonstationary time-varying fluid flows remains a fundamental challenge due to partial observability and the unpredict
arXiv:2607.13656v1 Announce Type: new Abstract: Image-based indoor scene relighting remains challenging due to the complex interplay between cluttered geometry and local illumination, requiring precis
arXiv:2607.13624v1 Announce Type: cross Abstract: Natural language interaction provides an intuitive way for non-expert users to communicate with robotic platforms. However, transforming user requests
arXiv:2607.13921v1 Announce Type: cross Abstract: Languages with rich static semantics, such as Rust, provide stronger guarantees for AI-generated code, but their strictness makes generation more diff
arXiv:2607.13394v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) offer a promising alternative to reward-maximizing reinforcement learning (RL) for large reasoning models, encour
arXiv:2607.13569v1 Announce Type: cross Abstract: Transit video understanding can provide valuable fine-grained data that conventional passenger counters and fare systems cannot capture. However, supe
arXiv:2603.12361v2 Announce Type: replace Abstract: Motion planning through narrow passages remains a core challenge: sampling-based planners rarely place samples inside these narrow but critical regi
arXiv:2607.13059v1 Announce Type: new Abstract: Data-driven embodied AI is rapidly transitioning into a paradigm that scales training through massively parallel simulation, where GPU-accelerated simul
arXiv:2607.13115v1 Announce Type: new Abstract: Small language models (SLMs) have shown promise for zero-shot molecular property prediction from SMILES strings, yet they often suffer from structural b
arXiv:2607.14024v1 Announce Type: cross Abstract: With rising global energy demand and growing awareness of climate change and its impacts, the share of renewable energies in the global energy mix con
arXiv:2607.14021v1 Announce Type: new Abstract: Dexterous manipulation remains a critical bottleneck in industrial automation; tasks such as cable routing, connector insertion, and precision assembly
arXiv:2510.10002v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in sensitive everyday contexts -- offering personal advice, mental health support, and mor
arXiv:2607.13413v1 Announce Type: cross Abstract: This study presents an empirical benchmarking comparison between Kolmogorov-Arnold Networks (KANs) and Multi-Layer Perceptrons (MLPs) on structured ta
arXiv:2607.13245v1 Announce Type: new Abstract: While 3D Scene Graphs (3DSGs) provide crucial structured representations for embodied agents, conventional Ahead-of-Time, build-everything-then-filter p
arXiv:2607.13770v1 Announce Type: cross Abstract: Video diffusion transformers (vDiTs) generate high quality video but introduce extremely high compute cost due to the long diffusion timesteps and sel
arXiv:2607.13522v1 Announce Type: cross Abstract: A robot must understand the state of its own body, but a camera sees only part of it. Force and contact leave almost no trace in a single frame, and r
arXiv:2607.13501v1 Announce Type: new Abstract: Reinforcement learning for multi-turn search reasoning typically relies on terminal outcome rewards, which cannot distinguish useful, redundant, and har
arXiv:2607.13497v1 Announce Type: new Abstract: In expeditionary medical facilities, routine patient transport imposes a compounding burden of personal protective equipment consumption, staff diversio
arXiv:2607.13818v1 Announce Type: new Abstract: Robotic manipulation poses fundamental challenges due to uncertainty, long-horizon execution, and compounding errors, which can easily destabilize execu
arXiv:2604.00830v3 Announce Type: replace-cross Abstract: Test-Time Learning (TTL) enables language agents to iteratively refine their performance through repeated interactions with the environment at
arXiv:2601.20496v2 Announce Type: replace-cross Abstract: Generating dense physical fields from sparse measurements is a fundamental question in sampling, signal processing, and many other application
arXiv:2607.14086v1 Announce Type: new Abstract: Robust and accurate neural decoders are integral to neurotechnologies such as brain-computer interfaces and closed-loop experiments. Recent work has sho
arXiv:2607.14081v1 Announce Type: new Abstract: Linear Independent Component Analysis (ICA) recovers jointly independent source signals from their linear mixtures. To achieve this, classical ICA algor
arXiv:2607.13499v1 Announce Type: new Abstract: 3D anomaly detection has recently emerged as an important research topic in computer vision. Although existing methods have achieved high performance, e
arXiv:2510.24803v3 Announce Type: replace-cross Abstract: Inference-time search over multi-agent systems (MAS) wastes compute when it cannot identify which agent's intermediate message advanced progre
arXiv:2607.14005v1 Announce Type: new Abstract: Driving-world generation has emerged as a core capability for scalable autonomous-driving simulation, yet existing methods remain limited in object-leve
arXiv:2601.12349v3 Announce Type: replace-cross Abstract: Large multimodal model powered GUI agents are emerging as high-privilege operators on mobile platforms, entrusted to perceive screen content a
arXiv:2607.14041v1 Announce Type: cross Abstract: Historical Manchu OCR must accommodate various visually distinct writing styles, including regular script, running script, and the semi-cursive chance
arXiv:2607.13984v1 Announce Type: cross Abstract: Longitudinal tumor measurements, dropout information, and genetic covariates provide complementary information about treatment response, but integrati