Knowledge catalogue
arXiv:2606.22046v1 Announce Type: new Abstract: Tailless flapping-wing micro-aerial vehicles (FWMAVs) mimic the impressive flight performance of hummingbirds, utilising unsteady aerodynamic effects. H
arXiv:2606.20031v2 Announce Type: replace Abstract: Dynamic environmental changes, confined workspaces, and stringent real-time constraints make pathfinding in Robotic Mobile Fulfillment Systems (RMFS
arXiv:2606.21252v1 Announce Type: new Abstract: Video-based seizure detection is essential for the management of epilepsy patients, offering a non-invasive complement to electroencephalography. While
arXiv:2606.21639v1 Announce Type: new Abstract: Minimum Spanning Trees have been used in unsupervised learning, particularly in clustering tasks, due to their ability to recognize clusters by removing
arXiv:2606.23010v1 Announce Type: new Abstract: Predicting temporal Quality of Service (QoS) data is critical for optimizing network services and rationalizing resource allocation in cloud computing a
arXiv:2606.21771v1 Announce Type: new Abstract: Fish achieve efficient swimming across varied speeds through active modulation of their body flexibility. To explore the effects of tunable stiffness on
arXiv:2604.04098v2 Announce Type: replace Abstract: Precision livestock farming requires accurate and timely heat stress prediction to ensure animal welfare and optimize farm management. This study pr
arXiv:2407.07357v4 Announce Type: replace Abstract: Predicting signed interactions in biological networks is crucial for understanding drug mechanisms and facilitating drug repurposing. While deep gra
arXiv:2606.20671v1 Announce Type: new Abstract: Neural wrappers are learned pre-and postprocessing networks designed to enhance the performance of conventional video codecs. Although these approaches
arXiv:2606.23658v1 Announce Type: new Abstract: Woven structures exhibit rich mechanical behaviors including anisotropic stiffness, shear-induced locking, and crimp interchange that emerge purely from
arXiv:2606.23355v1 Announce Type: new Abstract: Dynamic feedback linearization (DFL) is a classical technique for trajectory tracking of unicycle-type mobile robots, but the resulting DFL-based contro
arXiv:2606.21350v1 Announce Type: new Abstract: This paper introduces an interpretation of Temporal Behavior Trees (TBTs) as Reward-Petri-Nets (RPNs) for reinforcement learning (RL). Designing reward
arXiv:2603.13293v2 Announce Type: replace Abstract: Accurate cardiovascular risk prediction is crucial for preventive healthcare; however, the development of robust Artificial Intelligence (AI) models
arXiv:2606.21216v1 Announce Type: new Abstract: Trained policies for real-world robotics rely on computer vision components, typically in the form of pre-trained visual encoders. These encoders are an
arXiv:2606.21511v1 Announce Type: cross Abstract: Respiratory rate is a vital indicator of pulmonary and cardiovascular health, yet conventional methods for estimating respiratory rate are often intru
arXiv:2606.21568v1 Announce Type: new Abstract: Student behavior detection is important for intelligent classroom analysis but remains challenging in large-class scenarios due to dense instance co-occ
arXiv:2606.23572v1 Announce Type: new Abstract: We develop a spectral theory for normalized corrected GNN propagation. The object of study is the symmetric normalized adjacency with its degree-station
arXiv:2606.21960v1 Announce Type: new Abstract: Laser-induced breakdown spectroscopy (LIBS) faces challenges in high-accuracy quantitative measurement under few-shot scenarios due to spectral noise an
arXiv:2507.07907v2 Announce Type: replace-cross Abstract: Learning is a complex dynamical process shaped by a range of interconnected decisions. Careful design of hyperparameter schedules for artifici
arXiv:2606.21509v1 Announce Type: new Abstract: End-to-end autonomous driving systems tightly couple perception and decision-making through latent representations. Consequently, updates to perception
arXiv:2606.22360v1 Announce Type: new Abstract: Successful conversations require speakers to align on the meaning of concepts, a challenging but crucial task for human-robot interaction. Understanding
arXiv:2606.21304v1 Announce Type: new Abstract: This paper introduces the CERTH-ITI solution for the MediaEval NewsImages 2026 challenge, which focuses on generating images related to news headlines.
Nous Research announced that their Hermes Agent has achieved a trillion tokens processed daily and reached 200,000 GitHub stars, reflecting significant adoption and performance milestones for their AI
arXiv:2606.20681v1 Announce Type: new Abstract: Slope hazards constitute a major safety threat to expressway infrastructure, and their evolution is typically manifested as slow surface deformation. Co
arXiv:2606.21220v1 Announce Type: new Abstract: Inspection of offshore wind turbine rotor blades is critical for predictive maintenance to maximise efficiency and extend operational lifetime. However,
arXiv:2606.22881v1 Announce Type: new Abstract: LiDAR (Light Detection and Ranging) sensors capture the surrounding environment as dense 3D point clouds by measuring the time-of-flight of emitted lase
arXiv:2606.21884v1 Announce Type: new Abstract: It is tempting to assume any task solvable by a short program can be taught to a model as its chain-of-thought: write the steps out, fine-tune, and the
arXiv:2606.20620v1 Announce Type: new Abstract: Starting from the axiomatic formulation of scale-space theory, we develop a viscosity-solution framework for multiscale image representations arising fr
arXiv:2606.23574v1 Announce Type: cross Abstract: Vision-language-action (VLA) models and world-action models (WAM) are the generative models now driving general-purpose robot control, turning raw cam
ABC launched an on-air campaign urging viewers to support 'The View' and eight Disney-owned ABC affiliates in its battle with the Federal Communications Commission (FCC). The FCC launched an investiga
arXiv:2606.21528v1 Announce Type: cross Abstract: We study first-order methods for solving monotone variational inequalities arising in min-max optimization. Classical approaches such as the extragrad
arXiv:2606.22112v1 Announce Type: new Abstract: The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcin
arXiv:2606.21244v1 Announce Type: new Abstract: 3D Gaussian Splatting achieves exceptional real-time rendering, but its substantial computational and storage demands hinder widespread deployment. Exis
arXiv:2606.22091v1 Announce Type: new Abstract: Per-scene 3D Gaussian Splatting (3DGS) enables high-fidelity rendering, but practical robotic and AR scene capture pipelines often depend on external ge
arXiv:2603.20819v2 Announce Type: replace Abstract: This paper studies finite-sample set-membership identification for discrete-time bilinear systems under bounded symmetric log-concave disturbances.
arXiv:2606.23662v1 Announce Type: cross Abstract: Bayesian experimental design (BED) has traditionally been based on maximising expected uncertainty reductions from prior to posterior. A major shortfa
arXiv:2503.01290v3 Announce Type: replace Abstract: Predicting post-intervention distributions from observational data is central to many scientific and decision-making problems, but remains challengi
arXiv:2602.02451v2 Announce Type: replace Abstract: Discovering causal relationships requires controlled experiments, but experimentalists face a sequential decision problem: each intervention reveals
arXiv:2606.22277v1 Announce Type: cross Abstract: We study trajectory optimization in mobile sensing systems that must identify which member of a finite candidate set is the true target, while maintai
ActiveGraph: 1 month in: 📄Paper #1: The Log is the Agent 🧠3 LongMemEval Experiments 🔄 Paper #2: Regimes, self-improvement loop 🎓 http://learn.activegraph.ai 🗂️ 2 reference agents (code, research) 💾 co
arXiv:2602.14257v2 Announce Type: replace-cross Abstract: While Large Language Model (LLM) agents have made remarkable progress on complex reasoning, evaluating them in real-world environments remains
arXiv:2606.22326v1 Announce Type: cross Abstract: Adam is one of the most widely implemented and influential modern optimizers. Why is it effective across different optimization problems in practice?
arXiv:2511.06675v2 Announce Type: replace-cross Abstract: Beside the standard stochastic gradient descent (SGD) method, the Adam optimizer due to Kingma & Ba (2014) is currently probably the best-know
arXiv:2606.21757v1 Announce Type: new Abstract: We present AdaPrivate-TS, a differentially private contextual bandit algorithm that combines Thompson Sampling with batched zCDP composition. Our key in
arXiv:2606.21713v1 Announce Type: cross Abstract: In X-ray tomography, reconstruction quality generally improves with larger numbers of projections. However, more projections increase experiment costs
arXiv:2606.23359v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide an effective way to solve partial differential equations (PDEs) by embedding physical principles into t
arXiv:2606.22462v1 Announce Type: new Abstract: Pre-trained foundation models have demonstrated remarkable success in many domains, enabling a unified backbone to generalize across diverse downstream
arXiv:2606.23079v1 Announce Type: new Abstract: Neural world models coupled with model predictive control (MPC) replan at every environment step to bound accumulated prediction error, but this incurs
arXiv:2606.19891v2 Announce Type: replace Abstract: We study adversarial bandit optimization in which the loss functions may be non-convex and non-smooth. In each round, the learner selects an action
arXiv:2606.21736v1 Announce Type: new Abstract: Single domain generalization (SDG) aims to learn a robust model, which could perform well on many unseen domains while there is only one single domain a
arXiv:2606.20880v1 Announce Type: cross Abstract: Decision-making under partial or adversarial observability requires accurate inference of the environment's latent state and its associated uncertaint
arXiv:2606.20697v1 Announce Type: new Abstract: AlphaEarth Foundations (AEF) unify global remote sensing foundation embeddings through multimodal self-supervised learning, but their pretraining focuse
Gary Marcus argues that data security is fundamentally fragile and that mass surveillance and data harvesting practices create persistent security vulnerabilities that cannot be eliminated. The post e
arXiv:2606.21013v1 Announce Type: cross Abstract: Forecasting future events is a critical challenge for large language model (LLM) agents, spanning domains from elections and monetary policy to financ
arXiv:2506.04018v3 Announce Type: replace-cross Abstract: As Large Language Model (LLM) agents become more widespread, associated misalignment risks increase. While prior research has studied agents'
arXiv:2606.21892v1 Announce Type: cross Abstract: Crop recommendation systems in precision agriculture have long suffered from a fundamental modality gap: visual soil characterization and chemical nut
arXiv:2603.20179v3 Announce Type: replace-cross Abstract: Large language model-based AI agents are now able to autonomously execute substantial portions of a high energy physics (HEP) analysis pipelin
arXiv:2503.00366v3 Announce Type: replace-cross Abstract: Thyroid scintigraphy is vital for diagnosing thyroid disorders, yet deep learning (DL) models in this domain often struggle with limited, imba
AI Capex pushback from GS: 'If frontier intelligence can increasingly be developed in the East at a fraction of the cost incurred in the West … then the largest capital allocators are also the ones mo
AI data centres are hungry for land, water & power. I’m calling on every major AI company to publicly disclose the full environmental impact of its systems – as a matter of transparency No more hidden