Knowledge catalogue
arXiv:2606.08500v1 Announce Type: cross Abstract: Software engineering agents (SWE agents) increasingly work through tool-mediated trajectories in real repositories, yet their behavior remains difficu
arXiv:2606.08186v1 Announce Type: new Abstract: Monopedal hopping robots are conceptually simple but highly dynamic and inherently unstable. Achieving robust 3D hopping is still difficult because grou
arXiv:2606.08150v1 Announce Type: new Abstract: Designing 3D metamaterial microstructures that meet the intended functions remains a major challenge, as it typically requires domain expertise, iterati
arXiv:2606.09245v1 Announce Type: cross Abstract: Few-shot object detection has gained widely attention in recent years. Some excellent algorithms have been proposed to handle this task. However, most
arXiv:2606.08015v1 Announce Type: new Abstract: We propose Q-Guided Value-Gradient Matching (Q-VGM), an off-policy reinforcement learning (RL) method that tackles a long-standing challenge in fine-tun
arXiv:2606.07606v1 Announce Type: new Abstract: Very low birth weight infants (VLBWI) are at high risk of mortality and severe neurodevelopmental impairment, including cerebral palsy, yet reliable dis
arXiv:2606.08790v1 Announce Type: new Abstract: Autonomous agents negotiate, purchase, deploy code, and move funds, but no neutral mechanism determines whether they met their delegated obligation, who
arXiv:2606.09108v1 Announce Type: cross Abstract: Many stages of the robotic lifecycle, from morphology synthesis to operation, rely fundamentally on the reachable workspace. However, current methods
arXiv:2606.08156v1 Announce Type: cross Abstract: Vision Transformers (ViTs) achieve strong performance but suffer from high computational costs due to quadratic self-attention complexity. Although to
arXiv:2606.08725v1 Announce Type: new Abstract: In teleoperation, the human operator typically controls only the end-effector pose, which often leads to self-collisions of the manipulator and collisio
arXiv:2606.07798v1 Announce Type: new Abstract: Alzheimer's disease is a progressive neurodegenerative disorder, and its progression varies substantially across patients. Existing work aims to forecas
arXiv:2606.09630v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies provide strong priors for language-conditioned manipulation, but remain brittle in off-nominal states requiring
arXiv:2509.09501v4 Announce Type: replace Abstract: Understanding region-wise correspondences between manga line art images is fundamental for high-level manga processing, supporting downstream tasks
arXiv:2606.08104v1 Announce Type: new Abstract: Soft-bodied organisms such as octopuses and elephant trunks exhibit remarkable morphological adaptability, dynamically reconfiguring body shape and stif
arXiv:2606.08020v1 Announce Type: cross Abstract: Hard-constraint decision systems usually veto infeasible candidates. This is too rigid when the system can act: if a known affordable repair would mak
arXiv:2606.09200v1 Announce Type: cross Abstract: The rapid growth of large-scale machine learning (ML) has made distributed training across multiple GPUs a fundamental component of modern ML systems.
arXiv:2606.08103v1 Announce Type: cross Abstract: We are surrounded by various objects with movable, articulated parts, e.g., box, handle, door. An accurate and generalizable perception of articulated
arXiv:2606.08296v1 Announce Type: new Abstract: A key premise in leading arguments for existential risk from artificial intelligence is that malfunctioning artificial agents could not be easily shut d
arXiv:2606.08765v1 Announce Type: cross Abstract: Effective visuo-tactile integration is critical for robotic dexterous manipulation, especially when visual observations are unreliable or occluded. Ho
arXiv:2506.06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al., 20
arXiv:2505.07573v2 Announce Type: replace-cross Abstract: Renal mass segmentation has important potential to enhance the clinical workflow, especially in settings requiring quantitative assessments. K
arXiv:2511.05355v3 Announce Type: replace Abstract: Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action
arXiv:2606.08741v1 Announce Type: new Abstract: Robots operating in human environments must not only ensure physical safety but also exhibit behaviors that are understandable, fluent, and acceptable t
arXiv:2606.09719v1 Announce Type: new Abstract: Autonomous mobile robots operating in tight environments require motion planning frameworks that account for the physical footprint of the robot. Simpli
arXiv:2511.18493v4 Announce Type: replace-cross Abstract: The significant variability in cell size and shape continues to pose a major obstacle in computer-assisted cancer detection on gigapixel Whole
arXiv:2606.09377v1 Announce Type: cross Abstract: Formal neural network verification -- proving that a network satisfies safety properties for all inputs in a specified domain -- is bounded in practic
arXiv:2606.08234v1 Announce Type: new Abstract: LLM-based scientific agents have shown strong capacity for autonomous research, yet their safety layers remain structurally divorced from core reasoning
arXiv:2606.09262v1 Announce Type: new Abstract: Two-view correspondence learning aims to distinguish true correspondences (inliers) from false ones (outliers) in image pairs by leveraging their underl
arXiv:2606.08405v1 Announce Type: new Abstract: While data-intensive deep reinforcement learning can optimize complex control policies, scientific discovery in physical systems fundamentally requires
arXiv:2606.09236v1 Announce Type: cross Abstract: Autonomous Racing has seen remarkable progress through deep Reinforcement Learning (RL), primarily for four-wheeled vehicles. However, motorbikes intr
arXiv:2512.00239v2 Announce Type: replace Abstract: The effectiveness of self-supervised learning (SSL) for physiological time series depends on the ability of a pretraining objective to preserve info
arXiv:2602.05845v2 Announce Type: replace Abstract: We propose a multi-task formulation of self-predictive Siamese SSL in which each spatial transformation defines a distinct latent-space alignment ta
arXiv:2606.08364v1 Announce Type: cross Abstract: Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative condition whose osseous changes are often subtle on cone-beam CT (CBCT), m
arXiv:2606.08324v1 Announce Type: cross Abstract: Passive long-wave infrared (LWIR) hyperspectral imaging under a standoff geometry depends on atmospheric absorption and emission, as well as reflected
arXiv:2606.08854v1 Announce Type: cross Abstract: Standard Reinforcement Learning with Verifiable Rewards (RLVR) training allocates a fixed rollout budget to every query, without regard for what each
arXiv:2606.07716v1 Announce Type: cross Abstract: Adversarial attacks pose a serious and growing threat to Machine Learning (ML)-based Intrusion Detection Systems (IDS), where imperceptible perturbati
arXiv:2606.07596v1 Announce Type: new Abstract: Fine-tuning often introduces spurious correlations alongside task knowledge, causing systematic failures on underrepresented groups. Existing mitigation
arXiv:2511.14143v2 Announce Type: replace-cross Abstract: Video Moment Retrieval is a task in video understanding that aims to localize a specific temporal segment in an untrimmed video based on a nat
arXiv:2510.22450v3 Announce Type: replace-cross Abstract: The choice of activation function plays a critical role in neural networks, yet most architectures still rely on fixed, uniform activation fun
arXiv:2606.08712v1 Announce Type: cross Abstract: Purpose: Spatial transcriptomics (ST) enables gene expression measurements within the tissue context. However, these measurements are often noisy, low
arXiv:2606.09679v1 Announce Type: new Abstract: We describe our system for the SoccerNet 2026 Player-Centric Ball-Action Spotting Challenge, which requires predicting who performs which action and whe
arXiv:2606.08992v1 Announce Type: cross Abstract: Vision-and-Language Navigation in continuous environments requires agents to understand the spatial structure of previously unseen environments in ord
arXiv:2405.17823v5 Announce Type: replace-cross Abstract: A central question in vector- and function-valued learning is how to design kernels that capture both local and non-local interactions while r
arXiv:2606.07557v1 Announce Type: new Abstract: Decentralized multi-agent swarm coordination on resource-constrained edge platforms remains fundamentally bottlenecked by the exponential scaling of joi
arXiv:2406.19749v2 Announce Type: replace-cross Abstract: Automatic vessel segmentation plays a pivotal role in the development of next-generation interventional navigation systems for surgical roboti
arXiv:2606.07565v1 Announce Type: new Abstract: Intelligent scaling of microservices in cloud platforms is crucial for mitigating escalating compute costs while avoiding service disruptions. Current s
arXiv:2606.08710v1 Announce Type: cross Abstract: Modernization of legacy scientific codes is often necessary to keep up with the ever-evolving changes in the compute resource ecosystem. Parallelizati
arXiv:2606.08154v1 Announce Type: new Abstract: In-context imitation learning (ICIL) enables robots to learn new tasks from a small number of demonstrations by conditioning a pre-trained policy on tas
arXiv:2606.08738v1 Announce Type: cross Abstract: Urban last-mile parcel delivery increasingly relies on heterogeneous fleets whose performance depends on timely coordination, reliable communication,
arXiv:2606.07950v1 Announce Type: new Abstract: RL with verifiable rewards can substantially improve LLM reasoning, yet standard GRPO-style training often treats easy, hard, and learnable questions al
arXiv:2606.07675v1 Announce Type: cross Abstract: Smartphone telephoto cameras are approaching a 'telephoto physics wall': as pixel pitches shrink toward sub-0.5 micron, the optics remain limited by g
arXiv:2606.08388v1 Announce Type: new Abstract: Muon replaces a matrix gradient G=USigma V^op by its polar factor UV^op. This keeps the singular directions selected by the gradient, but makes the upda
arXiv:2606.08122v1 Announce Type: new Abstract: Predicting a user's next Point-of-Interest (POI) based on their historical check-in records is a fundamental task in location-based services. While rece
arXiv:2606.07688v1 Announce Type: cross Abstract: Generative recommendation formulates next-item prediction as autoregressive generation over semantic ID (SID) sequences derived from users' historical
arXiv:2602.20967v2 Announce Type: replace-cross Abstract: Automatic speech recognition (ASR) degrades severely in noisy environments. Although speech enhancement (SE) front-ends effectively suppress b
arXiv:2606.09188v1 Announce Type: cross Abstract: Bearing-only target localization is a fundamental problem in optical measurement and finds extensive applications in unmanned aerial vehicle (UAV) tec
arXiv:2606.08256v1 Announce Type: new Abstract: Verifiability, attribution, and reproducibility are foundational requirements of scientific knowledge, yet current publishing infrastructure does not en
arXiv:2606.09030v1 Announce Type: cross Abstract: Clinical early warning systems built on electronic health records, in which clinical observations are recorded as irregularly sampled medical time ser
arXiv:2606.08140v1 Announce Type: new Abstract: Supply Chain Finance (SCF) and LendTech platforms need credit scoring systems that respond to evolving transaction behavior, repayment delays, and activ
arXiv:2606.09227v1 Announce Type: cross Abstract: The convergence of the 2026 European Union Safe and Sustainable by Design (SSbD) framework, Corporate Sustainability Due Diligence Directive (CSDDD),