Search: “models”

From Ontology Conformance to Admissible Reconfiguration: A RoSO/SMGI Adequacy Argument for Robotic Service Governance

arXiv:2605.08185v1 Announce Type: cross Abstract: The Robotic Service Ontology (RoSO) gives service robotics a typed semantic vocabulary for services, functions, interactions, and deployment-sensitive

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From Regression to Inference: Meta-Learning Predictors for Neural Architecture Search

DGX agent

arXiv:2605.09290v1 Announce Type: new Abstract: Prediction-based approaches are widely used in neural architecture search (NAS), where a predictor estimates the performance of candidate architectures

tutorialsarxiv-cs-lg

12 May 2026

From Single-Step Edit Response to Multi-Step Molecular Optimization

arXiv:2605.10035v1 Announce Type: new Abstract: Conditional molecular optimization aims to edit a molecule to realize a specified property shift. In practice, structurally similar molecule data is sca

local-aiarxiv-cs-ai

GLEAM: A Multimodal Imaging Dataset and HAMM for Glaucoma Classification

arXiv:2603.12800v2 Announce Type: replace-cross Abstract: We propose glaucoma lesion evaluation and analysis with multimodal imaging (GLEAM), the first publicly available tri-modal glaucoma dataset co

GridProbe: Posterior-Probing for Adaptive Test-Time Compute in Long-Video VLMs

arXiv:2605.10762v1 Announce Type: cross Abstract: Long-video understanding in VLMs is bottlenecked by a single monolithic forward pass over thousands of frames at quadratic attention cost. A common mi

GSMap: 2D Gaussians for Online HD Mapping

arXiv:2605.09619v1 Announce Type: new Abstract: Accurate High-Definition (HD) map construction is critical for autonomous driving, yet existing methods face a fundamental trade-off: vectorization-base

agentsarxiv-cs-cv

Hierarchical Attention-based Graph Neural Network with Relevance-driven Pruning

arXiv:2605.09308v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) excel at relational reasoning but face two persistent challenges: the lack of interpretable attribution for heterogeneous

Hierarchical Prompting with Dual LLM Modules for Robotic Task and Motion Planning

arXiv:2605.08330v1 Announce Type: new Abstract: We present a hierarchical language-driven framework for robotic task and motion planning to improve natural, intuitive human-robot interaction in servic

agentsarxiv-cs-ro

HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection

arXiv:2602.09524v3 Announce Type: replace Abstract: Unsupervised industrial anomaly detection (UAD) is essential for modern manufacturing inspection, where defect samples are scarce and reliable detec

safetyarxiv-cs-cv

IMPACT: An Implicit Active-Set Augmented Lagrangian for Fast Contact-Implicit Trajectory Optimization

arXiv:2605.09127v1 Announce Type: new Abstract: Contact-implicit trajectory optimization (CITO) has attracted growing attention as a unified framework for planning and control in contact-rich robotic

researcharxiv-cs-ro

Applications

Information Filtering via Variational Regularization for Robot Manipulation

arXiv:2601.21926v4 Announce Type: replace Abstract: Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However,

applicationsarxiv-cs-ro

Insight: Enhancing Mobile Accessibility for Blind and Visually Impaired Users with LLMs

arXiv:2605.09803v1 Announce Type: cross Abstract: This research paper addresses the limitations of current mobile accessibility services like TalkBack, which provide manual gesture-based sequential fe

Instruction Anchor: Dissecting the Mechanistic Dynamics of Modality Arbitration

arXiv:2602.03677v2 Announce Type: replace Abstract: Modality following is the ability to selectively leverage multimodal contexts based on user instructions. It is fundamental to the safety and reliab

safetyarxiv-cs-cl

Intelligent Autonomous Orchestration for Distributed Cloud Resources using Complex-Stability Analysis

arXiv:2605.08139v1 Announce Type: cross Abstract: In modern distributed cloud environments, efficient resource allocation is required as traditional scaling mechanisms are often subject to cloud thras

Interpretable Coreference Resolution Evaluation Using Explicit Semantics

arXiv:2605.10627v1 Announce Type: cross Abstract: Coreference resolution is typically evaluated using aggregate statistical metrics such as CoNLL-F1, which measure structural overlap between predicted

It's All Connected: Topology-Aware Structural Graph Encoding Improves Performance on Polymer Prediction

arXiv:2605.10551v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have achieved strong results in molecular property prediction, but polymers present distinct challenges: labeled datasets a

Key-Value Means

arXiv:2605.09877v1 Announce Type: cross Abstract: We present Key-Value Means ('KVM'), a novel block-recurrence for attention that can accommodate either fixed-size or growing state. Equipping a strong

Applications

Kinematics-Driven Gaussian Shape Deformation for Blurry Monocular Dynamic Scenes

arXiv:2605.08635v1 Announce Type: new Abstract: Reconstructing dynamic 3D scenes from blurry monocular videos is challenging as motion-induced blur entangles object motion and geometry, hindering geom

applicationsarxiv-cs-cv

Kintsugi: Learning Policies by Repairing Executable Knowledge Bases

arXiv:2605.09487v1 Announce Type: new Abstract: Modern embodied agents achieve impressive performance, but their task knowledge is often stored in neural weights, latent state, or prompt-bound memory,

local-aiarxiv-cs-lg

LASSA Architecture-Based Autonomous Fault-Tolerant Control of Unmanned Underwater Vehicles

arXiv:2605.09494v1 Announce Type: cross Abstract: Unmanned underwater vehicles (UUVs) operate persistently in communication-constrained environments, thus requiring high-level autonomous fault-toleran

agentsarxiv-cs-ai

LCGNav: Local Candidate-Aware Geometric Enhancement for General Topological Planning in Vision-Language Navigation

arXiv:2605.09053v1 Announce Type: new Abstract: Online topological planning has become an effective paradigm for Vision-Language Navigation in Continuous Environments (VLN-CE), but existing methods st

agentsarxiv-cs-cv

Learning from Acceptance: Cumulative Regret in the Game of Coding

arXiv:2605.09754v1 Announce Type: cross Abstract: Classical coding-theoretic guarantees often rely on trust assumptions, such as requiring sufficiently many honest nodes compared with adversarial ones

tutorialsarxiv-cs-lg

Learning Point Cloud Geometry as a Statistical Manifold: Theory and Practice

arXiv:2605.10456v1 Announce Type: new Abstract: Point clouds are a fundamental representation for robotic perception tasks such as localization, mapping, and object pose estimation. However, LiDAR-acq

local-aiarxiv-cs-ro

Learning Pure Quantum States in Any Dimension (Almost) Without Regret

arXiv:2605.09019v1 Announce Type: cross Abstract: We extend quantum state tomography with minimal cumulative disturbance, first investigated in [arXiv:2406.18370], to arbitrary finite-dimensional pure

tutorialsarxiv-cs-lg

Learning the Channel Gain from Anywhere to Anywhere via Cross-environment Transformer Estimators

arXiv:2605.08211v1 Announce Type: cross Abstract: Channel-gain maps provide the channel gain between any two locations in a geographical region. They find numerous applications, from resource allocati

agentsarxiv-cs-lg

Learning the Preferences of a Learning Agent

arXiv:2605.09217v1 Announce Type: new Abstract: For AI systems to be useful to humans, they must understand and act in accordance with our values and preferences. Since specifying preferences is a har

Learning to Bid with Unknown Private Values in Budget-Constrained First-Price Auctions

arXiv:2605.09448v1 Announce Type: new Abstract: The transition to First-Price Auctions (FPA) in digital advertising has spurred significant research, yet existing work typically assumes access to a va

Learning to Compress Time-to-Control: A Reinforcement Learning Framework for Chronic Disease Management

arXiv:2605.09818v1 Announce Type: new Abstract: Reinforcement learning (RL) in healthcare has had mixed results, with reward sparsity, unreliable off-policy evaluation, and deployment-simulation gap a

safetyarxiv-cs-lg

Learning Unified Representations of Normalcy for Time Series Anomaly Detection

arXiv:2605.09685v1 Announce Type: cross Abstract: The core challenge in unsupervised anomaly detection is identifying abnormal patterns without prior knowledge of their characteristics. While existing

tutorialsarxiv-cs-ai

Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift

arXiv:2605.09183v1 Announce Type: new Abstract: Behavior cloning provides strong imitation learning guarantees when training and test environments share the same dynamics. However, in many deployment

safetyarxiv-cs-lg

Less is More: Towards Simple Graph Contrastive Learning

arXiv:2509.25742v4 Announce Type: replace Abstract: Graph Contrastive Learning (GCL) has shown strong promise for unsupervised graph representation learning, yet its effectiveness on heterophilic grap

LLM-Driven Performance-Space Augmentation for Meta-Learning-Based Algorithm Selection

arXiv:2605.09518v1 Announce Type: new Abstract: Meta-learning for algorithm selection relies on a meta-dataset in which each row corresponds to a supervised learning dataset described by meta-features

safetyarxiv-cs-lg

MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation

arXiv:2502.13451v5 Announce Type: replace Abstract: Vision-and-language navigation (VLN) is a key task in Embodied AI, requiring agents to navigate diverse and unseen environments while following natu

agentsarxiv-cs-ro

Applications

MARGIN: Margin-Aware Regularized Geometry for Imbalanced Vulnerability Detection

arXiv:2605.10240v1 Announce Type: cross Abstract: Software vulnerability detection is critical for ensuring software security and reliability. Despite recent advances in deep learning, real-world vuln

applicationsarxiv-cs-lg

Markerless Head Tracking for Accurate and Accessible Neuronavigation

arXiv:2602.07052v2 Announce Type: replace Abstract: Neuronavigation is widely used in biomedical research and interventions to guide the precise placement of instruments around the head to support pro

tutorialsarxiv-cs-cv

Mazocarta: A Seeded Procedural Deckbuilder for Instrumented Game Development

arXiv:2605.08319v1 Announce Type: cross Abstract: Mazocarta is a seeded procedural tactical deckbuilder implemented in Rust, compiled to WebAssembly for browser play, and executable natively for simul

local-aiarxiv-cs-ai

Measuring and Decomposing Mode Separation via the Canonical Diffusion

arXiv:2605.08777v1 Announce Type: cross Abstract: Mode separation, namely how sharply a distribution fragments into barrier-separated clusters, is a fundamental geometric property of densities, diffic

Mechanism Design Is Not Enough: Prosocial Agents for Cooperative AI

arXiv:2605.08426v1 Announce Type: cross Abstract: Ensuring that AI agents behave safely and beneficially when interacting with other parties has emerged as one of the central challenges of modern AI s

MePo: Meta Post-Refinement for Rehearsal-Free General Continual Learning

arXiv:2602.07940v3 Announce Type: replace Abstract: To cope with uncertain changes of the external world, intelligent systems must continually learn from complex, evolving environments and respond in

MicroViTv2: Beyond the FLOPS for Edge Energy-Friendly Vision Transformers

arXiv:2605.10148v1 Announce Type: new Abstract: The Vision Transformer (ViT) achieves remarkable accuracy across visual tasks but remains computationally expensive for edge deployment. This paper pres

MineEvolve: Self-Evolution with Accumulated Knowledge for Long-Horizon Embodied Minecraft Agents

arXiv:2603.13131v3 Announce Type: replace Abstract: Long-horizon embodied intelligence requires agents to improve through interaction, not merely to execute plans generated from static goals. A centra

MultiAnimate: Pose-Guided Image Animation Made Extensible

arXiv:2602.21581v2 Announce Type: replace Abstract: Pose-guided human image animation aims to synthesize realistic videos of a reference character driven by a sequence of poses. While diffusion-based

Multimodal Emotion Recognition via Causal-Diffusion Bridge (Affect-Diff)

arXiv:2605.08252v1 Announce Type: new Abstract: Multimodal emotion recognition on CMU-MOSEI faces an extreme imbalance as Happy accounts for 65.9% of samples while three Ekman categories collectively

MuonEq: Balancing Before Orthogonalization with Lightweight Equilibration

arXiv:2603.28254v2 Announce Type: replace Abstract: Orthogonalized-update optimizers such as Muon improve training of matrix-valued parameters, but existing extensions typically either rescale updates

MVB-Grasp: Minimum-Volume-Box Filtering of Diffusion-based Grasps for Frontal Manipulation

arXiv:2605.09672v1 Announce Type: new Abstract: State-of-the-art 6-DoF grasp generators excel on tabletop benchmarks with overhead cameras but struggle in frontal grasping scenarios on low-cost manipu

safetyarxiv-cs-ro

NaiAD: Initiate Data-Driven Research for LLM Advertising

arXiv:2605.09918v1 Announce Type: cross Abstract: Reconciling platform revenue with user experience in LLM advertising motivates a data-centric foundation. We introduce NaiAD, the first comprehensive

NEO: No-Optimization Test-Time Adaptation through Latent Re-Centering

arXiv:2510.05635v2 Announce Type: replace-cross Abstract: Test-Time Adaptation (TTA) methods are often computationally expensive, require a large amount of data for effective adaptation, or are brittl

safetyarxiv-cs-cv

Neural at ArchEHR-QA 2026: One Method Fits All: Unified Prompt Optimization for Clinical QA over EHRs

arXiv:2605.10877v1 Announce Type: new Abstract: Automated question answering (QA) over electronic health records (EHRs) demands precise evidence retrieval, faithful answer generation, and explicit gro

safetyarxiv-cs-cl