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Safety

Continual Humanoid Motion Learning

DGX agent

arXiv:2610.04231v1 Announce Type: new Abstract: Humanoid whole-body controllers can now track a diverse set of dynamic motions, but they are typically trained offline and then frozen, so teaching such

safetyarxiv-cs-ro

6 Oct 2026

Safety

Contrastive Time Series Forecasting with Anomalies

DGX agent

arXiv:2512.11526v2 Announce Type: replace Abstract: Time series forecasting predicts future values from past data. In real-world settings, some anomalous events have lasting effects and influence the

All entries

Continual Humanoid Motion Learning

Contrastive Time Series Forecasting with Anomalies

Control How Your GPU Shares Work with Green Contexts

Controllable and Photorealistic Pedestrian Risky Motion Generation for End-to-End Driving Safety Evaluation

Controllable Road Marking Generation

Convergence of Statistical Estimators via Mutual Information Bounds

Cooperative Sheaf Neural Networks

CoreWeave targets GPU utilization in continuous AI post-training

Correct Verdicts, Flawed Reasoning: Structured Auditing of LLM-based Vulnerability Reasoning

COSMOS: Soft Mechanism Mixtures with Verifiable Routing for Long-Horizon PDE Forecasting

Coupling Noisy Pairwise Knowledge to the DAG Posterior for Causal Discovery

COVER: Learning to Accept More in Selective Sleep Staging

Critical Points of Degenerate Metrics on Algebraic Varieties: A Tale of Overparametrization

Cross-dataset harmonization for robust endoscopic image analysis

Cross-Modal Contrastive Learning for the Retrieval of Immunotherapy-Associated Molecular Signatures from Histopathology

Cross-Modal Solar Image Synthesis: Adapting the Surya Foundation Model from He I 10830 {AA} to EUV Translation and Coronal Hole Segmentation

Cross-Time Directional Selection in Diffusion Sampling

Cross-Trait Transfer in Subliminal Learning

CT-Miner: Fast and Coarse-Grained Time-Series Pattern Mining via Cartesian Trees

CURIO: Curiosity-Driven Test-Time Learning for Open-Ended Discovery

CurveCodec 2: Skeleton-agnostic animation compression with a learned entropy model

Cut Binary Cross Entropy: Efficient Large-Vocabulary Loss and Gradient Kernels for Sequential Recommendation

CyTReX: Explainable AI-Based Cybersecurity Threat Reasoning Framework for DER Networks

D-DOIT: Training-free Adaptation of Discrete Diffusion via Doob's h-Transform

DABACO: A Multi-Camera Dataset and Benchmark for Screen Localization and Pointing Estimation

DASH: A da Vinci Adapter for Serial-link and Humanoid Robots as an Accessible Platform for Surgical Robotics Research

DASH: Fast, Valid Counterfactuals for Deep Networks via Batched Directional Search

Dataset-Free Compliant Humanoid Loco-Manipulation with Dynamic Online Posture

Day-0 support for EmbeddingGemma 2 in llama.cpp https://huggingface.co/ggml-org/embeddinggemma-2-GGUF

De-occluding broadband metalens

decision models + local ai = ❤️ tried Laya (421M) on llama.cpp in a little apple-picking benchmark, it's almost as good as Qwen 4B at 12x th…

Decouple, Purify and Unite: Semantic-Structural Prototype Learning for Federated Medical Segmentation

Decoupling Time and Space: A Temporally Conditioned Refinement for EEG Source Imaging

Deep Fair Learning: Task-Aware Fair Representations via Joint Distance-Covariance Regularization

Deep Learning Denoising of Real SWOT Sea Surface Height Observations

Deep Learning for Sleep Heart Rate Estimation from Accelerometers: Toward Population-Scale Cardiac Insight Without Optical Sensors

Deep Learning Reforms Image Matching: A Survey and Outlook

Deep Prior Learning for Embodied Perception

Deepseek Peak/Off-Peak and Ownership

DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management

DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts

Delay-coordinate reconstruction and conditional-moment causal diagnostics in stochastic systems

DelegationBench: Measuring When AI Agents Should Ask Before Acting

Dell’s AI Data Platform gets a knowledge graph for agents and faster Nvidia processing

Demonstration-Calibrated Port-Hamiltonian Retuning for Manipulation Policies

Demystifying Hybrid Thinking: Can LLMs Truly Switch Between Think and No-Think?

DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection

Dependable AI-Assisted Engineering: A Formal Framework for AI Participation and Assurance in Safety-Critical Workflows