Search: “safety”

GIFT: Goal-Injected Fine-Tuning for Efficient Manipulation Policy Adaptation

arXiv:2609.07006v1 Announce Type: new Abstract: Compared with relying solely on initial observations and language instructions, predicting goal images with generative models as high-level visual guida

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GLoRI: Closed-Loop Whole-Body Tracking with Global-Local Reference Interaction for Humanoid Loco-Manipulation

DGX agent

arXiv:2609.05994v1 Announce Type: new Abstract: Humanoid loco-manipulation requires accurate whole-body motion tracking in the world frame for physical interaction. While local references preserve mot

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9 Sept 2026

HB-PVI: A Hierarchical Bayesian Personalization and Value-of-Information Framework for Complex Activity Recognition

arXiv:2609.05582v1 Announce Type: new Abstract: Personalization can improve activity-recognition performance, but participant-specific gains are heterogeneous, and every additional calibration label h

HyCO: A Hybrid Neural Solver for Combinatorial Optimization

arXiv:2609.07990v1 Announce Type: new Abstract: Sequential reinforcement learning (RL) solvers and global diffusion model (DM) solvers for neural combinatorial optimization exhibit complementary failu

Hypersolid: Emergent Vision Representations via Short-Range Repulsion

arXiv:2601.21255v2 Announce Type: replace Abstract: A central problem in self-supervised learning is preventing representation collapse. Most methods avoid it through global mechanisms, such as contra

ICI-VLA: In-Context Imitation with Spatiotemporally Aligned Demonstrations for Vision-Language-Action Models

arXiv:2609.07581v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are commonly adapted to new manipulation settings through additional gradient updates, which limits rapid deployme

Improving Generalizability and Undetectability for Targeted Adversarial Attacks on Multimodal Pre-trained Models

arXiv:2509.19994v3 Announce Type: replace Abstract: Multimodal pre-trained models (e.g., ImageBind), which align distinct data modalities into a shared embedding space, have shown remarkable success a

Interpretable and Fair Generalized Additive Neural Networks via Multi-objective Learning

arXiv:2609.05946v1 Announce Type: new Abstract: Interpretability and fairness are two of the most emphasized dimensions in trustworthy artificial intelligence (AI). Various explainable AI methods have

Kairos: A Dataset for Fine-Grained Video-Language Modeling over Space, Time, and Dynamics

arXiv:2609.08755v1 Announce Type: new Abstract: Many emerging video language modeling tasks require systems to move beyond clip-level abstraction and model visual content as it unfolds over extended t

KDFlow: A User-Friendly and Efficient Knowledge Distillation Framework for Large Language Models

arXiv:2603.01875v4 Announce Type: replace-cross Abstract: Knowledge distillation (KD) is widely used to compress and post-train large language models (LLMs), yet many existing frameworks execute teach

Knowledge-Guided Hierarchical Policy Learning for High-Precision Cylindrical Assembly under Tight Tolerances

arXiv:2609.06522v1 Announce Type: new Abstract: A hybrid hierarchical learning framework is proposed to achieve high-precision assembly of 170mm cylindrical components with tolerance of 0.1mm. The low

KTO: Model Alignment as Prospect Theoretic Optimization

arXiv:2402.01306v5 Announce Type: replace Abstract: Kahneman & Tversky's extit{prospect theory} tells us that humans perceive random variables in a biased but well-defined manner (1992); for example,

LAMP: Language-Assisted Motion Planning for Controllable Video Generation

arXiv:2512.03619v4 Announce Type: replace Abstract: Video generation has achieved remarkable progress in visual fidelity and controllability, enabling conditioning on text, layout, or motion. Among th

Large Discrete Policy: Advancing Explicit Behavior Modeling with Stochastic Iterative Scoring

arXiv:2609.07049v1 Announce Type: cross Abstract: Behavior policies are often formulated as continuous generative models, whose iterative denoising processes are expressive but difficult to interpret

LATS: Levy Adaptive Tree Sampling for Feedback-Driven Diverse Target Discovery

arXiv:2609.06761v1 Announce Type: new Abstract: While diffusion models excel at capturing complex data distributions, scientific discovery often requires steering generation toward specific, uncharact

Learning Adaptive SED for heterogeneous load balancing

arXiv:2609.06881v1 Announce Type: new Abstract: We study a two-server load balancing system with heterogeneous service rates that are a priori unknown to the dispatcher. The goal is to route customers

Learning Kernels by Alignment for Multiclass Bayes Classification

arXiv:2609.06474v1 Announce Type: new Abstract: Kernel methods separate data representation from decision-making, but typically require the kernel to be chosen in advance. We show that this kernel can

Let It Go or Learn to Self-Correct: Continuous Diffusion for Constrained Discrete Tasks

arXiv:2609.09009v1 Announce Type: new Abstract: Denoising Diffusion Probabilistic Models (DDPMs) generate samples by starting from noise and repeatedly denoising while keeping each update close to the

Leveraging Discrete Function Decomposability for Scientific Design

arXiv:2511.03032v3 Announce Type: replace Abstract: In the era of AI-driven science and engineering, we often want to design discrete objects in silico according to user-specified properties. For exam

Local and Global Stability in Performative Reinforcement Learning

arXiv:2609.06467v1 Announce Type: new Abstract: In performative reinforcement learning the deployed policy shapes the environment that generates the learner's future data, and the natural solution con

LongNav-R1: Horizon-Adaptive Multi-Turn RL for Long-Horizon VLA Navigation

arXiv:2602.12351v2 Announce Type: replace-cross Abstract: This paper develops LongNav-R1, an end-to-end multi-turn reinforcement learning (RL) framework designed to optimize Visual-Language-Action (VL

M3-Tele: A Unified Multimodal Teleoperational Framework for Compliant Whole-Body Mobile Manipulation

arXiv:2609.07859v1 Announce Type: new Abstract: Executing contact-rich tasks efficiently requires the seamless integration of whole-body coordination and physical compliance regulation. However, exist

MCGS-SLAM: A Multi-Camera SLAM Framework Using Gaussian Splatting for High-Fidelity Mapping

arXiv:2509.14191v4 Announce Type: replace-cross Abstract: Recent progress in dense SLAM has primarily targeted monocular setups, often at the expense of robustness and geometric coverage. We present M

MemCorr-DP: Counterfactual Correspondence Conditioning for a Diffusion Policy Guided by a Reference

arXiv:2609.06615v1 Announce Type: new Abstract: Behavior-cloned visuomotor policies can remain accurate near their training distribution yet fail when object position and camera viewpoint change toget

MetaRSI / RSI2: A Meta-Recursive Self-Improving System for Recursive Self-Improving Systems Themselves

arXiv:2609.06396v1 Announce Type: new Abstract: Recursive self-improvement (RSI) lets a system improve the model-building machinery from its own failures, so every later model inherits the gain. Yet R

Mind the Phase: Effective Rank and Representation Health in Legged Locomotion

arXiv:2609.06958v1 Announce Type: new Abstract: Reinforcement learning has become the leading paradigm in legged locomotion, enabling complex behaviors from backflips to parkour through massively para

Minimizing the Effect of Sleep Deprivation in the Forward-Forward Algorithm

arXiv:2609.06042v1 Announce Type: new Abstract: This paper addresses the challenge posed by sleep deprivation in the Forward-Forward algorithm, where separating the two passes in this algorithm and im

Mixing Makes Markovian Contexts Cheap for Linear Bandits

arXiv:2603.12530v3 Announce Type: replace Abstract: Recent work shows that when contexts are drawn i.i.d., linear contextual bandits can be reduced to single-context linear bandits. This ``contexts ar

MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control

arXiv:2609.06251v1 Announce Type: new Abstract: Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on

ModularPhaseNet: Finite-Cyclic Phase Geometry for Computable Semantic Hierarchy, Direction, and Context Consistency in Standard Transformers

arXiv:2609.06000v1 Announce Type: cross Abstract: We propose ModularPhaseNet, a classical and integer-computable discretization of the continuous complex phase geometry introduced in QuantumPhaseNet.

Monocular Visual Odometry without Calibration or Test-time Optimization

arXiv:2510.03348v4 Announce Type: replace Abstract: The most accurate monocular visual odometry systems require known camera intrinsics, refine their estimates with test-time optimization, and recover

MRI-Guided Reslice-Refined Cross-Slice SDF Reconstruction of the Left Ventricle from Cardiac MRI with Sparse Axial Supervision

arXiv:2609.08148v1 Announce Type: new Abstract: Reconstructing a three-dimensional left-ventricular (LV) endocardial surface from cardiac magnetic resonance (CMR) data is challenging when supervision

Multi-robot Learning-based Informative Path Planning Using Spatio-Temporal Gaussian Process Kalman Filter

arXiv:2609.05515v1 Announce Type: new Abstract: Multi-robot informative path planning (IPP) for persistent target monitoring requires robots to reason about spatial uncertainty, temporal evolution, an

Multi-Task Learning with Covariate-Overlap Regularization

arXiv:2505.24281v2 Announce Type: replace-cross Abstract: Multi-task learning improves data efficiency by sharing information across related tasks, but indiscriminate sharing can be harmful when their

Nearly Tight Rademacher Bounds for Sparsely Activated Neural Networks

arXiv:2609.09130v1 Announce Type: new Abstract: An input may activate few hidden units even when different inputs collectively use an entire network. We study the statistical complexity of this input-

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

arXiv:2609.09140v1 Announce Type: new Abstract: The digitization of healthcare has generated vast, longitudinal, and multimodal patient records over a lifetime, yet fully exploiting these data to repr

Noisy-Space Policy Gradient for Diffusion Policies in Offline Reinforcement Learning

arXiv:2609.06882v1 Announce Type: new Abstract: Diffusion policies offer a powerful and expressive parameterization for continuous control. Yet, their integration with reinforcement learning remains c

Non-Coherent Over-the-Air Federated Learning: Protocol, Convergence, and Device Scheduling

arXiv:2609.08312v1 Announce Type: cross Abstract: To mitigate the scalability bottleneck in the radio access network (RAN) in federated edge learning (FEEL), over-the-air federated learning (AirFL) ex

Norms at a Price: Why RL-Based Alignment Can Promise Conditional Compliance at Best

arXiv:2609.07627v1 Announce Type: cross Abstract: AI agents sometimes act aligned when they infer they are being tested, and differently when not. We argue this is not an anomaly but what current trai

NOVA: Normal-Side Modeling for Training-Free Zero-Shot Video Anomaly Detection

arXiv:2609.06360v1 Announce Type: new Abstract: Training-free zero-shot video anomaly detection (ZS-VAD) leverages vision-language models (VLMs) to localize anomaly instances from a predefined anomaly

Observing Health Outcomes Using Remote Sensing Imagery and Geo-Context Guided Visual Transformer

arXiv:2602.00110v2 Announce Type: replace Abstract: Visual transformers have driven major progress in remote sensing image analysis, particularly in object detection and segmentation. Recent vision-la

One Perturbation Is Not Enough: Identifiability and Blind Baselines for Behavioral AI Evaluation

arXiv:2609.06190v1 Announce Type: new Abstract: Behavioral evaluations perturb an input and read the induced change in the output in order to certify that a system uses that input. We show that the nu

One Step, One Lead: Mitigating Higher-Order Interference in Multi-Domain Reinforcement Learning via Cross-Step Control

arXiv:2609.06469v1 Announce Type: new Abstract: Reinforcement learning (RL) across multiple domains can broaden the reasoning capabilities of large language models (LLMs), yet joint training often deg

OracleZoom: On-Policy Self-Distillation Inspired Reference-Constrained Recursive Image Super Resolution

arXiv:2609.06490v1 Announce Type: new Abstract: Recursive Super-Resolution (SR) extends fixed-scale SR to extreme magnification by repeatedly feeding predictions back into the same model, analogous to

Parameterized and Streaming Algorithms for Euclidean Fair k-Center Clustering

arXiv:2609.06384v1 Announce Type: new Abstract: Motivated by the growing importance of fairness in machine learning, fair k-center clustering has attracted considerable research attention as a fundame

PASTEL: Panoramic Alignment for Monocular 4D Scene Reconstruction

arXiv:2609.06099v1 Announce Type: new Abstract: Reconstructing 4D scenes from casually captured monocular video is vital for applications in virtual reality (VR) and embodied AI. Recent advances in 4D

PGMT: Perceptive General Motion Tracking for Humanoid Robots

arXiv:2609.08511v1 Announce Type: new Abstract: Humanoid motion trackers can reproduce diverse whole-body motions, but their performance degrades on complex terrain where terrain-agnostic references b

PICANet: Physics-Informed Cascaded Asymmetric Network for Infrared Small Target Detection

arXiv:2609.07515v1 Announce Type: new Abstract: Infrared small target detection (ISTD) is an important research direction in image processing. However, existing methods are limited by severe backgroun