safety

Neural Architecture Distributions: A New Paradigm for Stochastic Segmentation

arXiv:2606.21061v1 Announce Type: new Abstract: Stochastic segmentation seeks to represent multiple plausible masks for a single image, which is essential in safety- and quality-critical applications

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Neural Conjugate Aggregation: Identifiable Unsupervised Multi-Sensor Regression under Heterogeneous Sensor Bias

DGX agent

arXiv:2606.22200v1 Announce Type: new Abstract: We study regression-based data fusion under uncertainty, where multiple noisy and biased measurement sources are available but ground-truth labels are a

safetyarxiv-cs-lg

23 Jun 2026

Noise is Signal: Density-Based Outliers as Leading Indicators of Occupational Emergence in Labor Market Text

arXiv:2606.22769v1 Announce Type: new Abstract: Standard NLP pipelines for occupational clustering discard the 10-15% of job postings that density-based methods assign to noise. We argue this is an er

Objective-Behavior Alignment: Diagnostics for MORL Policy Selection

arXiv:2606.21321v1 Announce Type: new Abstract: Real-world decision-making often requires optimizing multiple competing objectives simultaneously. In reinforcement learning (RL), this is typically add

OFMU: Optimization-Driven Framework for Machine Unlearning

arXiv:2509.22483v2 Announce Type: replace Abstract: Large language models deployed in sensitive applications increasingly require the ability to unlearn specific knowledge, such as user requests, copy

OmniNWM: Omniscient Driving Navigation World Models

arXiv:2510.18313v5 Announce Type: replace Abstract: Autonomous driving world models are expected to work effectively across three core dimensions: state, action, and reward. However, existing methods

On the Limits of Prompt-Conditioned Language Models as General-Purpose Learners

arXiv:2606.23668v1 Announce Type: new Abstract: Large Language Models (LLMs) are frequently portrayed as general-purpose solvers capable of solving arbitrary tasks. We argue that this view overlooks a

On the Position Bias of On-Policy Distillation

arXiv:2606.22600v1 Announce Type: new Abstract: On-Policy Distillation (OPD) improves the learning efficiency of standard reinforcement learning through dense, token-level supervision from teachers. I

One Image is All You Need: Agentic One-Shot Image Generation via Text-Based World Models for Long-Tail Spatial Perception

arXiv:2606.20764v1 Announce Type: new Abstract: Reliable spatial decision automation, such as autonomous driving and maritime surveillance, critically depends on robust visual perception. However, rea

One Size does not Fit All: Heterogeneous Latent Space Alignment for Unsupervised Domain Adaptation

arXiv:2606.21415v1 Announce Type: new Abstract: Domain shift remains a major obstacle to the reliable deployment of machine learning models in high-stakes environments such as healthcare. While Domain

oops

oops Goldman reckons that AI will create about 10trn of discounted value for the world, or up to 22trn. But markets have priced in 27trn of additional value creation. So the size of the 'bubble' has n

safetygary-marcus--x

OpenHLM: An Empirical Recipe for Whole-Body Humanoid Loco-Manipulation

arXiv:2606.22174v1 Announce Type: new Abstract: Whole-body humanoid loco-manipulation requires coordinating the robot's entire kinematic chain. However, most existing systems typically decouple the up

'Oracle is under financial pressure because of an expensive build-out of AI data centers for customers like OpenAI.' https://www.bloomberg.c…

'Oracle is under financial pressure because of an expensive build-out of AI data centers for customers like OpenAI.' https://www.bloomberg.com/news/articles/2026-06-22/oracle-layoffs-fueled-by-ai-redu

safetygary-marcus--x

Overcoming Imperfect Kinematics in Surgical Robotics Through Sim-to-Real Visuomotor Learning

arXiv:2606.21396v1 Announce Type: new Abstract: Robot-Assisted Surgery is integral to modern minimally invasive procedures, with automation emerging as the next frontier to enhance precision and reduc

PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation

arXiv:2606.18375v2 Announce Type: replace Abstract: World foundation models (WFMs) are powerful simulators, yet they predominantly operate in a single-view setting and lack the multi-view 3D consisten

PanoVine: Whole-Body Visuomotor Control for Soft Growing Vine Robot

arXiv:2606.22923v1 Announce Type: new Abstract: Vine robots, a class of soft, growing robots, are suitable for navigating complex and confined environments due to their compliant bodies and self-suppo

PG-MAP: Joint MAP Optimization for Inference-Time Alignment of Diffusion and Flow-Matching Models

arXiv:2606.22958v1 Announce Type: cross Abstract: Inference-time alignment of pretrained text-to-image models is typically performed along a single control axis, such as classifier-free guidance, atte

phi-Scene: Physically Grounded Image-to-3D Scene Reconstruction

arXiv:2606.21596v1 Announce Type: new Abstract: Reconstructing compositional 3D scenes from a single image is a fundamental challenge in 3D world modeling. Recent methods can recover high-fidelity, co

Physically-guided Image Generation for Multi-Projection Mapping

arXiv:2606.22477v1 Announce Type: new Abstract: Projection Mapping (PM) enables seamless superimposition of digital content onto real-world 3D objects, serving as a fundamental technique for immersive

PISCES: Annotation-free Text-to-Video Post-Training via Optimal Transport-Aligned Rewards

arXiv:2602.01624v2 Announce Type: replace Abstract: Text-to-video (T2V) generation aims to synthesize videos with high visual quality and temporal consistency that are semantically aligned with input

PJ-RoPE: A Fourier-Jet-Affine Position Space for Relative Attention

arXiv:2606.05345v2 Announce Type: replace Abstract: We organize relative-position mechanisms in attention as a learnable Fourier-Jet-Affine position space. The starting point is lag-shift dynamics: a

Platooning Connected, Autonomous, and Human-Driven Vehicles: A Deep Reinforcement Learning-based Approach

arXiv:2606.20648v1 Announce Type: cross Abstract: Conventionally, existing vehicle platooning approaches are designed for connected vehicles, typically including connected autonomous vehicles and conn

PoLAR: Factorizing Extent and Mode in Latent Actions for Robot Policy Learning

arXiv:2606.21139v1 Announce Type: cross Abstract: Latent action pretraining learns representations of visual change from pairs of observations, but existing methods typically encode each transition as

Policy-as-Data: Learning Generalizable HOI Diffusion Models from Simulated Physics

arXiv:2606.22806v1 Announce Type: new Abstract: Synthesizing realistic Human-Object Interactions (HOI) is critical for creating embodied avatars and functional virtual environments. However, current d

PolicyTrim: Boosting Intrinsic Policy Efficiency of Vision-Language-Action Models

arXiv:2606.22540v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide a unified paradigm for robotic manipulation, yet their real-world deployment is often bottlenecked by execut

Pose-Agnostic Robotic Functional Grasping via Observation-Action Canonicalization

arXiv:2606.21148v1 Announce Type: new Abstract: Functional robotic grasping requires a policy that generalizes across diverse object geometries and poses while maintaining task-specific contact precis

Pose Anything Anywhere:Model-free Object Poses from Arbitrary References

arXiv:2606.23634v1 Announce Type: new Abstract: Estimating the 6D pose of unseen objects is a fundamental yet challenging problem for open-world robotics and embodied perception. Model-based methods a

Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation

arXiv:2606.20118v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) policies have shown strong potential for general-purpose manipulation, yet they often fail on novel, out-of-distr

Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model

arXiv:2408.06350v2 Announce Type: replace-cross Abstract: One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving.

Prefix-Guided On-Policy Distillation: Mining Golden Trajectories from Rollouts

arXiv:2606.21994v1 Announce Type: new Abstract: On-policy distillation (OPD) improves reasoning models by applying dense teacher supervision on student-sampled trajectories. However, scaling OPD to lo

Programmable magnetic soft robots with controlled locomotion and directional liquid cargo release

arXiv:2606.21737v1 Announce Type: new Abstract: Magnetically programmable soft elastomers enable complex shape morphing and locomotion dynamics in small scale soft robots under external magnetic field

Provably Efficient Policy-Reward Co-Pretraining for Adversarial Imitation Learning

arXiv:2606.22056v1 Announce Type: new Abstract: Adversarial imitation learning (AIL) achieves high-quality imitation compared to behavioral cloning (BC), but demands substantial online environment int

Real-Time Multimodal Activity-Aware Error Detection in Robot-Assisted Surgery

arXiv:2606.23593v1 Announce Type: cross Abstract: Robot-assisted minimally invasive surgery improves surgical precision but introduces complexity, making technical error detection essential for ensuri

RECALL: Recovery Experience Collection for Active Lifelong Learning in Vision-Language-Action Models

arXiv:2606.23617v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are commonly fine-tuned through passive imitation learning, where additional demonstrations are collected for task

Recency/Frequency Adaptive KV Caching for Large Language Model Serving

arXiv:2606.21238v1 Announce Type: cross Abstract: Key-value (KV) caching is a powerful technique for accelerating large language model inference and generation. Inference workloads are large and diver

ReFPO: Reflow Regularization for Flow Matching Policy Gradients

arXiv:2606.21086v1 Announce Type: new Abstract: We present Reflow-regularized Flow Matching Policy Gradients (ReFPO), a simple online RL method that adds explicit Reflow regularization to FPO for effi

Reinforcement Learning-Based Traffic Signal Control for IoT-Enabled Intersections

arXiv:2606.22108v1 Announce Type: cross Abstract: Urban traffic congestion remains a persistent challenge in car-dependent cities, imposing significant economic and societal costs. Traffic signal syst

RelightAnyone: A Generalized Relightable 3D Gaussian Head Model

arXiv:2601.03357v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has become a standard approach to reconstruct and render photorealistic 3D head avatars. A major challenge is to religh

Remember what you did?: Learning Behavioral Memories for Partially Observable Object Manipulation

arXiv:2606.21188v1 Announce Type: new Abstract: Long horizon, contact-rich manipulation is inherently partially observable. This is as a single visual observation rarely captures a robot's full action

Rethinking Object-Centric Representations for Video Dynamics Modeling

arXiv:2606.23436v1 Announce Type: new Abstract: Unsupervised video object tracking aims to decompose dynamic scenes into persistent, object-centric entities without manual annotations. Many recent app

RoboLineage: Agent-Native Data Lifecycle Governance Across Robot Policy Iterations

arXiv:2606.22142v1 Announce Type: new Abstract: We present RoboLineage, an agent-native data lifecycle governance system for robot policy iteration. Modern robot policies improve through repeated data

Robot Critics that Sweat the Small Stuff

arXiv:2606.21572v1 Announce Type: new Abstract: Large vision-language models contain several priors about the world and object interactions, making them useful critics during inference to steer robot

Robot Self-Improvement via Human-Video Dynamics Models

arXiv:2606.21406v1 Announce Type: cross Abstract: A central question in robot learning is how to acquire skills from the kinds of data that humans learn from: passive observation, embodied practice, a

Robust Representation Learning in Masked Autoencoders

arXiv:2602.03531v2 Announce Type: replace-cross Abstract: Masked Autoencoders (MAEs) achieve impressive performance in image classification tasks, yet the internal representations they learn remain le

Rotation-Aware Point-Cloud Embeddings for Vision-Based In-Hand Reorientation

arXiv:2606.21788v1 Announce Type: cross Abstract: Point-cloud goals provide a direct way to specify dexterous in-hand reorientation: instead of defining an object-specific pose frame or estimating 6D

RubricRL: Simple Generalizable Rewards for Text-to-Image Generation

arXiv:2511.20651v2 Announce Type: replace Abstract: Reinforcement learning (RL) has recently emerged as a promising approach for aligning text-to-image generative models with human preferences. A key

Safe Few-Step Generation via Velocity Editing

arXiv:2606.23267v1 Announce Type: new Abstract: Flow matching has recently emerged as a strong paradigm for state-of-the-art text-to-image (T2I) generation, enabling high-quality generation with a sma

Safe-SAGE: Social-Semantic Adaptive Guidance for Safe Engagement through Laplace-Modulated Poisson Safety Functions

arXiv:2603.05497v3 Announce Type: replace Abstract: Traditional safety-critical control methods, such as control barrier functions, suffer from semantic blindness, exhibiting the same behavior around