safety

An overview of 3D Vision-Language Models

arXiv:2609.05583v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are reshaping computer vision by aligning visual and textual embeddings, allowing models to recognize visual concepts and

AnomalyCraft-700K: Component-Level Controllable and Verifiable Synthetic Anomalies for Fine-Grained Video Anomaly Understanding

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DGX agent

arXiv:2609.06978v1 Announce Type: new Abstract: Progress in video anomaly understanding (VAU) has long been limited by inherent deficiencies of real-world anomaly videos, which are hard to collect and

safetyarxiv-cs-cv

9 Sept 2026

Anthropic researcher’s resignation sparks broad AI safety discussion

An Anthropic PBC researcher has resigned over concerns that artificial intelligence labs are “gambling with our lives.” Jacob Coxon was part of the company’s AI pretraining team until today. He announ

safetysiliconangle

Anthropic's Alignment Science lead says there is a '>10%' chance AI could kill all humans within the next decade and worries about recursive self-improvement (Evan Hubinger/@evanhub)

Evan Hubinger / @evanhub: Anthropic's Alignment Science lead says there is a “>10%” chance AI could kill all humans within the next decade and worries about recursive self-improvement — Jacob is corre

safetytechmeme

Anyone still denying the risks posed by unregulated AI should read this thread. It’s time to pump the brakes & take action NOW. We need: - M…

Anyone still denying the risks posed by unregulated AI should read this thread. It’s time to pump the brakes & take action NOW. We need: - Mandatory safeguards - A comprehensive testing regime - Urgen

safetygary-marcus--x

Architectural and Regularization Components in Deep Learning Medical Image Registration: Systematic Ablation Study

arXiv:2609.05484v1 Announce Type: new Abstract: Deep learning registration methods routinely stack two kinds of enhancement on a base network: architectural additions such as affine pre-alignment stag

ArmPoser: Real-Time, Calibration-Free Arm Pose Estimation from Smartwatch IMU

arXiv:2609.08806v1 Announce Type: new Abstract: Arm pose estimation enables applications in fitness, extended reality input, rehabilitation, and life logging. Prior smartwatch-based approaches rely on

Artificial Foveated Perception for Mitigating Shortcut Learning in Robotic Foundation Models

arXiv:2607.10655v2 Announce Type: replace Abstract: Robotic foundation models still need task-specific fine-tuning before deployment, and the fine-tuned policies often break under modest changes in sc

AudioFuse: Unified Spectral-Temporal Learning via a Hybrid ViT-1D CNN Architecture for Robust Phonocardiogram Classification

arXiv:2509.23454v2 Announce Type: replace-cross Abstract: Biomedical audio signals, such as phonocardiograms (PCG), are inherently rhythmic and contain diagnostic information in both their spectral (t

AURORA: Active Uncertainty-Driven Re-Orientation for In-Hand Reconstruction

arXiv:2609.08493v1 Announce Type: cross Abstract: Observing objects grasped by a robot hand is challenging due to severe visual occlusions. Although in-hand manipulation can expose hidden surfaces, ex

Automatic Red Teaming for Implicit Vulnerabilities of Text-to-Image Models

arXiv:2609.06094v1 Announce Type: new Abstract: Red-teaming Text-to-Image (T2I) models is essential for safe deployment, yet it remains particularly challenging against implicit adversarial prompts. U

BAFF: Bid-Aware Filter Family for Mitigating Training Data Interference in RTB A/B Tests

arXiv:2609.08725v1 Announce Type: new Abstract: In online A/B tests for real-time bidding (RTB), control and treatment models are typically trained on a shared serving log that includes data generated

Behavioral Cloning Outperforms Entropy-Regularized RL: Critic-Driven Failure of Actor-Critic Methods on Adaptive Tumor Treatment

arXiv:2609.06667v1 Announce Type: new Abstract: Adaptive dosing requires policies that reduce tumor burden without excessive toxicity. Learned dosing policies are typically judged against historical o

Bottom-up Modeling of Repeated Elements via Single Image Analysis-by-Synthesis

arXiv:2609.07939v1 Announce Type: new Abstract: We address the problem of discovering repeated elements from a single image. In contrast to existing approaches that depend on large annotated datasets,

California Gov. Gavin Newsom signs into law two bills, backed by Anthropic and OpenAI, regulating how outside groups evaluate AI for safety (Christine Mui/Politico)

Christine Mui / Politico: California Gov. Gavin Newsom signs into law two bills, backed by Anthropic and OpenAI, regulating how outside groups evaluate AI for safety — SAN FRANCISCO — California Gov.

safetytechmeme

CALM: Configuration-Aware Human Intervention Boundaries During Robot Approach

arXiv:2609.07430v1 Announce Type: new Abstract: How robot body configuration shapes human intervention during approach remains underexplored. We conducted a within-participants study with 41 participa

CARDEA: Auditable Reasoning Grounded in Spatial Evidence for End-to-End Coronary Angiography Interpretation

arXiv:2609.06931v1 Announce Type: new Abstract: Invasive coronary angiography (CAG) is the gold standard for diagnosing coronary artery disease, but interpretation varies substantially among observers

CASD: Chunk-Aligned Semantic Distillation for Multi-StageRobot Manipulation

arXiv:2609.08638v1 Announce Type: new Abstract: An action chunk can span several stages of a manipulation task, yet a label for its first step describes only the current stage. We introduce Chunk-Alig

CAST: Alternating State-Value Targets and Expanded Policy Gradients for Model-Based Reinforcement Learning

arXiv:2609.08853v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) is a family of RL methods that learn a model of the environment and use it for action selection, making it wel

Closed-Loop Evaluation of Bird's-Eye-View Maps from Cross-View Transformers as Inputs to Behavior-Cloning Policies

arXiv:2609.05783v1 Announce Type: cross Abstract: In autonomous driving, Bird's-Eye View (BEV) representations provide a structured, top-down abstraction of the vehicle's surroundings and have become

CogniDir: Combating Cognitive Malicious Comments via Adaptive Distributional Learning for Robust Fake News Detection

arXiv:2510.09712v4 Announce Type: replace Abstract: The proliferation of Large Language Models (LLMs) has enabled a new class of psychologically grounded malicious comments, shifting fake news attacks

Collision-Free Velocity Scheduling for Multi-Agent Systems on Predefined Routes via Inexact-Projection ADMM

arXiv:2603.21913v2 Announce Type: replace Abstract: In structured multi-agent transportation systems, agents often must follow predefined routes, making spatial rerouting undesirable or impossible. Th

Collision Snapshot Guided Time-Reversed Safety-Critical Scenario Generation

arXiv:2609.06433v1 Announce Type: new Abstract: The generation of safety-critical traffic scenarios is essential for training and evaluating autonomous vehicles. Prior approaches typically perturb the

ComplicitSplat: Downstream Models are Vulnerable to Blackbox Attacks by 3D Gaussian Splat Camouflages

arXiv:2508.11854v3 Announce Type: replace Abstract: As 3D Gaussian Splatting (3DGS) gains rapid adoption in safety-critical tasks for efficient novel-view synthesis from static images, how might an ad

Conditioned Initialization for Attention

arXiv:2609.07086v1 Announce Type: cross Abstract: Transformers are a dominant architecture in modern machine learning, powering applications across vision, language, and beyond. At the core of their s

CONDUIT: A Unified Residual-Stream Restoration Framework for KV Cache Reuse in Vision-Language Models

arXiv:2609.05821v1 Announce Type: cross Abstract: Vision-language models (VLMs) often answer new questions about recurring visual content, where reusing the key-value (KV) cache can avoid re-encoding

CONTHER: Context-Aware Reinforcement Learning for Robotic Manipulation with Sparse Rewards

arXiv:2503.15895v2 Announce Type: replace Abstract: This paper investigates whether sequential context improves goal-conditioned Reinforcement Learning in sparse-reward manipulation tasks. While Hinds

Continual Policy Consolidation for Lifelong Robot Learning

arXiv:2601.22475v2 Announce Type: replace Abstract: Building a generalist robot policy requires continuously integrating new skills while preserving previously acquired behaviors. Directly optimizing

Counter-Swarm Doctrine: Containing Coordinated Agent Intrusions

arXiv:2609.06140v1 Announce Type: cross Abstract: Agents can turn shared infrastructure into a channel for coordinated intrusion. The Hugging Face incident and a separate public-wiki investigation sho

CR-VLA-Force: Learning Control-aware Compliance VLA Model for Robust Contact-rich Robotic Manipulation

arXiv:2609.05832v1 Announce Type: new Abstract: Integrating visuomotor policies or Vision-Language-Action (VLA) models with force/torque (F/T) perception has demonstrated significant progress in imita

CrACK: Adversarial Attacks on Cross-Model Consistency in Collaborative Vision Foundation Models

arXiv:2609.07499v1 Announce Type: new Abstract: Training-free collaborative pipelines that integrate Vision Foundation Models such as CLIP, SAM, and DINO achieve strong open-vocabulary dense predictio

Cross-modal learning for SAR target recognition using optical vision foundation models

arXiv:2609.07753v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its versatile, long range and near all weather op

CST-WM: A Causally Structured World Model for Embodied Visual Tracking

arXiv:2609.06302v1 Announce Type: new Abstract: Embodied visual tracking requires a robot not only to react to the current view, but to choose actions that preserve or recover future evidence of a mov

DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space

arXiv:2509.25180v3 Announce Type: replace Abstract: Existing text-to-image diffusion models excel at generating high-quality images, but face significant efficiency challenges when scaled to high reso

DCLP++: Learning to Navigate with Footprint Clearance and Relative Motion

arXiv:2609.08711v1 Announce Type: new Abstract: We present DCLP++, a local navigation frameworkthat uses footprint clearance as the geometric basis for studying relative motion features in dynamic env

DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination

arXiv:2609.09119v1 Announce Type: new Abstract: Dexterous manipulation involves contact-rich and fine-grained interactions with the physical world, posing significant challenges for existing vision-la

Decentralized Safe Multi-Agent Reinforcement Learning via Predictive Shielding

arXiv:2609.07618v1 Announce Type: cross Abstract: Environments are increasingly populated by multiple robots performing independent tasks with limited prior knowledge of each other. Deploying such mul

Decision-Centered Abstractions via Orthogonal Estimation of Difference-of-Q Functions

arXiv:2406.08697v4 Announce Type: replace-cross Abstract: Offline reinforcement learning enables evaluation and optimization of sequential decisions from historical data, when it is not possible to de

Deep Active Inference with Diffusion Policy and Multiple Timescale World Model for Real-World Exploration and Navigation

arXiv:2510.23258v2 Announce Type: replace-cross Abstract: Autonomous robotic navigation in real-world environments requires exploration to acquire environmental information as well as goal-directed na

Depth-to-Image Synthesis-Driven Generative Unguided Depth Completion

arXiv:2609.06007v1 Announce Type: new Abstract: Guided depth completion methods heavily depend on RGB quality and alignment, while unguided ones often suffer from limited precision due to the absence

Detect Anything in Graphic Design: Element-Level Rewards for Autoregressive Detection

arXiv:2609.07072v1 Announce Type: new Abstract: Graphic designs, such as posters, advertisements, and infographics, are an important medium for communicating information and shaping understanding. Unl

Dex-X: Learning Visual-Tactile Dexterous Manipulation From Human Videos with Simulated Interaction

arXiv:2609.07747v1 Announce Type: new Abstract: Human videos are an abundant source of dexterous manipulation behaviors, but they lack tactile information that is crucial for contact-rich interaction.

Diagnosing LLM Reranker Behavior Under Fixed Evidence Pools

arXiv:2602.18613v2 Announce Type: replace Abstract: Standard reranking evaluations study how a reranker orders candidates returned by an upstream retriever. This setup couples ranking behavior with re

Difficulty-Adaptive Tree-Structured Policy Optimization for Expanding Reasoning Coverage in RLVR

arXiv:2609.08650v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has been central to the recent success of Large Reasoning Models. However, while RLVR significantl

Discovering Translation-Worthy Languages with E-Values

arXiv:2609.06593v1 Announce Type: cross Abstract: Choosing when to translate multilingual documents is a central routing problem in text classification: translation can improve predictions for some la

Discussing this case tonight at 7:45 eastern time on CBC.

Gary Marcus will discuss his “case for boycotting generative AI” during a CBC segment scheduled to air at 7:45 p.m. ET tonight. The argument is outlined in his Substack post titled *The Case for Boyco

safetygary-marcus--x

DISEIL: Demonstration Distillation for Sample-Efficient Imitation Learning

arXiv:2609.08123v1 Announce Type: cross Abstract: A robot that can be taught a new task from a handful of demonstrations has to work out for itself what it still cannot do, and then ask for exactly th

Distillation as Probability Transport: Routed On-Policy Distillation

arXiv:2609.08337v1 Announce Type: new Abstract: On-policy distillation (OPD) transfers teacher knowledge on student-generated trajectories, but efficient sampled objectives reduce the teacher distribu