safety

Anthropic didn’t just add guardrails to make Mythos safer; they added guardrails to protect their own IP. Their own IP. They are still as …

Anthropic didn’t just add guardrails to make Mythos safer; they added guardrails to protect their own IP. *Their own IP*. They are still as happy as fuck to build their AI on other people’s IP. Intere

safetygary-marcus--x

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Safety

Anthropic played the media like a fiddle. From “untold catastrophe” to “check our latest model”, in two months and a day 🙄 (cc @tomfriedman…

DGX agent

Anthropic played the media like a fiddle. From “untold catastrophe” to “check our latest model”, in two months and a day 🙄 (cc @tomfriedman) This is the scary phase of AI — a model deemed so powerful

safetygary-marcus--x

9 Jun 2026

Automated Framework to Evaluate and Harden LLM System Instructions against Encoding Attacks

arXiv:2604.01039v2 Announce Type: replace-cross Abstract: System Instructions in Large Language Models (LLMs) are commonly used to enforce safety policies, define agent behavior, and protect sensitive

Autonomous Aerial Manipulation via Contextual Contrastive Meta Reinforcement Learning

arXiv:2606.08533v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are increasingly being deployed in logistics, service robotics, and other real-world applications, creating a growing de

Autonomous FPV Flight with Translational Optical Flow and Uncertainty Mask

arXiv:2606.09088v1 Announce Type: new Abstract: Autonomous FPV quadrotor flight in complex environments using a monocular RGB camera as the sole exteroceptive sensor remains a fundamental challenge. R

Autonomous Incident Resolution at Hyperscale: An Agentic AI Architecture for Network Operations

arXiv:2606.09122v1 Announce Type: cross Abstract: Cloud network infrastructure at hyperscale presents unique operational challenges where traditional human-driven incident response cannot keep pace wi

Autonomous Obstacle Removal for Excavators through Policy Learning with Particle Simulation

arXiv:2606.09183v1 Announce Type: new Abstract: Autonomous obstacle removal from the ground is an important earthwork task, but this is difficult to automate because an excavator must adapt its excava

Back to the Familiar Future: Failure Recovery for VLA Policies via Pre-Imagined Milestone Selection

arXiv:2606.09258v1 Announce Type: new Abstract: Vision-language-action (VLA) policies can deviate from nominal trajectories during manipulation, even when tasks remain physically feasible. Recovering

Baichuan-M4: A Clinical-Grade Medical Agent System for Continuous Care

arXiv:2606.08982v1 Announce Type: new Abstract: Baichuan-M4 is Baichuan Intelligence's clinical-grade medical large model, designed for continuous care rather than single-turn medical question answeri

Bandits for Efficient Experimentation: Adapting to Control Group, Preferences, and Context Drifts

arXiv:2606.09802v1 Announce Type: cross Abstract: We consider a variant of the linear contextual stochastic multi-armed bandits, where the learner must provide recommendations to a group of users, eac

BareWave: Waveform-Native Flow-Matching Text-to-Speech

arXiv:2606.09048v1 Announce Type: cross Abstract: Removing intermediate representations and separately trained decoding stages has become an important direction in generative modeling. In text-to-spee

Beware of GeeksBearing Gifts: Building True EU Frontier AI Sovereignty

arXiv:2606.07536v1 Announce Type: cross Abstract: Frontier artificial intelligence is reshaping all aspects of society, from economic output or military capability to democratic institutions. The EU i

Beyond Accuracy: Interpreting Topic Representation in Suicide Ideation Detection Models

arXiv:2606.07714v1 Announce Type: cross Abstract: Suicide ideation detection models are typically evaluated using aggregate performance metrics, yet little is known about how they internally represent

Beyond Homophily: Towards Generalized Graph Reconstruction Attack and Defense

arXiv:2606.08067v1 Announce Type: new Abstract: Graph neural networks (GNNs) are widely deployed on relational data, yet they can leak sensitive or proprietary information about the training graph adj

Beyond Linear Activation Steering: Invertible Latent Transformations for Controlling LLM Behavior

arXiv:2606.08454v1 Announce Type: new Abstract: Activation steering provides a lightweight inference-time mechanism for controlling large language models (LLMs) by modifying their internal activation

Beyond Neural Collapse: Task-Intrinsic Geometry Governs Neural Representations in Modular Arithmetic

arXiv:2606.08985v1 Announce Type: new Abstract: While neural collapse (NC) predicts that a K-class-balanced classifier should organize terminal representations as a (K-1)-dimensional simplex equiangul

Beyond Scalar Rewards by Internalizing Reasoning into Score Distributions

arXiv:2606.09076v1 Announce Type: new Abstract: Reward models are central to text-to-image post-training, but visual preference is subjective and better represented as a distribution over rubric score

Boundary Variance Inflation Causes Acquisition Bias in Gaussian Processes

arXiv:2606.07561v1 Announce Type: new Abstract: Gaussian processes with stationary kernels on bounded domains exhibit inflated posterior variance near the boundary. Despite being a long-recognized art

Brain-Prompt Injection: A Route-Safety Audit for BCI-LLM Agents

arXiv:2606.09315v1 Announce Type: cross Abstract: BCI-to-agent pipelines turn decoded neural activity into an authorization channel for tool-use agents, exposing a new attack surface we call brain-pro

Breaking the Tokenizer Barrier: On-Policy Distillation across Model Families

arXiv:2606.09456v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has become a core technique in the post-training of Large Language Models (LLMs) for transferring knowledge from domain exp

Bridging Expert Knowledge and Automated Feature Engineering via Self-Evolution

arXiv:2606.08800v1 Announce Type: new Abstract: In high-stakes settings such as brand compliance, clinical care, and content moderation, machine learning cannot be deployed as opaque oracles: practiti

Bridging Traditional Explainability Methods and Multimodal Multilingual Models: An XAI-Based Analysis

arXiv:2606.07533v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) effectively integrate text and audio to interpret context in complex interactive dialogues. However, the inte

Brilliant idea! Next up: Apple randomly reboots your Mac if you're building competing tech, Gmail silently edits your email if you mention r…

Brilliant idea! Next up: Apple randomly reboots your Mac if you're building competing tech, Gmail silently edits your email if you mention rival platforms, and Tesla Autopilot swerves if it detects yo

safetyjeremy-howard--x

Can Data Work be Reparative?

arXiv:2606.09408v1 Announce Type: cross Abstract: We present an ethnographic study of an alternative approach to data work, developed by a civic-tech initiative that builds datasets for training and b

Can the Environment Speak for Itself? T^{2}-GRPO: A Turn-Trajectory Group Relative Policy Optimization for Caregiver Agents

arXiv:2606.08875v1 Announce Type: new Abstract: Optimizing large language models (LLMs) for long-horizon caregiver agents requires balancing delayed task objectives with immediate environment dynamics

Capability-Aligned Hierarchical Learning for Tool-Augmented LLMs

arXiv:2606.09371v1 Announce Type: new Abstract: Tool learning enables LLMs to invoke external tools to accomplish tasks. Prior studies have demonstrated the effectiveness of a hierarchical structure:

CARE: A Conformal Safety Layer for Medical Summarization

arXiv:2606.08969v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for medical summarization, but their outputs can omit medically important information and introduce

Causal Semantic Alignment for LLM-based Time Series Forecasting

arXiv:2606.08262v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened new possibilities for time series forecasting by enabling alignment between temporal pattern

Causal Transfer in Medical Image Analysis

arXiv:2603.24388v2 Announce Type: replace Abstract: Medical imaging models frequently fail when deployed across hospitals, scanners, populations, or imaging protocols due to domain shift, limiting the

CheXanatomy: Anatomy-Aware Vision-Language Modeling for Chest Radiographs

arXiv:2606.08420v1 Announce Type: new Abstract: Vision-language models (VLMs) pretrained on large-scale image-text pairs demonstrate strong image-level understanding, but are primarily optimized for g

CineDance: Towards Next-Generation Multi-Shot Long-Form Cinematic Audio-Video Generation

arXiv:2606.09639v1 Announce Type: new Abstract: The fidelity and structural diversity of training datasets fundamentally determine the capabilities of video generation models. While commercial systems

Claw-R1: A Step-Level Data Middleware System for Agentic Reinforcement Learning

arXiv:2606.09138v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) has become an important post-training paradigm for turning LLMs from static chatbots into interactive agents, giving

CLPO: Curriculum Learning meets Policy Optimization for LLM Reasoning

arXiv:2509.25004v2 Announce Type: replace Abstract: Online reinforcement learning with verifiable rewards (RLVR) has become an effective paradigm for improving the reasoning abilities of large languag

Code Is More Than Text: Uncertainty Estimation for Code Generation

arXiv:2606.09577v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as code generators, where silently wrong programs pose real safety and reliability risks. Relia

Cold feet about coating the entire surface of the earth in data centers?

Gary Marcus likely discusses concerns about the environmental and practical implications of exponentially expanding data center infrastructure across the globe, questioning whether covering Earth's su

safetygary-marcus--x

Comparative evaluation of training strategies using partially labelled datasets for segmentation of white matter hyperintensities and stroke lesions in FLAIR MRI

arXiv:2601.20503v2 Announce Type: replace-cross Abstract: White matter hyperintensities (WMH) and ischaemic stroke lesions (ISL) are key imaging biomarkers of cerebral small vessel disease (SVD) detec

ConSteer-RL: Steering Reasoning Capabilities in Large Language Models via Confidence-Aware Reinforcement Learning

arXiv:2606.08088v1 Announce Type: new Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) has recently become a key paradigm for improving the reasoning abilities of Large Language Models

Constrained Paraphrase Consistency for LLM Hallucination Detection

arXiv:2606.08158v1 Announce Type: cross Abstract: Large language models (LLMs) can generate factually inconsistent claims, motivating accurate and scalable hallucination detectors. Prior work largely

Constrained user-item allocation for e-commerce marketing campaigns

arXiv:2606.09623v1 Announce Type: new Abstract: When running marketing campaigns, retailers must decide which products to promote and which users to target. These decisions are inherently coupled: eff

Constraint-Aware Optimization for Robust Protein Stability Prediction

arXiv:2606.08100v1 Announce Type: new Abstract: Multimodal DeltaDelta G predictors integrating protein language models with inverse-folding representations achieve strong in-distribution accuracy on t

Context-Fractured Decomposition Attacks on Tool-Using LLM Agents: Exploiting Artifact Provenance Gaps

arXiv:2606.09084v1 Announce Type: cross Abstract: Tool-using LLM agents interact with the world through actions that persist state in artifacts (e.g., workspace files or logs). Consequently, jailbreak

Context Over Compute Human-in-the-Loop Outperforms Iterative Chain-of-Thought Prompting in Interview Answer Quality

arXiv:2603.09995v2 Announce Type: replace-cross Abstract: Behavioral interview evaluation using large language models presents unique challenges that require structured assessment, realistic interview

Contrast encodes inductive bias: separating slow noise from dynamics in predictive representation learning

arXiv:2606.07770v1 Announce Type: new Abstract: Self-supervised methods that learn representations and predict dynamics fully in the latent space, such as JEPA, have been shown to confuse slowly varyi

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers

arXiv:2606.07604v1 Announce Type: cross Abstract: Analyzing attention weights has become a standard approach for interpreting the information flow of Large Language Models (LLMs). However, this approa

Cooperative Long Rope Skipping via Multi-Agent Reinforcement Learning

arXiv:2606.08064v1 Announce Type: new Abstract: Humans exhibit remarkable motor agility, enabling a wide range of dynamic skills such as running and jumping, which highlights the great potential of hu

Correct Looks Better: Pairwise Comparisons Reveal Accuracy Rankings

arXiv:2606.09409v1 Announce Type: new Abstract: Pairwise comparisons combined with aggregation methods like Elo have become central to evaluating generative models, yet concerns remain that they rewar

Cranio-Diff: Diffusion-based Cross-domain Craniofacial Reconstruction with 2D X-ray Skull Guidance and Structural Identity Constraints

arXiv:2606.09699v1 Announce Type: new Abstract: The state-of-the-art generative models, such as CycleGAN, Pix2Pix, and diffusion models have demonstrated remarkable performance in the face generation

Crayotter: Traceable Multi-Agent Workflows for Long-Form Video Editing

arXiv:2606.07636v1 Announce Type: new Abstract: Editing a long-form video from heterogeneous footage requires more than selecting clips: an agent must preserve narrative intent across material prepara