safety

PPO-EAL: Exact Augmented Lagrangian Proximal Policy Optimization for Safe Robotic Control

arXiv:2606.27861v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a promising solution to accomplish complex robotic control tasks; however, most of the current work ignores t

PreferThinker: Reasoning-based Personalized Image Preference Assessment

DGX agent

arXiv:2511.00609v4 Announce Type: replace Abstract: Personalized image preference assessment aims to evaluate an individual user's image preferences by relying only on a small set of reference images

safetyarxiv-cs-ai

29 Jun 2026

PRISON: Unmasking the Criminal Potential of Large Language Models

arXiv:2506.16150v4 Announce Type: replace-cross Abstract: As large language models (LLMs) advance, concerns about their misconduct in complex social contexts intensify. Existing research overlooked th

Productionized Fairness Measurement Under Privacy Constraints

arXiv:2606.27558v1 Announce Type: new Abstract: Fairness measurements in the form of disaggregated evaluations often rely on demographic signals that are legally constrained or culturally sensitive. R

Quantum Dynamic Time Warping for Multivariate Time Series Classification

arXiv:2606.27815v1 Announce Type: cross Abstract: Dynamic Time Warping (DTW) is a cornerstone for time series classification, but its reliance on Euclidean distances fails to capture latent cross-chan

Really impressive first few drives with FSD v14 lite! Big leap in capability and feature set from v12.6.4, it’s tuned for safety right now s…

Really impressive first few drives with FSD v14 lite! Big leap in capability and feature set from v12.6.4, it’s tuned for safety right now so it’s taking things slow and smoothly. Highway performance

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Reasoning-Enhanced Rare-Event Prediction with Balanced Outcome Correction

arXiv:2601.16406v2 Announce Type: replace-cross Abstract: Rare-event prediction is critical in domains such as healthcare, finance, reliability engineering, customer support, aviation safety, where po

RECAST: Model Reconstruction via Counterfactual-Aware Wasserstein Geometry under Limited Data

arXiv:2606.27948v1 Announce Type: new Abstract: Counterfactual explanations (CFs) help understand machine learning models by identifying minimal input changes that would lead to alternative model outc

Reflect-R1: Evidence-Driven Reflection for Self-Correction in Long Video Understanding

arXiv:2606.27922v1 Announce Type: cross Abstract: Current multimodal reflection mechanisms for long video understanding predominantly rely on closed-loop self-reflection within internal parameters. La

Regularized Reward-Punishment Reinforcement Learning

arXiv:2606.28152v1 Announce Type: new Abstract: We propose KL-Coupled Policy Regularization (KCPR), a policy coordination framework for Reward-Punishment Reinforcement Learning (RPRL). Based on KCPR,

Retroactive Advantage Correction: Closed-Form V-Trace Bias Correction for Delay-Aware RLHF

arXiv:2606.27580v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) in production does not always have a synchronous reward signal. Code-execution verifiers, slow judge

ReWorld: Learning Better Representations for World Action Models

arXiv:2606.27504v1 Announce Type: new Abstract: World Action Models (WAMs) model future environment evolution under action conditioning, offering a scalable paradigm for autonomous driving. However, e

Robust Harmful Features Under Jailbreak Attacks: Mechanistic Evidence from Attention Head Specialization in Large Language Models

arXiv:2606.28153v1 Announce Type: cross Abstract: Jailbreak attacks bypass LLM safety alignment, yet their mechanisms remain poorly understood. We provide evidence that attacks do not comprehensively

RPM-Distill: Physiology-guided Adaptive Cross-modal Distillation for Robust Remote Physiological Measurement

arXiv:2606.28089v1 Announce Type: new Abstract: Video-based remote physiological measurement (RPM) is highly accessible but remains fragile under varying illumination, skin tones, and motion. Radio fr

Scalable and Differentiable Point-Cloud Registration Using Maximum Mean Discrepancy

arXiv:2606.27818v1 Announce Type: new Abstract: We present MMD-Reg, a novel correspondence-free approach to point-cloud registration that is differentiable and has linear computational complexity in t

ScaLe-INR: Scale and Learn Implicit Neural Representations

arXiv:2606.27862v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) parameterized by multilayer perceptrons excel at modeling continuous signals. However, a key challenge persists a

Scene Generation at Absolute Scale: Utilizing Semantic and Geometric Guidance From Text for Accurate and Interpretable 3D Indoor Scene Generation

arXiv:2603.13910v2 Announce Type: replace Abstract: We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable

SceneBot: Contact-Prompted General Humanoid Whole Body Tracking with Scene-Interaction

arXiv:2606.27581v1 Announce Type: cross Abstract: Current humanoid reinforcement-learning policies excel at free-space motions but struggle with contact-rich tasks, as pure kinematic tracking cannot r

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems

arXiv:2505.23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disas

SHIFT: Motion Alignment in Video Diffusion Models with Adversarial Hybrid Fine-Tuning

arXiv:2603.17426v2 Announce Type: replace Abstract: Image-conditioned video diffusion models achieve impressive visual realism but often suffer from weakened motion fidelity, e.g., reduced motion dyna

SIDA: Synthetic Image Driven Zero-shot Domain Adaptation

arXiv:2507.18632v2 Announce Type: replace-cross Abstract: Zero-shot domain adaptation is a method for adapting a model to a target domain without utilizing target domain image data. To enable adaptati

SIFT: Self-Imagination Fine-Tuning for Physically Plausible Motion in Video Diffusion Models

arXiv:2606.27741v1 Announce Type: new Abstract: Recent advances in video diffusion models have greatly improved visual fidelity, yet their generated motions often violate physical plausibility. We obs

SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation

arXiv:2606.28276v1 Announce Type: new Abstract: Training and evaluating robot policies in the real world is costly and difficult to scale. We introduce SimFoundry, a modular and automated system for z

SITUATION EXPLAINED: Why is restricting open source AI models structurally impossible? @ClementDelangue, co-founder and CEO of @huggingface:…

SITUATION EXPLAINED: Why is restricting open source AI models structurally impossible? @ClementDelangue, co-founder and CEO of @huggingface: 'Open weights are fundamentally different than an API. The

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Soaring memory costs are posing existential threats to small electronics makers, amid thin margins, low supply chain leverage, and little room for price hikes (Kif Leswing/CNBC)

Kif Leswing / CNBC: Soaring memory costs are posing existential threats to small electronics makers, amid thin margins, low supply chain leverage, and little room for price hikes — Earlier this year,

safetytechmeme

Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting

arXiv:2602.01588v3 Announce Type: replace-cross Abstract: Multimodal time series forecasting is crucial in real-world applications, where decisions depend on both numerical data and contextual signals

SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks

arXiv:2606.27807v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become a dominant paradigm for embodied intelligence. However, most existing approaches are built on large-scal

StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views

arXiv:2606.28321v1 Announce Type: new Abstract: We present StructSplat, a feed-forward and generalizable 3D Gaussian reconstruction framework that operates directly on uncalibrated images without requ

Support-Constrained RL Enables Real-World Policy Improvement without Real-World Experience

arXiv:2606.27475v1 Announce Type: cross Abstract: Robots trained on real world data tend to be imprecise, slow, and brittle to perturbations. Improving these policies with reinforcement learning (RL)

Symmetry-Aware Transformer Training for Automated Planning

arXiv:2508.07743v2 Announce Type: replace Abstract: While transformers excel in many settings, their application in the field of automated planning is limited. Prior work like PlanGPT, a state-of-the-

SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation

arXiv:2508.06115v3 Announce Type: replace Abstract: Semantic segmentation in open-vocabulary scenarios presents significant challenges due to the wide range and granularity of semantic categories. Exi

TempAct: Advancing Temporal Plausibility in Autoregressive Video Generation via Planner-Executor RL

arXiv:2606.28016v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion models enable low-latency streaming generation by synthesizing videos chunk by chunk with cached visual context, but

Text as Illumination: Spatial Contrastive Retinex Learning for Language-guided Medical Image Segmentation

arXiv:2606.27794v1 Announce Type: new Abstract: Language-guided Medical Image Segmentation (LMIS) has shown great potential to improve the delineation of anatomical structures and lesions by integrati

That Wall Street Journal article about GLM catching up with Mythos (which is not true & the reporting doesn’t back up) is another one of tho…

That Wall Street Journal article about GLM catching up with Mythos (which is not true & the reporting doesn’t back up) is another one of those “everyone will ask me about it at every conference or mee

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The Bear Necessities: A Look at the Drivers, Dynamics, and Applications of the Pro-Russia Influence Ecosystem

Written by: James Sadowski, Alden Wahlstrom Introduction Four years into Russia’s full-scale invasion of Ukraine, the pro-Russia influence ecosystem has evolved from a tool of war back into a global s

safetygoogle-cloud-ai

Tidal adopts an AI policy that blocks wholly AI-generated music from earning royalties and removes AI-generated music that impersonates artists (Murray Stassen/Music Business Worldwide)

Murray Stassen / Music Business Worldwide: Tidal adopts an AI policy that blocks wholly AI-generated music from earning royalties and removes AI-generated music that impersonates artists — TIDAL is in

safetytechmeme

ToE: A Hierarchical and Explainable Claim Verification Framework with Dynamic Multi-source Evidence Retrieval and Aggregation

arXiv:2606.27736v1 Announce Type: new Abstract: The rapid spread of fake news poses increasing threats to information ecosystems, especially as AI-generated misinformation under Generative Engine Opti

Towards Value-Constrained Credit Assignment in Fully Delegated AI Cooperatives

arXiv:2606.28217v1 Announce Type: cross Abstract: We propose a framework for reward allocation in fully delegated AI cooperatives where humans are represented by agents that contribute data and partic

Training Observable Control Policies to Expose Agent State Through Actions

arXiv:2606.27609v1 Announce Type: new Abstract: Physical or operational constraints often impose communications limitations on autonomous agents. Such limitations complicate monitoring or multiagent c

Trust Region Masking for Long-Horizon LLM Reinforcement Learning

arXiv:2512.23075v5 Announce Type: replace-cross Abstract: Policy gradient methods for Large Language Models optimize a policy pi_heta via a surrogate objective computed from samples of a rollout polic

Two-Stage Cross-Domain Cervical Abnormality Screening with Cytopathological Image Synthesis and Knowledge Distillation

arXiv:2606.27678v1 Announce Type: new Abstract: Cross-domain diagnosis remains a major challenge in cervical cell pathology due to pronounced domain shifts across institutions and the subtle visual di

Two-Stage Fine-Tuning for Protein Sequence Generation with Targeted Amino-Acid Composition

arXiv:2606.27939v1 Announce Type: cross Abstract: Protein language models are standard priors for biological sequence generation, but steering them toward explicit distributional design targets remain

Unbiased Binning for Fairness-aware Attribute Representation

arXiv:2509.21785v2 Announce Type: replace-cross Abstract: Discretizing raw features into bucketized attribute representations is a popular step before sharing a dataset. It is, however, evident that t

WARP-RM: A Warp-Augmented Relative Progress Reward Model for Data Curation

arXiv:2606.28320v1 Announce Type: new Abstract: Scaling imitation learning requires large datasets, yet human teleoperation inevitably produces mixed-quality demonstrations containing hesitations and

Another case of what I call The Klarna Effect.

Another case of what I call The Klarna Effect. 🦔Ford admitted it had to rehire engineers after replacing them with AI systems that couldn't do the job. The company's VP of hardware engineering said th

safetygary-marcus--x

@GaryMarcus For those interested in “The Klarna Effect”, see this post by @GaryMarcus : https://garymarcus.substack.com/p/ai-layoffs-product…

Gary Marcus discusses 'The Klarna Effect,' examining how AI adoption by companies like Klarna has led to significant workforce reductions despite increased productivity. The post explores the broader

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hard to see how anyone makes much money from all this in the long run. more like the airline industry; very small margins and big expenses p…

hard to see how anyone makes much money from all this in the long run. more like the airline industry; very small margins and big expenses pouring trillions in probably wasn’t wise China’s AI playbook

safetygary-marcus--x

I just watched an amazingly good lecture by Adam Brown about the future impact of AI on physics https://www.youtube.com/watch?v=Mw60FH5iflI

Adam Brown delivers a lecture examining how artificial intelligence is likely to transform physics research and discovery in the future. The talk covers the potential applications and impacts of AI to

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