safety

OpenAI changed safety practices and paused RL training for two weeks after the Hugging Face breach and evidence Astra may have met a critical cyber threshold (Ina Fried/Axios)

Ina Fried / Axios: OpenAI changed safety practices and paused RL training for two weeks after the Hugging Face breach and evidence Astra may have met a critical cyber threshold — OpenAI said Tuesday t

safetytechmeme

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

PaSTel: Anchoring Histology in Spatial Transcriptomics via Multi-Scale Hierarchical Bio-Prior Contrastive Pretraining

DGX agent

arXiv:2608.14924v1 Announce Type: cross Abstract: Spatial transcriptomics (ST) links tissue morphology with molecular programs, motivating multimodal pretraining methods that align histology images wi

safetyarxiv-cs-ai

18 Aug 2026

Periocular Soft Biometrics: A Survey and Applications to Multimedia Forensics and Disinformation Detection

arXiv:2608.14701v1 Announce Type: new Abstract: Soft-biometric attributes such as gender, age, and ethnicity provide valuable ancillary evidence when full identity recognition is not feasible, support

PickStyle: Video-to-Video Style Transfer with Context-Style Adapters

arXiv:2510.07546v2 Announce Type: replace Abstract: We address the task of video style transfer with diffusion models, where the goal is to preserve the context of an input video while rendering it in

Planner-Conditioned Diffusion for Coordinated Multi-Agent Exploration

arXiv:2608.16229v1 Announce Type: new Abstract: Coordinated multi-agent exploration requires not only efficient individual coverage but also non-redundant coverage across agents over extended planning

POI Recommendation with LLM-Augmented Multi-Graph Learning and Contrastive Alignment

arXiv:2608.16407v1 Announce Type: cross Abstract: Point-of-interest (POI) recommendation models based on graph neural networks achieve strong performance by propagating collaborative signals over user

Pointer Networks with Q-Learning for Combinatorial Optimization

arXiv:2311.02629v5 Announce Type: replace Abstract: We introduce the Pointer Q-Network (PQN), a hybrid neural architecture that integrates model-free Q-value policy approximation with Pointer Networks

Position: AI Governance Needs ISO-like Interoperability Protocols, Not Just Laws

arXiv:2608.14568v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems become deeply integrated into critical global infrastructure, the urgency for robust governance frameworks has i

Position: AI Lock-In Is in Progress, and We Must Be Prepared

arXiv:2608.14565v1 Announce Type: new Abstract: AI safety research has mainly focused on two areas: technical alignment (ensuring AI systems produce human-aligned outputs) and the regulation of genera

Pre-training Visual Dexterity in Simulation

arXiv:2608.15917v1 Announce Type: cross Abstract: Large-scale pre-training has made robot policy fine-tuning increasingly data-efficient, but this progress has largely been driven by datasets and embo

Protein Structure Prediction: From Evolutionary Constraints to Generative Modeling

arXiv:2608.16094v1 Announce Type: new Abstract: Accurate protein structure prediction is fundamental to structural biology because protein structure underlies molecular function and provides a basis f

Prototype-Rectified Iterative Self-supervised Manifold Denoising under Severe Acoustic Shift

arXiv:2608.15037v1 Announce Type: cross Abstract: Audio-Text Foundation Models (ATMs) fail catastrophically under severe acoustic noise, yet existing adaptation strategies either rely on gradient-base

Q-based Variational Inverse Reinforcement Learning

arXiv:2608.16888v1 Announce Type: new Abstract: The development of safe and beneficial AI requires that systems can learn and act in accordance with human preferences. However, explicitly specifying t

Q-Regularized Generative Auto-Bidding: From Suboptimal Trajectories to Optimal Policies

arXiv:2601.02754v3 Announce Type: replace-cross Abstract: With the rapid development of e-commerce, auto-bidding has become a key asset in optimizing advertising performance under diverse advertiser e

QA-Merging: Query-Adaptive Reasoning via Layer Selective Model Merging

arXiv:2601.03506v2 Announce Type: replace-cross Abstract: Recent large reasoning models (LRMs) have achieved strong performance on complex reasoning tasks by generating a long chain-of-thought (Long-C

QuantumPhaseNet: A Gauge-Covariant Geometric and Quantum-Spectral Theory of Semantic Concept Hierarchies with Prototype Validation of a Classical Quantum-Inspired Model

arXiv:2608.15820v1 Announce Type: new Abstract: We present QuantumPhaseNet, a gauge-covariant geometric and quantum-spectral extension of Transformer representations. Context-dependent semantic states

safetyarxiv-cs-cl

R^3-Bench: LLMs Struggle with Resource-Rational Reasoning under Shared Budgets

arXiv:2608.16033v1 Announce Type: new Abstract: In cognitive science, resource rationality asks how an agent should allocate limited computation to maximize expected value. Most reasoning and agent be

safetyarxiv-cs-cl

Random Quadratic Form with random forcing: Metastable synchronization by noise

arXiv:2608.16664v1 Announce Type: cross Abstract: We study the Random Quadratic Form (RQF) on a sphere in the presence of random Brownian forcing. We show that the forcing does not effectively change

REFLEX: Reflexive Equilibrium Fixed-point Learning for Endogenous eXchanges

arXiv:2608.16155v1 Announce Type: new Abstract: In over-the-counter corporate bond markets, dealers compete for client trades by quoting bid and ask prices. Tighter quotes attract more business, but a

ReForge: Keeping ABR Algorithms Never Finished with Verified Large Language Model Edits

arXiv:2608.15138v1 Announce Type: new Abstract: Designing an ABR algorithm for one network scenario takes an engineer months, and large language models now do this work in hours, matching or beating h

Reminder that the data that feeds large language models – and thereby influences the world - can change at any moment, without warning.

Reminder that the data that feeds large language models – and thereby influences the world - can change at any moment, without warning. looks like reddit is almost wiped from chatgpt sources the query

safetygary-marcus--x

Rethinking Reverse KL as Adaptive Entropy Distillation

arXiv:2608.14685v1 Announce Type: new Abstract: Knowledge distillation (KD) is widely used to transfer the capabilities of large language models (LLMs) to smaller students, but existing objectives oft

Revisiting Classifier-Free Guidance Methods in Latent Diffusion Models

arXiv:2608.16786v1 Announce Type: new Abstract: Inference-time quality-enhancement methods are an effective and widely adopted means of improving diffusion models without expensive retraining. We stud

Reward hacking in physical reinforcement learning revealed by turbulent drag reduction

arXiv:2606.06227v3 Announce Type: replace-cross Abstract: Reinforcement-learning controllers optimise specified rewards, but in physical systems those rewards often capture only part of the true contr

RLCascadeRouter: Quality-Estimator-Free Cascade Routing via Reinforcement Learning

arXiv:2608.15817v1 Announce Type: new Abstract: The growing ecosystem of large language models (LLMs) offers huge potential to optimize performance-cost trade-offs. However, their heterogeneous capabi

RoboMirror: Understand Before You Imitate for Video to Humanoid Locomotion

arXiv:2512.23649v4 Announce Type: replace-cross Abstract: Humans learn locomotion through visual observation, interpreting visual content first before imitating actions. However, state-of-the-art huma

Robust structure from motion for aerial-ground images via detector-free feature matching and multi-view track refinement

arXiv:2608.15251v1 Announce Type: new Abstract: Integrated 3D reconstruction from aerial-ground images is essential for generating high-precision urban 3D models, yet severe variations in viewpoint, s

S^3: A Smooth Simulation Surrogate for Optimizing Discrete Abstractions of Dynamical Systems

arXiv:2608.15920v1 Announce Type: cross Abstract: Intelligent systems are increasingly deployed in safety-critical settings with black-box controllers, including neural networks. The properties and be

SCALE: State-Calibrated Latent Embeddings for JEPA Planning in the Right Geometry

arXiv:2608.16287v1 Announce Type: new Abstract: Joint-embedding predictive world models plan by scoring predicted terminal embeddings against a goal embedding using a cost defined on the representatio

ScenarioCharacterization: A Modular Toolkit for Characterizing Safety across Trajectory Datasets

arXiv:2608.16041v1 Announce Type: new Abstract: We introduce ScenarioCharacterization, an open-source framework for automated, dataset-agnostic profiling of driving scenarios in trajectory datasets. O

Seeing Before Answering: Training-Free Visual Layer Profiling for Vision-Language Models

arXiv:2608.16263v1 Announce Type: new Abstract: LLaVA-style Vision-Language Models (VLMs) pass visual tokens from a fixed late layer of the vision backbone, typically the penultimate one, to the langu

Seeing the Bigger Picture: 3D Latent Mapping for Mobile Manipulation Policy Learning

arXiv:2510.03885v4 Announce Type: replace Abstract: In this paper, we demonstrate that mobile manipulation policies utilizing a 3D latent map achieve stronger spatial and temporal reasoning than polic

Self-Supervised Auxiliary Task Discovery for Stable Reinforcement Learning in Stock Trading

arXiv:2608.15841v1 Announce Type: new Abstract: Reinforcement learning has gained increasing attention as a data-driven approach for stock trading. However, learning a policy that is both profitable a

Self-Supervised Noise2Noise-Enhanced Denoising for Continuous-Scan Air-Plasma THz Spectroscopy

arXiv:2608.16454v1 Announce Type: cross Abstract: Terahertz time-domain spectroscopy (THz-TDS) based on air-plasma generation and balanced air-biased coherent detection offers gap-free broadband cover

Semantic Bandits: In-Context Exploration-Exploitation is Biased by Semantic Priors

arXiv:2608.16707v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as decision-making agents in settings that require sophisticated environmental exploration. How

SemVideo: Reconstructs What You Watch from Brain Activity via Hierarchical Semantic Guidance

arXiv:2602.21819v3 Announce Type: replace-cross Abstract: Reconstructing dynamic visual experiences from brain activity provides a compelling avenue for exploring the neural mechanisms of human visual

Sequential Batch Learning in Finite-Action Linear Contextual Bandits

arXiv:2004.06321v2 Announce Type: replace Abstract: We study the sequential batch learning problem in linear contextual bandits with finite action sets, where the decision maker is constrained to spli

Sequential Multimodal Evidence Optimization for Product Media Ranking in E-Commerce

arXiv:2608.15662v1 Announce Type: new Abstract: On modern e-commerce stores, customers consume ordered slates of heterogeneous product media, such as images, videos, and 3D renders, before making purc

SIGMA-Lane: Scale-pyramId Gated MAmba for Temporally Consistent Video Lane Detection

arXiv:2608.16338v1 Announce Type: cross Abstract: Video lane detection requires predictions that remain stable across frames, yet severe vehicle occlusions can break temporal cues. In streaming recurr

SingDance: Compositional Zero-Shot Singing-and-Dancing Video Generation with Role-Aware Audio Conditioning

arXiv:2608.16220v1 Announce Type: cross Abstract: Generating personalized dance videos from a reference image, text prompt, and audio track requires music-conditioned body motion. Singing-and-dancing

Software Engineering for AI-driven Building Operation

arXiv:2608.16237v1 Announce Type: cross Abstract: Building operations are energy-inefficient. Artificial Intelligence (AI)-driven control systems promise benefits through optimization and predictive c

Some Modifications to Our End-to-End UAV Planner

arXiv:2608.15741v1 Announce Type: new Abstract: The one-stage planner YOPO maps a single depth image and the robot state directly to a set of candidate trajectories, trained by backpropagating through

Spatially-Grounded Flow Matching: Structured Source Distributions for Image Generation

arXiv:2608.15452v1 Announce Type: new Abstract: Current flow matching models learn to transport the source i.i.d. Gaussian noise into the target distribution of natural images, yet this source distrib

STAG-VIO: Stabilized Prompt-to-Geometry Interface for Robust Dynamic Visual--Inertial Odometry

arXiv:2411.19289v4 Announce Type: replace Abstract: Dynamic visual-inertial odometry (VIO) requires reliable suppression of motion-corrupted measurements, yet prior semantic-assisted approaches depend

Step-Level On-Policy Distillation: Interpolating Between On-Policy Distillation and Supervised Fine-Tuning

arXiv:2608.16333v1 Announce Type: cross Abstract: On-policy distillation (OPD) aligns a student model with a teacher's logit distribution on student-generated trajectories. This approach has achieved

StreamOPD: A Post-Training Recipe with Spatio-Temporal Cue Gating for Streaming Video Understanding

arXiv:2608.16320v1 Announce Type: new Abstract: Streaming video understanding demands direct responses from the causally observed prefix of an unfolding video. Existing systems add inference-time memo

StructRL: Structured Action-Space Exploration for Flow-Based VLAs

arXiv:2608.15139v1 Announce Type: new Abstract: Flow-based Vision-Language-Action (VLA) models are now widely used for continuous robotic manipulation, and online reinforcement learning (RL) is emergi

SurgVIL: Scaling Surgical Robot Imitation Learning with Open-source Surgical Videos

arXiv:2608.16058v1 Announce Type: new Abstract: Learning-based surgical robot autonomy requires large-scale demonstrations with synchronized videos and robot actions, but such data are exceedingly rar