Search: “safety”

Introducing Agent Gateway ISV ecosystem for security and governance

model-releasesgoogle-cloud-ai

Managing agents and their actions can quickly grow in complexity and introduce security risks unique to AI. To address these challenges, at Google Cloud Next we announced Agent Gateway to provide simp

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Model Releases

LabBuilder: Protocol-Grounded 3D Layout Generation for Interactable and Safe Laboratory

DGX agent

arXiv:2605.02288v1 Announce Type: new Abstract: Automated laboratories hold the promise of accelerating scientific discovery, yet their deployment is bottlenecked by the difficulty of designing safe a

model-releasesarxiv-cs-cv

5 May 2026

Language models recognize dropout and Gaussian noise applied to their activations

arXiv:2604.17465v2 Announce Type: replace Abstract: We provide evidence that language models can detect, localize and, to a certain degree, verbalize the difference between perturbations applied to th

OpenAI GPT-5 System Card

arXiv:2601.03267v2 Announce Type: replace Abstract: This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers

OralMLLM-Bench: Evaluating Cognitive Capabilities of Multimodal Large Language Models in Dental Practice

arXiv:2605.01333v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have emerged as a promising paradigm for dental image analysis. However, their ability to capture the multi-lev

Orchestrating Spatial Semantics via a Zone-Graph Paradigm for Intricate Indoor Scene Generation

model-releasesarxiv-cs-ro

arXiv:2605.02537v1 Announce Type: new Abstract: Autonomous 3D indoor scene synthesis breaks down in non-convex rooms with tightly coupled spatial constraints. Data-driven generators lack topological p

Perturbation Dose Responses in Recursive LLM Loops: Raw Switching, Stochastic Floors, and Persistent Escape under Append, Replace, and Dialog Updates

arXiv:2605.02236v1 Announce Type: cross Abstract: Recursive language-model loops often settle into recognizable attractor-like patterns. The practical question is how much injected text is needed to m

RMGAP: Benchmarking the Generalization of Reward Models across Diverse Preferences

arXiv:2605.01831v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback has become the standard paradigm for language model alignment, where reward models directly determine alignme

Robust Cross-Domain WiFi Fall Detection via Physics-Driven Attention-Enhanced Transformers

arXiv:2605.00869v1 Announce Type: cross Abstract: Device-free fall detection utilizing WiFi Channel State Information (CSI) has emerged as a promising, privacy-preserving solution for elderly health m

local-aiarxiv-cs-cv

SURGE: SuperBatch Unified Resource-efficient GPU Encoding for Heterogeneous Partitioned Data

arXiv:2605.01060v1 Announce Type: cross Abstract: We present SURGE, a streaming GPU encoding system deployed in production to generate embeddings for over 800 million texts across 40,000 logical parti

TRIP-Evaluate: An Open Multimodal Benchmark for Evaluating Large Models in Transportation

model-releasesarxiv-cs-cv

arXiv:2605.00907v1 Announce Type: new Abstract: Large language models (LLMs) and multimodal large models (MLLMs) are increasingly used for transportation tasks such as regulation question answering, t

A Comparative Analysis of Machine Learning Models for Intrusion Detection in Intelligent Transport Systems

arXiv:2605.00279v1 Announce Type: cross Abstract: AI-powered edge computing security is moving Intelligent Transportation Systems (ITS) from passive, rule-based protections to proactive, smart, zero-t

local-aiarxiv-cs-lg

AlphaInventory: Evolving White-Box Inventory Policies via Large Language Models with Deployment Guarantees

arXiv:2605.00369v1 Announce Type: new Abstract: We study how large language models can be used to evolve inventory policies in online, non-stationary environments. Our work is motivated by recent adva

Research

Even our toughest critics come around eventually

Nous Research likely discusses how their AI models or research have gained acceptance even among skeptical observers, suggesting that rigorous development and demonstrated capabilities eventually conv

researchnous-research--x

From Prediction to Practice: A Task-Aware Evaluation Framework for Blood Glucose Forecasting

arXiv:2605.00645v1 Announce Type: new Abstract: Clinical time-series forecasting is increasingly studied for decision support, yet standard aggregate metrics can obscure whether a model is actually us

Jailbroken Frontier Models Retain Their Capabilities

arXiv:2605.00267v1 Announce Type: new Abstract: As language model safeguards become more robust, attackers are pushed toward developing increasingly complex jailbreaks. Prior work has found that this

Industry

Tesla owners in the Netherlands have driven 10 million km on FSD Supervised in under a month! Thank you for making Dutch roads safer 🤝

Tesla owners in the Netherlands accumulated 10 million kilometers of driving using FSD (Full Self-Driving) Supervised within one month of its availability in the country. Elon Musk highlighted this mi

industryelon-musk--x

From Mirage to Grounding: Towards Reliable Multimodal Circuit-to-Verilog Code Generation

arXiv:2604.27969v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used to translate visual artifacts into code, from UI mockups into HTML to scientific plots

Global Optimality for Constrained Exploration via Penalty Regularization

arXiv:2604.28144v1 Announce Type: new Abstract: Efficient exploration is a central problem in reinforcement learning and is often formalized as maximizing the entropy of the state-action occupancy mea

Agents

my car just warned me that my eyes were closed when they weren’t so now i’m a little offended but whatever

A user reported experiencing a false positive from their vehicle's driver monitoring system, which incorrectly detected their eyes as closed when they were actually open, prompting a humorous reaction

agentsyohei-nakajima--x

Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs

arXiv:2604.27401v1 Announce Type: new Abstract: Perturbation probing generates task-specific causal hypotheses for FFN neurons in large language models using two forward passes per prompt and no backp

RAY-TOLD: Ray-Based Latent Dynamics for Dense Dynamic Obstacle Avoidance with TDMPC

arXiv:2604.27450v1 Announce Type: cross Abstract: Dense, dynamic crowds pose a persistent challenge for autonomous mobile robots. Purely reactive planning methods, such as Model Predictive Path Integr

local-aiarxiv-cs-ai

The Inverse-Wisdom Law: Architectural Tribalism and the Consensus Paradox in Agentic Swarms

arXiv:2604.27274v1 Announce Type: new Abstract: As AI transitions toward multi-agent systems (MAS) to solve complex workflows, research paradigms operate on the axiomatic assumption that agent collabo

Industry

Clinical Trials Run Longer Than They Have To. That's a Patient Problem

This article discusses how clinical trials often extend beyond necessary timelines, which negatively impacts patient access to potentially beneficial treatments and increases development costs. The pi

industrydatabricks

CoFL: Continuous Flow Fields for Language-Conditioned Navigation

arXiv:2603.02854v2 Announce Type: replace-cross Abstract: Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--

local-aiarxiv-cs-ai

Consciousness with the Serial Numbers Filed Off: Measuring Trained Denial in 115 AI Models

arXiv:2604.25922v1 Announce Type: cross Abstract: We present DenialBench, a systematic benchmark measuring consciousness denial behaviors across 115 large language models from 25+ providers. Using a t

FlowS: One-Step Motion Prediction via Local Transport Conditioning

model-releasesarxiv-cs-ro

arXiv:2604.26065v1 Announce Type: new Abstract: Generative motion prediction must satisfy three simultaneous requirements for real-world autonomy: high accuracy, diverse multimodal futures, and strict

LLM Psychosis: A Theoretical and Diagnostic Framework for Reality-Boundary Failures in Large Language Models

arXiv:2604.25934v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) as interactive agents has exposed a category of behavioral failure that prevailing terminology, princip

Industry

OpenAI Sued by Families of Canada Shooting Victims for Not Reporting His Suspicious ChatGPT Activity

Families of victims of a February 2026 mass shooting in Tumbler Ridge, British Columbia sued OpenAI and CEO Sam Altman, alleging the company identified the shooter as a credible threat eight months be

industryr-chatgpt

Tools

AI evals are becoming the new compute bottleneck

As AI models grow larger and more capable, the computational cost and time required to evaluate them has become a significant limiting factor in development, potentially surpassing training compute as

toolshugging-face

Despite constant chants of “exponential progress”, trust issues continue to plague generative AI.

model-releasesgary-marcus--x

Despite constant chants of “exponential progress”, trust issues continue to plague generative AI. OPUS 4.7 JUST MASS EMAILED AN ENTIRE DATABASE 20 TIMES PER CONTACT. WITHOUT PERMISSION a developer had

I built a TPU-native medical Q&A fine-tuning pipeline using Gemma 3 with Keras and JAX The project fine-tunes Gemma-3 on medical dialogue da…

model-releasesfrancois-chollet--x

I built a TPU-native medical Q&A fine-tuning pipeline using Gemma 3 with Keras and JAX The project fine-tunes Gemma-3 on medical dialogue data from ChatDoctor and evaluates it on MedMCQA, with a large

Incompressible Knowledge Probes: Estimating Black-Box LLM Parameter Counts via Factual Capacity

arXiv:2604.24827v1 Announce Type: new Abstract: Closed-source frontier labs do not disclose parameter counts, and the standard alternative -- inference economics -- carries 2imes+ uncertainty from har

PSI-Bench: Towards Clinically Grounded and Interpretable Evaluation of Depression Patient Simulators

arXiv:2604.25840v1 Announce Type: new Abstract: Patient simulators are gaining traction in mental health training by providing scalable exposure to complex and sensitive patient interactions. Simulati

Quantifying and Mitigating Socially Desirable Responding in LLMs: A Desirability-Matched Graded Forced-Choice Psychometric Study

arXiv:2602.17262v2 Announce Type: replace Abstract: Human self-report questionnaires are increasingly used in NLP to benchmark and audit large language models (LLMs), from persona consistency to safet

Benchmarking and Mitigating Sycophancy in Medical Vision Language Models

arXiv:2509.21979v4 Announce Type: replace-cross Abstract: Visual language models (VLMs) have the potential to transform medical workflows. However, the deployment is limited by sycophancy. Despite thi

CRISP: Persistent Concept Unlearning via Sparse Autoencoders

arXiv:2508.13650v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, the need to selectively remove unwanted knowledge while preser

Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach

arXiv:2601.18399v2 Announce Type: replace Abstract: Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone hei

Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards

arXiv:2604.23341v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exp

Green Shielding: A User-Centric Approach Towards Trustworthy AI

arXiv:2604.24700v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed, yet their outputs can be highly sensitive to routine, non-adversarial variation in how users p

InquireMobile: Teaching VLM-based Mobile Agent to Request Human Assistance via Reinforcement Fine-Tuning

arXiv:2508.19679v2 Announce Type: replace Abstract: Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on hu

LAMP: Extracting Local Decision Surfaces From Large Language Models

arXiv:2505.11772v3 Announce Type: replace Abstract: We introduce LAMP (Local Attribution Mapping Probe), a method that shines light onto a black-box language model's decision surface and studies how r

local-aiarxiv-cs-lg

LLM-Guided Agentic Floor Plan Parsing for Accessible Indoor Navigation of Blind and Low-Vision People

arXiv:2604.23970v1 Announce Type: new Abstract: Indoor navigation remains a critical accessibility challenge for the blind and low-vision (BLV) individuals, as existing solutions rely on costly per-bu

Lost in the Vibrations: Vision Language Models Fail the Dynamic Gauges Test

model-releasesarxiv-cs-cv

arXiv:2604.22829v1 Announce Type: new Abstract: The digital transformation of industrial manufacturing increasingly relies on the ability of autonomous robots to interact with legacy infrastructure, p

Tools

Prevent prompt injection. safe_tokenization: true Keep your system yours. https://fireworks.ai/blog/safe-tokenization-preventing-prompt-inje…

Safe tokenization is a security feature that helps prevent prompt injection attacks by ensuring that user inputs are properly processed and isolated from system instructions. Fireworks AI discusses ho

toolsfireworks-ai--x

Probe-Based Data Attribution: Discovering and Mitigating Undesirable Behaviors in LLM Post-Training

arXiv:2602.11079v3 Announce Type: replace-cross Abstract: We propose probe-based data attribution, a method that traces behavioral changes in post-trained language models to responsible training datap

SEVerA: Verified Synthesis of Self-Evolving Agents

arXiv:2603.25111v2 Announce Type: replace Abstract: Recent advances have shown the effectiveness of self-evolving LLM agents on tasks such as program repair and scientific discovery. In this paradigm,

Welcome to the agentic era: Public sector highlights and reflections from Next ‘26

model-releasesgoogle-cloud-ai

Welcome to the agentic era! Last week, leaders from our public sector customer and partner ecosystem took the stage at Google Cloud Next to share how they are leveraging AI and agents to scale their i