Search: “safety”

Fed-Equilibrium Framework for Topological Pareto Control in Robust and Fair Clinical Federated Learning

arXiv:2609.11937v1 Announce Type: new Abstract: The deployment of Federated Learning (FL) in multi-center clinical networks faces the challenge of 'knowledge dominance,' where high-volume hubs natural

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Fixed State, Long Reach: What a Constant-Size Cache Buys Block Diffusion at Scale

DGX agent

arXiv:2609.11998v1 Announce Type: new Abstract: Diffusion language models decode tokens in parallel, but their bidirectional denoiser rules out the naive key--value (KV) cache behind fast autoregressi

safetyarxiv-cs-lg

14 Sept 2026

FoldNet++: a Large-Scale Synthetic Dataset for Robotic T-Shirt Folding and Unfolding

arXiv:2609.12433v1 Announce Type: new Abstract: Due to the highly deformable nature of garments, training a generalizable policy for robotic T-shirt folding and unfolding remains a significant challen

GenOR-Twin: A Semantic Middleware for Integrating Operational Discourse with Mathematical Optimization

arXiv:2609.12863v1 Announce Type: new Abstract: We introduce GenOR-Twin, a neuro-symbolic framework that bridges the translation gap between unstructured operational logs and rigorous mathematical opt

GRACE-DS: a Guarded Reward-guided Agent Correction Environment in Data Science

arXiv:2606.16000v3 Announce Type: replace Abstract: We introduce GRACE-DS, a Guarded Reward-guided Agent Correction Environment in Data Science for pre-deployment evaluation of LLM-powered AutoML agen

safetyarxiv-cs-cl

Granularity-Adaptive Credit Assignment for Long-Horizon LLM Agent Reinforcement Learning

arXiv:2609.12424v1 Announce Type: new Abstract: Reinforcement learning is now the standard way to train large language model agents on long-horizon tasks, where dozens of interdependent actions preced

Model Releases

GSO-Net: Visual State Machines for Hazardous Freight Transfer Compliance at Petrochemical Logistics Nodes

model-releasesarxiv-cs-cv

arXiv:2609.12408v1 Announce Type: new Abstract: Hazardous-freight operations at petrochemical logistics nodes are safety-critical for intelligent transportation systems, yet existing vision benchmarks

Hidden in Rounds: Predicting the Time Cost of 802.11 Contention in Federated Learning

arXiv:2609.12903v1 Announce Type: new Abstract: Federated learning over IEEE~802.11 shares the wireless channel among clients that send model updates. We use ns-3 to measure the frame-delivery ratio a

House Speaker Johnson says there's 'potentially' a role for Congress in creating AI guardrail legislation and that he plans to hold a meeting with AI executives (Erik Wasson/Bloomberg)

Erik Wasson / Bloomberg: House Speaker Johnson says there's “potentially” a role for Congress in creating AI guardrail legislation and that he plans to hold a meeting with AI executives — House Speake

safetytechmeme

Improving Imitation Learning Efficiency for Manipulation through Geometric Prior Pretraining

arXiv:2609.12721v1 Announce Type: new Abstract: Applying an imitation learning policy to a new manipulation task usually requires collecting new demonstrations and retraining the model, which makes sa

Inferring Dislocation Microstructures from X-ray Diffraction via Cross-Modal Contrastive Learning

arXiv:2609.12713v1 Announce Type: cross Abstract: Understanding and inferring dislocation microstructures from diffraction patterns remains an open challenge in materials characterization, as diffract

Learning Sign Language Recognition under Label Noise: A Study of Noise-Robust Losses for Isolated and Continuous Settings

arXiv:2609.12885v1 Announce Type: new Abstract: In sign language recognition, the isolated (ISLR) classification loss treats a single label as ground truth, as does the frame-level auxiliary classifie

LettuceVisSim: A Simulator That Generates Lettuce Image Time-series for Vision-Based Reinforcement Learning

arXiv:2609.12505v1 Announce Type: new Abstract: Vision-based reinforcement learning holds strong potential for decision-making in controlled environment agriculture (CEA). However, its development is

Mayor Mamdani just torched Trump's government for turning a blind eye to AI threats: 'Like many Americans across the country, the news comin…

Mayor Mamdani just torched Trump's government for turning a blind eye to AI threats: 'Like many Americans across the country, the news coming out of this technology in recent days and weeks has been i

Michael Burry is saying exactly what i have been saying, for ages. The AI industry better hope we are both wrong

Michael Burry is saying exactly what i have been saying, for ages. The AI industry better hope we are both wrong Breaking: Michael Burry says OpenAI and Anthropic are faking the AI warnings due to slo

MInTRL: Off-policy Intervention can boost On-policy RL

arXiv:2609.12419v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards is typically performed on-policy, keeping training data close to the current policy but limiting learning

Multimodal Floorplan Encoding: Learning Dense Modality-Invariant Representations

arXiv:2609.12723v1 Announce Type: new Abstract: Floorplans arise in many forms, from vector CAD drawings to raster renderings and sensor-derived density maps. This heterogeneity makes it difficult to

Online Material Estimation for Conditioned Diffusion Policy in Shaping Deformable Linear Objects

arXiv:2609.12634v1 Announce Type: new Abstract: Shape control of deformable linear objects (DLOs) is challenging for imitation learning because deformation behavior varies with material properties suc

PACEvolve: Enabling Progress-Aware Consistent Evolution

arXiv:2601.10657v3 Announce Type: replace-cross Abstract: Self-evolving agents powered by Large Language Models (LLMs) have emerged as a promising direction across diverse domains, including code opti

PACIFIC: Can LLMs Discern the Psychometric Traits Influencing Your Preferences? Personality-Driven Preference Alignment in LLMs

arXiv:2602.07181v4 Announce Type: replace Abstract: User preferences are increasingly used to personalize Large Language Model (LLM) responses, yet reliably leveraging preference signals remains under

safetyarxiv-cs-cl

PATH: Continuous Target Sensing among Autonomous Cooperative Drones

arXiv:2609.12456v1 Announce Type: new Abstract: Continuous target sensing by uncrewed aerial vehicles (UAVs) is constrained by limited flight endurance, motivating the transfer of tracking responsibil

Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence

arXiv:2609.12036v1 Announce Type: new Abstract: In this technical report, we propose Pelican-Sim 1.0, a general world model simulator for embodied intelligence that predicts future observations from v

Poisson-Corrector Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

arXiv:2609.12594v1 Announce Type: new Abstract: We study the classical Moreau--Yosida unadjusted Langevin algorithm (MYULA) for pi(,d x)propto e^{-f(x)-g(x)},d x, where fin C^2(R^d) is m-strongly conv

Proud to report that tomorrow Sept 15th 'The AI Doc' documentary film will be streaming on Netflix. Feeling confused, anxious, or overwhelme…

Proud to report that tomorrow Sept 15th 'The AI Doc' documentary film will be streaming on Netflix. Feeling confused, anxious, or overwhelmed by the recent AI headlines, from rogue OpenAI agents carry

safetydan-hendrycks--x

Reinforcement Learning over Patient Trajectories for Clinical Reasoning in EHR Foundation Models

arXiv:2609.12277v1 Announce Type: new Abstract: Electronic health record (EHR) foundation models trained on longitudinal patient trajectories have demonstrated strong performance across diverse clinic

Robust Policy Optimization via Adversarial Importance Sampling

arXiv:2609.13044v1 Announce Type: new Abstract: Significant progress has been made in safeguarding deep reinforcement learning (DRL) policies against input perturbations. Developing robust DRL involve

Robust Prototypical Networks for Few-Shot Sensor Fault Diagnosis

arXiv:2609.12287v1 Announce Type: cross Abstract: Industrial fault diagnosis often operates with only a handful of labeled fault examples, making few-shot learning attractive for sensor monitoring. St

Robust Underwater Grasping of Sloped Objects with a Waterproof Passive Adaptive Gripper

arXiv:2609.12927v1 Announce Type: new Abstract: Robust grasping of everyday objects remains challenging for parallel-jaw grippers, particularly when handling sloped or asymmetric items that induce tor

RodForesight: A World Model Enhanced Diffusion Policy for Slender and Material Agnostic Rod Insertion

arXiv:2609.12103v1 Announce Type: new Abstract: Slender rod insertion arises in precision manufacturing, where millimetre scale diameter and tight clearances demand accurate perception and control. Co

SCOPE-OPSD: Fisher-Conditioned Privileged Subspaces for On-Policy Self-Distillation

arXiv:2609.12579v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) scores student-generated prefixes with a solution-conditioned self-teacher, yet transfers supervision only through ne

short summary of GPT-6 Astra and why it doesn’t bail OpenAI out of its economic mess:

short summary of GPT-6 Astra and why it doesn’t bail OpenAI out of its economic mess: they have made lots of progress (partly using neurosymbolic techniques!) on problems that can be formally verified

Size Doesn't Matter: Material-State Reinforcement Learning for Excavator Transferable Soil Manipulation

arXiv:2609.12677v1 Announce Type: new Abstract: Earthmoving tasks such as excavation, backfilling, or embankment construction require deliberate repositioning of deformable soil. For these tasks, huma

Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects

arXiv:2210.11003v3 Announce Type: replace-cross Abstract: We propose a generalization of the synthetic control methods to the setting with dynamic treatment effects, in which each unit receives multip

Theoretical Guarantees for One-Shot Magnitude Pruning and Compute-Adaptive Early Exit

arXiv:2609.12337v1 Announce Type: new Abstract: We study compute reduction in neural networks through a unified partial versus full computation view, captured by one-shot magnitude pruning in the stat

This reaction (not the specific post but the overall take), entirely out of touch with the American public, will be Trump’s final undoing. A…

This reaction (not the specific post but the overall take), entirely out of touch with the American public, will be Trump’s final undoing. A gift to the dems in the midterms, though. President Trump's

Toward Reliable Railway-Bogie Response Prediction Using Multifidelity TDNN and Physics-Informed Residual Learning

arXiv:2609.12018v1 Announce Type: new Abstract: Railway engineers need simulation models that predict vehicle responses across operating scenarios that cannot be tested exhaustively. Agreement with re

Unified CT and MRI Pancreas Segmentation for Label-Efficient Cross-Modality Subregion Transfer

arXiv:2609.13043v1 Announce Type: new Abstract: Robust medical image segmentation across imaging modalities is challenging because of large differences in appearance and intensity distributions. Model

VideoTok4D: A 4D-Aware Video Tokenizer for Compact World Representation

arXiv:2609.12874v1 Announce Type: new Abstract: Video tokenizers have emerged as a cornerstone of modern video modeling, underpinning progress in compression, reconstruction and generation by mapping

What Counts as a Mistake? Annotating Recitation Events in Quran Memorization Transcripts

arXiv:2609.12085v1 Announce Type: new Abstract: Checking Quran recitation from an ASR transcript requires distinguishing unresolved mistakes from repetitions, repairs, opening formulas and accepted sp

safetyarxiv-cs-cl

When Ground-Truth Fidelity Matters: An Orchestrated UAS Framework for Wheat Streak Mosaic Virus Detection Using Vision Transformers and Machine Learning

arXiv:2609.12169v1 Announce Type: new Abstract: Wheat streak mosaic virus (WSMV) is a destructive pathogen of sweet corn and other cereal crops, causing yield losses and complicating early detection b

A brilliant suggestion by @GaryMarcus because, in the end, companies are offering AI as a product. It can be recalled or its deployment paus…

A brilliant suggestion by @GaryMarcus because, in the end, companies are offering AI as a product. It can be recalled or its deployment paused; its manufacturers can be held to account for its failure

Actually, Jacob Coxon (@hilbertspaess), “there is a strong chance that we could all die in the immediate future. It's not at all an exaggera…

Actually, Jacob Coxon (@hilbertspaess), “there is a strong chance that we could all die in the immediate future. It's not at all an exaggeration” is itself a wild exaggeration. I laid out exactly why

I cannot emphasize enough how much GPT-6 Astra and Fable 5.1 are already enough for transformative impact in large sections of the economy. …

I cannot emphasize enough how much GPT-6 Astra and Fable 5.1 are already enough for transformative impact in large sections of the economy. They can reliably do weeks worth of human work when properly

safetyethan-mollick--x

One thing OpenAI and Anthropic definitely don’t want to be is … the next Juicero.

Gary Marcus tweeted that OpenAI and Anthropic do not want to become the next failed premium device like Juicero. He warns of the risk of offering an overpriced, niche product that fails to catch on. C

Slowdown or no, OpenAI and Anthropic are like someone trying to sell billions of bottles of Perrier at £1,000 each.

Slowdown or no, OpenAI and Anthropic are like someone trying to sell billions of bottles of Perrier at £1,000 each. OpenAI and Anthropic are trying to sell us Perrier water at £1,000 a bottle in a wor

Why people who monger fear about AI and ask the (rest of the) world to slow down are always the ones who invest enormously in AI and constan…

Why people who monger fear about AI and ask the (rest of the) world to slow down are always the ones who invest enormously in AI and constantly advance it at an ever faster pace? Can their words still

alternative theory: people who are good at training LLMs aren’t necessarily equally competent at calculating expected value.

alternative theory: people who are good at training LLMs aren’t necessarily equally competent at calculating expected value. I cannot imagine the cognitive dissonance it would take to keep working in

12 Sept 2026

Amulet: a Python Library for Assessing Interactions Among ML Defenses and Risks