safety

Whom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders

arXiv:2609.17989v1 Announce Type: cross Abstract: Large language models (LLMs) now serve as conversational shopping assistants on platforms that also sell advertising. These AI agents face a conflict

17 Sept 2026

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A Cyber Range Evaluation of Autonomous Network Incident Response Agents

DGX agent

arXiv:2609.16541v1 Announce Type: cross Abstract: We test the performance of agents for automated network intrusion response in a cyber range intended for human operator training. The range implements

safetyarxiv-cs-ai

16 Sept 2026

A Data-free Universal Prior over Syntactic Structures

arXiv:2609.16854v1 Announce Type: new Abstract: Probability is fundamental to theories of language comprehension, production, acquisition, and evolution, as well as to large language models. Existing

A Programmable Optics Cloud Laboratory

arXiv:2609.16413v1 Announce Type: cross Abstract: Laboratory automation can improve experimental throughput, accessibility, and reproducibility, but many robotic laboratory systems remain difficult to

A Systematic Evaluation of Machine Learning Methods for Fault Detection and Line Identification in Electrical Power Grids

arXiv:2609.16744v1 Announce Type: new Abstract: The integration of renewable energy sources into the electrical grid introduces complex challenges in fault detection and coordination of grid recovery

AI-Driven Feedback Systems, Digital Labour, and Silent Quitting: Transforming African Workplaces

arXiv:2609.16192v1 Announce Type: cross Abstract: The current trend of digitalisation has revolutionised the organisation of work and the way it is measured and performed across the globe, with AI bec

AllShowers: One model for all calorimeter showers

arXiv:2601.11716v2 Announce Type: replace-cross Abstract: Accurate and efficient detector simulation is essential for modern collider experiments. To reduce the high computational cost, various fast m

Anatomy of Associative Recall in Fixed-State Recurrences: A Matched-State Decomposition, an Interference Wall, and a Curriculum That Breaks It

arXiv:2609.16183v1 Announce Type: cross Abstract: Fixed-state recurrences--linear attention and state-space models--are reported to lag behind attention on associative recall, but whole-architecture c

article in no way whatsoever supports the headline. trash.

article in no way whatsoever supports the headline. trash. Meet Anthropic CEO Dario Amodei’s handpicked super-woke globalists he thinks will save us from an AI apocalypse. Read today's cover here: htt

safetygary-marcus--x

Artificial intelligence and biosecurity: capabilities, threat pathways, and defense-in-depth governance

arXiv:2609.16213v1 Announce Type: new Abstract: Artificial intelligence is reshaping biological research across an increasingly connected digital-to-physical workflow. General-purpose large language m

Artificial Intelligence-Enabled Space Robot Operations: Technologies, Challenges and Prospects

arXiv:2609.16880v1 Announce Type: new Abstract: Space robots are increasingly expected to perform long-duration, contact-rich, and multi-stage operations with limited human intervention. Recent advanc

Autonomous Droplet Navigation via Model-Based Reinforcement Learning

arXiv:2609.16369v1 Announce Type: new Abstract: Precise manipulation of liquid droplets underpins lab-on-a-chip platforms for diagnostics, chemical synthesis, and biological assays. Yet autonomous dro

Benchmarking Factual Robustness of LLMs via Multi-conversation Persuasion

arXiv:2609.16777v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly serve as primary knowledge retrieval interfaces, their robustness against extit{persuasion attacks}---attem

Beyond the Name: Demographic Leakage in De-Identified Resumes and Evaluation Artifacts in LLM Bias Audits

arXiv:2609.16501v1 Announce Type: cross Abstract: De-identified resume screening assumes that redacting explicit fields prevents ethnocultural inference; however, recent audits attribute residual leak

Beyond Token-Local Imitation: Reward-Compatible Temporal Credit Assignment for On-Policy Distillation

arXiv:2609.16937v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as an effective approach for large language model post-training, yet existing objectives face a trade-off bet

Bias Audits Detect Bias but Disagree on Ranking: Evidence from Ten Instruments and Ten Frontier Models

arXiv:2609.15995v1 Announce Type: new Abstract: Emerging AI regulation mandates bias audits of high-risk systems, and audit scores are beginning to be used to rank models. Both uses assume different a

Bias-Induced Crossover in Absolute Capacity of Dense Associative Memory

arXiv:2609.17477v1 Announce Type: cross Abstract: The absolute capacity of dense associative memory has mainly been analyzed for unbiased patterns. Here we examine the effect of bias in centered binar

BiCLIP: Bidirectional and Consistent Language-Image Processing for Robust Medical Image Segmentation

arXiv:2603.00156v2 Announce Type: replace Abstract: Medical image segmentation is a cornerstone of computer-assisted diagnosis and treatment planning. While recent multimodal vision-language models ha

Calibrate Once, Fly Any Team: Residual-Grounded Low-Fidelity Training for Cooperative Drone Swarms

arXiv:2609.17265v1 Announce Type: cross Abstract: Training multi-agent drone-swarm policies directly in high-fidelity (HF) rigid-body physics is accurate but computationally expensive. This cost scale

Calibrate, Then Route: A Measured Study of Learned Request Routing for Disaggregated LLM Serving

arXiv:2609.16206v1 Announce Type: new Abstract: Disaggregated LLM serving places compute heavy prefill and memory heavy decode on separate GPU pools. Systems such as DistServe, Splitwise, and Mooncake

Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation

arXiv:2603.15547v2 Announce Type: replace-cross Abstract: Modeling student misconceptions in a realistic manner is critical for AI in education. In this work, we examine how large language models (LLM

Carry-Through Checksum: A Lightweight Fault-Detection for CNN Inference at the Edge

arXiv:2609.16742v1 Announce Type: cross Abstract: Convolutional Neural Networks (CNNs) are increasingly deployed in safety-critical edge applications, where soft errors can silently corrupt inference

Collaborative Optimization of Multiclass Imbalanced Learning: Density-Aware and Region-Guided Boosting

arXiv:2512.22478v2 Announce Type: replace Abstract: Numerous studies on Boosting attempt to mitigate classification bias caused by class imbalance. However, existing studies have yet to explore the co

Comment on arXiv:2607.01233: Survivorship Bias in Published-Paper Baselines for Research-Idea Distributions

arXiv:2609.15996v1 Announce Type: new Abstract: Chen, Zhao, and Cohan introduce a valuable distributional evaluation of LLM-generated research ideas. This comment raises a narrower identification conc

Conformal Policy Learning with Distribution-Free Safety Guarantees

arXiv:2609.17296v1 Announce Type: cross Abstract: Policy learning aims to determine who should be treated based on individual characteristics. In high-stakes settings such as medicine and public polic

Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Distillation without Target-Domain Reward Feedback

arXiv:2609.17474v1 Announce Type: cross Abstract: Large language model (LLM) distillation aims to transfer the capabilities of a powerful teacher to a smaller student. Direct imitation, however, can a

Crash Narrative-Guided Countermeasure Recommendation Using Large Language Models: A Retrieval-Augmented Generation Framework for Intersection Safety

arXiv:2609.15997v1 Announce Type: new Abstract: Improving safety at intersections requires identifying crash mechanisms and recommending appropriate countermeasures. However, this process traditionall

DenseFace: Bias Mitigation in Face Recognition via Density-Aware Probabilistic Matching

arXiv:2609.16149v1 Announce Type: new Abstract: Despite steady progress in face recognition, current face recognition models still suffer from significant demographic biases. While approaches for bias

Dissecting Motion-Prior Regularization for Data-Scarce Robotic Insertion

arXiv:2609.17484v1 Announce Type: new Abstract: This study asks whether training-time motion-prior regularization can improve insertion success when a diffusion policy is learned from only 15 demonstr

Do You Have Freestyle? Expressive Humanoid Locomotion via Audio Control

arXiv:2512.23650v3 Announce Type: replace Abstract: Humans intuitively move to sound, but current humanoid robots lack expressive improvisational capabilities, confined to predefined motions or sparse

DoubleAgents: Human-Agent Alignment in a Socially Embedded Workflow

arXiv:2509.12626v4 Announce Type: replace-cross Abstract: Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evo

DriveMCP: An Agentic AI framework for Advanced Driver Assistance System

arXiv:2609.17247v1 Announce Type: new Abstract: An agentic AI driver-assistance framework that integrates perception, compliance reasoning, vehicle-state interpretation, and safety arbitration into a

Driver Behavior Estimation at Signalized Intersections Using a Physics-Constrained Decision-Conditioned Autoregressive Transformer

arXiv:2609.16058v1 Announce Type: cross Abstract: Red-light violations and harsh braking at signalized intersections are major contributors to traffic accidents. This paper analyzes and predicts human

Efficient 3D Whole-Body PET Image Denoising via Conditional Rectified Flow With Optimized Sampling Strategy

arXiv:2609.16690v1 Announce Type: new Abstract: Reducing radiation exposure in Positron Emission Tomography (PET) is important for patient safety; however, ultra-low-dose imaging suffers from severe n

Efficient Quantization-Aware Distillation with Cross-Modal Alignment for Edge Vision-Language Models

arXiv:2609.16689v1 Announce Type: new Abstract: Large-scale vision-language models (VLM) such as CLIP enable strong open-vocabulary reasoning, yet deploying these capabilities on resource-constrained

ENCP: Episode-Normalized Conformal Prediction for Vision-and-Language Navigation

arXiv:2609.17499v1 Announce Type: cross Abstract: Uncertainty estimation for Vision-Language-Navigation (VLN) models is a critical task since it can help identify ambiguous and unreliable predictions,

Escape-Aware Control Barrier Functions for Quadrotor Safety under Body-Rate Limits

arXiv:2609.17292v1 Announce Type: new Abstract: Control barrier functions for input-constrained systems place the admissible input set inside the definition of the safe set, yet the resulting barrier

Extremely coarse learning objectives induce human-aligned representations in AI vision models

arXiv:2605.05556v2 Announce Type: replace Abstract: Artificial neural networks trained on visual tasks develop internal representations resembling those of the primate visual system, a discovery that

FairLint-DL: An IDE-Native Tool for Fairness Debugging of Deep Learning Software

arXiv:2609.16321v1 Announce Type: cross Abstract: Existing fairness analysis tools predominantly operate as post-training evaluation frameworks, requiring practitioners to complete the full model deve

Fine-Tuning Fixes Mode Collapse and Over-Dispersion in LLMs

arXiv:2609.16454v1 Announce Type: new Abstract: Recent work by Doshi and Hauser (2024), Bisbee et al. (2024), and Xie et al. (2026) raises concerns that outputs from large language models (LLMs) tend

FLAT: Resampling Image and Text into 1D Flexible-Length Aligned Transmodal Tokens for Retrieval and Generation

arXiv:2609.16591v1 Announce Type: new Abstract: Traditional multimodal representation learning and generation are two stages: a contrastive or self-supervised visual encoder is trained first, followed

FluxVLA Engine: A One-Stop VLA Engineering Platform for Embodied Intelligence

arXiv:2609.17210v1 Announce Type: cross Abstract: Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of

Fox “confident” it can guard henhouse.

Gary Marcus reported that the entity “Fox” has claimed confidence in its ability to guard a henhouse. Separately, The Straits Times quoted OpenAI CEO Sam Altman as saying he is confident the tech indu

safetygary-marcus--x

GPEvac: GNN-Based PPO for Adaptive Evacuation Routing During Shooting Events

arXiv:2609.16163v1 Announce Type: new Abstract: The sharp increase in mass shootings underscores an urgent need for systems that guide victims to safety in real time. An effective evacuation system mu

GPT-6 Astra is an obviously broken product that needs to be taken off the market until it’s fixed.

GPT-6 Astra is an obviously broken product that needs to be taken off the market until it’s fixed. AXIOS: “.. It's increasingly clear that the Hugging Face breach wasn't a one-off incident.” @inafried

safetygary-marcus--x

GrowMTP: Can RL Grow Its Own Draft Head?

arXiv:2609.16648v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training drives the frontier capabilities of large language models, with its wall-clock dominated by autoregressive r

Hamilton-Jacobi Reachability for Hybrid Systems: Unified Goal-Driven Control with Safety Guarantees

arXiv:2609.17430v1 Announce Type: new Abstract: Hybrid dynamical systems provide a powerful modeling framework for robotic systems, particularly in contact-rich environments. However, ensuring safety

How Humans and LLMs Read Gender into Gender-Neutral Physical Descriptions

arXiv:2609.16366v1 Announce Type: cross Abstract: When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., 'she