Search: “safety”

TopoSurfel: Closing the Loop between Gaussian Surfels and Meshes for Surface Reconstruction

arXiv:2608.20687v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in novel view synthesis. However, extracting high-fidelity surfaces directly from 3DGS remains cha

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Safety

Trojaning the Alignment: Stealthy Backdoor Attacks against Graph Foundation Models

DGX agent

arXiv:2608.20991v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) on text-attributed graphs (TAGs) align graph representations with language semantics to support transferable graph learni

safetyarxiv-cs-lg

24 Aug 2026

ViTacPhys: Physical Property-Aware Grasping from Human Visual-Tactile Demonstrations

arXiv:2608.21355v1 Announce Type: new Abstract: Recent vision-based action models have demonstrated strong capabilities in complex manipulation, but they rarely leverage explicit object physical prope

Volumetric Radiology AI in the Era of Multimodal Large Language Models

arXiv:2608.20549v1 Announce Type: new Abstract: Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward

Who Do Language Models Think Is Competent? A Mechanistic Analysis of Occupational Bias

arXiv:2608.20347v1 Announce Type: cross Abstract: Language models (LMs) often pass behavioral bias evaluations, but it remains unclear whether they no longer represent the underlying associations that

Why2Speak: Faithful Reasoning for Abstaining Action Policies

arXiv:2608.20670v1 Announce Type: new Abstract: Many agentic systems must repeatedly choose between acting and abstaining, making faithful reasoning important for oversight: an explanation is useful o

and yet they expect $2T

Gary Marcus recently posted on Twitter questioning why investors still expect a $2 trillion valuation for AI‑related companies, despite broader market skepticism. The Financial Times has reported that

23 Aug 2026

this would be more credible if Sam had left OpenAI when the board fired him.

this would be more credible if Sam had left OpenAI when the board fired him. 🚨 Sam Altman fires shots at Anthropic >“ai becomes too powerful we can’t control it” >“power gets too centralized… one comp

23 Aug 2026

If the AI comes for us, maybe we can all hide in Venecky.

Gary Marcus notes that multimodal large‑language models are likely to struggle with map interpretation. In a tongue‑in‑cheek post he suggests that by 2026—if AI poses a threat—people could seek refuge

22 Aug 2026

Me, 2023, 2024, 2025…. Multimodal LLMs are going to have problems with maps. 2026: It’s ok, you live in Venecky. Not far Tounesseo.

Me, 2023, 2024, 2025…. Multimodal LLMs are going to have problems with maps. 2026: It’s ok, you live in Venecky. Not far Tounesseo. @GaryMarcus It keeps getting crazier “Mom, did you know that we live

22 Aug 2026

The evaluation resolution has been shown to have a significant impact on the identification of the 'learning rule' that exhibits the most brain-like characteristics at V1. [R]

The preprint can be accessed via the following link: https://arxiv.org/abs/2608.12408 (q-bio.NC / cs.LG). And for the code: https://github.com/nilsleut/evaluation-resolution-rsa The following assertio

safetyr-machinelearning

22 Aug 2026

Active Spiking Perception: The Membrane Potential as a Belief State for Anytime 3D Point Cloud Recognition

arXiv:2608.19232v1 Announce Type: cross Abstract: Spiking point cloud networks usually scan space in a fixed, input-agnostic order, which leaves the most distinctive resource of spiking computation, t

APPROVE: Visual End-User-in-the-Loop Robot Programming with LLMs

arXiv:2608.19281v1 Announce Type: new Abstract: Programming robots remains challenging for non-experts, as traditional methods require expert knowledge and even block-based interfaces often lack flexi

Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity

arXiv:2103.04021v4 Announce Type: replace-cross Abstract: In the standard data analysis framework, data is collected (once and for all), and then data analysis is carried out. However, with the advanc

Auditing Cross-Lingual Fairness in Language Model Watermarking

arXiv:2608.20047v1 Announce Type: new Abstract: Watermarking schemes for large language model output are evaluated almost exclusively on English text using each scheme's detection threshold and a narr

Beyond Imitation: Filtering On-Policy Distillation by Reasoning Progress

arXiv:2608.19408v1 Announce Type: new Abstract: On-policy distillation (OPD) has emerged as an effective framework for post-training language models by pairing student-generated trajectories with dens

Beyond Memory Majority: Latent-Source Reasoning for Multi-Agent Memory Arbitration

arXiv:2608.19701v1 Announce Type: new Abstract: Long-term multi-agent systems continuously accumulate the memories produced by different agents. Existing memory methods typically treat retrieved memor

Beyond Multimodal Alignment: Certifying Physical Language through Response Substitution and Ordered Execution

arXiv:2608.19492v1 Announce Type: new Abstract: World models increasingly treat compact multimodal representations as interfaces between perception and physical interaction, yet existing probes do not

Model Releases

CADRE: Stable, Parameter Efficient Adaptation of Medical Vision Language Models with Bounded Forgetting and Prior Drift

model-releasesarxiv-cs-ai

arXiv:2606.23487v2 Announce Type: replace Abstract: Medical vision-language models (VLMs) such as BiomedCLIP generalize broadly, but adapting them to a clinical service is as much a safety problem as

Can Conversational AI loosen Us-Versus-Them Boundaries? The Effects of Common, Dual, and Separate Identity Framings on Pro-Immigrant Intergroup Helping

arXiv:2608.19220v1 Announce Type: cross Abstract: Rising immigration has intensified intergroup tensions in many countries. Traditional bias-reduction programs remain difficult to scale and increasing

CVSD-Reg: Cross-Modal Visual Semantic Prior Distillation for Robust LiDAR Registration

arXiv:2608.19536v1 Announce Type: cross Abstract: Learning-based global point cloud registration has achieved remarkable progress, yet its reliance on geometric representations makes existing methods

DIFFCZSL: Compositional Zero-Shot Learning Regularized by Diffusion Representations

arXiv:2608.19871v1 Announce Type: new Abstract: Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object compositions by leveraging knowledge of primitive concepts learned fro

Distilling Aggregate Mobility Statistics into a Language Model Policy for Post-Event Crowd Simulation

arXiv:2608.19778v1 Announce Type: cross Abstract: Pedestrian simulators need a behaviour rule for every agent, but privacy usually limits the data for setting one to aggregate statistics, namely zone-

Model Releases

DiverValue-Bench: A Benchmark and Fine-Tuning Framework for Aligning Large Language Models with Diverse Human Values

model-releasesarxiv-cs-ai

arXiv:2509.08022v3 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) with diverse human values is essential for safe and effective deployment, yet existing benchmarks often

Dynamic Gated Cross-Modal Fusion with Sarcastic-aware Contrastive Regularization for Multimodal Sarcasm Detection

arXiv:2608.19942v1 Announce Type: new Abstract: Multimodal sarcasm detection aims to identify sarcastic intent from multimodal content, where inconsistencies between literal meaning and contextual cue

Empirical Characterization of Learning Geometry in Hybrid Quantum Forecasting Models

arXiv:2608.19497v1 Announce Type: new Abstract: We characterize the learning dynamics of a compact hybrid quantum forecasting model through comparison with a structurally aligned classical baseline. U

EnvHarness: Awakening Static Worlds for Agent Learning

arXiv:2608.19880v1 Announce Type: new Abstract: LLM agents learn by interacting with environments, yet these environments are hand-built and static: blind to an agent's weaknesses, and quickly left be

EXIMO: VLM Guided Exploration of VLA Policies

arXiv:2608.19891v1 Announce Type: new Abstract: How to efficiently finetune robot policies to learn new tasks on the fly? State of the art robotic manipulation policies are based on behaviour cloning

Fairness-Aware Network Embeddings: Methods, Applications, and Challenges

arXiv:2608.19381v1 Announce Type: cross Abstract: Network embedding methods learn low-dimensional representations of graph-structured data to support downstream tasks such as node classification, link

FermatSyn: SAM2-Enhanced Bidirectional Mamba with Isotropic Spiral Scanning for Multi-Modal Medical Image Synthesis

arXiv:2505.07687v4 Announce Type: replace-cross Abstract: Multi-modal medical image synthesis is pivotal for alleviating clinical data scarcity, yet existing methods fail to reconcile global anatomica

Flow Matching-Based PET Image Reconstruction

arXiv:2608.20112v1 Announce Type: cross Abstract: Generative models have shown strong potential for positron emission tomography (PET) image reconstruction. Although diffusion model-based reconstructi

FMT^{X}: Lazy Wavefront Search for Dynamic Replanning

arXiv:2509.08521v2 Announce Type: replace-cross Abstract: FMT^{*} plans efficiently in static worlds by expanding a cost-ordered wavefront and collision-checking lazily, but its single-pass unvisited

Gen AI in Proof-based Math Courses: A Pilot Study

arXiv:2509.13570v2 Announce Type: replace Abstract: With the rapid rise of generative AI in higher education, understanding how students use AI is increasingly important. This exploratory study examin

Growth Without Us: Machine Consumers, Corporate Circularity, and the Decoupling of GDP from Humanity after AGI

arXiv:2608.20231v1 Announce Type: cross Abstract: The standard objection to full automation is demand-side: if humans earn nothing, who buys the output? This confuses an accounting role with a biologi

Hallucination as a Feature, not a Defect: Evaluating a multi-agent architecture to transform speculative language-model outputs into testable scientific hypotheses

arXiv:2608.19206v1 Announce Type: cross Abstract: Contemporary Large Language Models (LLMs) are increasingly aligned to suppress hallucinations, prioritizing factual retrieval over combinatorial creat

HARP: Hierarchical Adaptive Ranking with Preference-Adaptive Fusion for Query-Based CVE Prioritization

arXiv:2608.19430v1 Announce Type: cross Abstract: Vulnerability prioritization is inherently preference dependent, since the same CVE can receive different remediation priority under different operati

HBVLA: Pushing 1-Bit Post-Training Quantization for Vision-Language-Action Models

arXiv:2602.13710v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models enable instruction-following embodied control, but their large compute and memory footprints hinder deployment o

Hybrid Feedback Sampling for Sample-Efficient Model Predictive Control

arXiv:2608.19443v1 Announce Type: new Abstract: Thanks to its parallelizability and flexibility, sampling-based Model Predictive Control (MPC) has become widely popular for controlling real-world robo

Impressive research from Google on building better environments for agents. Training environments for agents are hand-built and go stale. Th…

Impressive research from Google on building better environments for agents. Training environments for agents are hand-built and go stale. The agent improves, the environment does not, and it's not abl

safetydair-ai--x

Learn for Variation: Efficient AAV Trajectory Learning through a Differentiable Wireless World Model

arXiv:2603.18853v3 Announce Type: replace-cross Abstract: Autonomous aerial vehicles (AAVs) enable data collection for sixth-generation Internet-of-Things networks, but their trajectories couple nonli

Learning Hierarchical Skill Policies with Offline Quality-Diversity Reinforcement Learning

arXiv:2608.19684v1 Announce Type: new Abstract: Recent studies investigate how to leverage pre-collected datasets to improve the policy performance and sample efficiency of RL. One promising approach

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

arXiv:2608.19977v1 Announce Type: new Abstract: Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating this behavior in quadrupedal robots ha

Learning how to Forget: Fine-tuning for Long-Context Sparse Attention

arXiv:2608.19920v1 Announce Type: new Abstract: A lot of prior work addressed key-value (KV) cache selection and compression by sparse attention to enable long-context inference for transformer langua

Learning the Right Abstraction: Neural Reduced Dynamics for Complex Robot Control

arXiv:2608.19375v1 Announce Type: new Abstract: High-fidelity embodied AI simulators provide realistic evaluation of complex robotic systems, but their computational cost limits their direct use for l

Learning Vision-Driven Reactive Soccer Skills for Humanoid Robots

arXiv:2511.03996v2 Announce Type: replace Abstract: Humanoid soccer poses a representative challenge for embodied intelligence, requiring robots to coordinate agile locomotion with unreliable visual p

Learning When to Think: Adaptive Reasoning for Test-Time Compute Allocation

arXiv:2608.20256v1 Announce Type: new Abstract: Reasoning language models trained with reinforcement learning typically operate under a fixed token budget rather than an explicitly adaptive one, which

Loreley: Repository-Scale Program Evolution with Quality-Diversity Search

arXiv:2608.19703v1 Announce Type: cross Abstract: Sequential agent search accumulates changes from its current champion but discards alternative branches; independent proposals preserve breadth but re

Merge Now, Regret Later: The Hidden Cost of Model Merging Is Adversarial Transferability

arXiv:2509.23689v2 Announce Type: replace Abstract: Model Merging (MM) has proven to be an effective alternative to multi-task learning, where several fine-tuned models are merged, without access to t