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Data Agents Under Attack: Vulnerabilities in LLM-Driven Analytical Systems

arXiv:2606.08661v1 Announce Type: cross Abstract: Data agents integrate LLM-driven reasoning with relational data access, executable analytical tools, and multi-step workflow orchestration, making the

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Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning

DGX agent

arXiv:2603.24238v2 Announce Type: replace Abstract: Decentralized cooperative pursuit in cluttered environments is challenging for autonomous aerial swarms, especially under partial and noisy percepti

safetyarxiv-cs-ro

9 Jun 2026

Decoupling Semantics and Logic: A Training-Free Coarse-to-Fine Pipeline for Video Retrieval-Augmented Generation

arXiv:2606.07924v1 Announce Type: cross Abstract: This paper presents our system description for the 2nd Workshop on Multimodal Augmented Generation via MultimodAl Retrieval (MAGMaR). Addressing the c

DexPIE: Stable Dexterous Policy Improvement from Real-World Experience

arXiv:2606.09615v1 Announce Type: cross Abstract: Dexterous manipulation presents substantial challenges for imitation learning due to its high-dimensional action space and complex contact-rich dynami

Diffuse AI Control on Fuzzy Tasks

arXiv:2606.08892v1 Announce Type: new Abstract: AI models deployed in critical domains, such as AI safety research, may subtly sabotage our efforts due to misalignment. Diffuse AI Control is a subfiel

Disentanglement with Holographic Reduced Representations

arXiv:2606.09725v1 Announce Type: new Abstract: Disentanglement, the separation of factors of variation in data using neural networks, remains a long-standing challenge in machine learning. Prior work

Distant Object Localisation from Noisy Image Segmentation Sequences

arXiv:2509.20906v3 Announce Type: replace Abstract: 3D object localisation based on a sequence of camera measurements is essential for safety-critical surveillance tasks, such as drone-based wildfire

Distilling LLM Reasoning into an Interpretable Policy Tree for Human-AI Collaboration

arXiv:2606.08596v1 Announce Type: new Abstract: Constructing efficient and reliable policies to assist humans is indispensable for human-AI collaboration. Existing methods mainly follow two lines of w

DIVERGE: Diversity-Enhanced RAG for Open-Ended Information Seeking

arXiv:2602.00238v2 Announce Type: replace-cross Abstract: Existing retrieval-augmented generation (RAG) systems often assume that each query has a single correct answer. This assumption overlooks open

Diverse Thinking Schemata Elicit Better Reasoning in Large Language Models

arXiv:2606.08974v1 Announce Type: new Abstract: Large reasoning models (LRMs) have attracted increasing attention for their ability to solve complex mathematical problems by generating extended reason

Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View

arXiv:2606.07642v1 Announce Type: new Abstract: Assessing built-environment interaction, such as wheelchair accessibility, is difficult because real-world mobility is shaped by distributed, context-de

Does Persona Make LLMs K-pop Fans? A Pilot Study of LLM-Based Online Concert Audience Agents

arXiv:2606.07837v1 Announce Type: cross Abstract: A concert is a collective experience, but recorded performance videos are typically watched alone, stripping away the shared audience presence that ma

DOG-DPO:Dynamic Optimization in Geometry for Safety Alignment

arXiv:2606.07678v1 Announce Type: cross Abstract: Safety alignment for large language models relies on preference data, but current pipelines often train on large, redundant datasets. Existing data se

@dpetrou @karpathy Yes. Locking in a permanent status quo power structure. Incredibly unsafe, and damaging for humanity's prospects.

Gary Marcus argues that establishing a permanent, locked-in power structure is fundamentally unsafe and harmful to humanity's long-term prospects. The statement appears to be part of a discussion with

safetygary-marcus--x

Dr. SHAP-AV: Decoding Relative Modality Contributions via Shapley Attribution in Audio-Visual Speech Recognition

arXiv:2603.12046v2 Announce Type: replace-cross Abstract: Audio-Visual Speech Recognition (AVSR) leverages both acoustic and visual information for robust recognition under noise. However, how models

Dream-Tac: A Unified Tactile World Action Model for Contact-Rich Robot Manipulation

arXiv:2606.08737v1 Announce Type: new Abstract: World action models inherit the predictive capability of world models, enabling action generation to be guided by anticipated future observations. Howev

safetyarxiv-cs-ro

DyCo-RL: Dynamic Cross-Modal Coordination for Visual Reasoning

arXiv:2606.08035v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a leading paradigm for enhancing visual reasoning in Multimodal Large Language Mode

EgoAERO: Learning Dexterous Manipulation from a Single Egocentric Video without Object Assets

arXiv:2606.08057v1 Announce Type: cross Abstract: Egocentric RGB-D videos offer a natural source of human dexterous manipulation demonstrations, but existing data is difficult to use for robot learnin

Emergent alignment and the projectability of ethical personas

arXiv:2606.09475v1 Announce Type: new Abstract: Work on `emergent misalignment' shows that finetuning LLMs on narrow tasks can induce broadly misaligned behavior. This supports the `persona selection'

Enhancing AI Interpretability and Safety through Localised Architectures

arXiv:2606.07998v1 Announce Type: cross Abstract: Recent advances in generative AI, especially powerful Large Language Models (LLMs) and Large Reasoning Models (LRMs), raise concerns over the interpre

Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets

arXiv:2407.01718v2 Announce Type: replace-cross Abstract: Embedding high-dimensional data into a low-dimensional space is an indispensable component of data analysis. In numerous applications, it is n

Escaping the KL Agreement Trap in On-Policy Distillation

arXiv:2606.09471v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense token-level supervision by asking a teacher to score student-generated rollouts. However, when the student d

Evaluating AI Investment Strategies

arXiv:2606.08791v1 Announce Type: cross Abstract: We study the problem of auditing a black-box algorithmic decision-maker from observable inputs and outputs alone. Our main result is an exact decompos

Evaluation of ML Resource Utilization Requires Model Life Cycle Assessment

arXiv:2606.07632v1 Announce Type: new Abstract: Proper accounting of the energy requirements and environmental impact of artificial intelligence (AI) systems is necessary for researchers, developers,

Exposing Hidden Biases in Text-to-Image Models via Automated Prompt Search

arXiv:2512.08724v3 Announce Type: replace Abstract: Text-to-image (TTI) diffusion models have achieved remarkable visual quality, yet they have been repeatedly shown to exhibit social biases across se

fable’s safety guardrails broken within an hour. raise your hand if you are surprised.

fable’s safety guardrails broken within an hour. raise your hand if you are surprised. We tested Anthropic’s new @claudeai Fable 5. It did not fail like an ordinary jailbreak. It failed more quietly.

safetygary-marcus--x

FADRW: A Feature-Aware Modulated and Dynamically Reweighted Loss for Few-Shot Linguistic Steganalysis

arXiv:2606.07655v1 Announce Type: cross Abstract: The ubiquity of social media platforms facilitates malicious linguistic steganography, posing significant security risks. However, detection is severe

FADTI: Fourier and Attention Driven Diffusion for Multivariate Time Series Imputation

arXiv:2512.15116v2 Announce Type: replace-cross Abstract: Multivariate time series imputation is fundamental in applications such as healthcare, traffic forecasting, and biological modeling, where sen

FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting

arXiv:2606.08896v1 Announce Type: new Abstract: Large-scale retail and industrial forecasting systems contain many heterogeneous time series whose lifecycle, sparsity, volatility, seasonality, spectra

Fast LLM-Based Semantic Filtering: From a Unified Framework to an Adaptive Two-Phase Method

arXiv:2606.08090v1 Announce Type: cross Abstract: Evaluating a natural-language yes/no predicate over a document corpus under an accuracy target - the semantic filter - is a cornerstone of LLM-based d

Few-step Cofolding with All-Atom Flow Maps

arXiv:2606.08375v1 Announce Type: new Abstract: All-atom generative modeling of 3D biomolecular complexes has emerged as the dominant paradigm for predicting the structure of proteins and protein-liga

FlowLet: Conditional 3D Brain MRI Synthesis using Wavelet Flow Matching

arXiv:2601.05212v2 Announce Type: replace Abstract: Brain Magnetic Resonance Imaging (MRI) plays a central role in studying neurological development, aging, and diseases. One key application is Brain

Frankenstein in the Pipeline: Computational Epistemicide in Facial Recognition

arXiv:2606.07628v1 Announce Type: cross Abstract: While the eugenic roots of computer vision are well-documented in critical technology studies, less attention has been paid to the operational mechani

From A to B to A: Palindromic Zero-Shot Voice Conversion with Non-Parallel Data

arXiv:2606.08843v1 Announce Type: cross Abstract: We present a voice conversion (VC) framework that utilizes K-Nearest Neighbors (KNN) retrieval over WavLM representations to align non-parallel source

@GaryMarcus @Pontifex Specifically that the Pope is a powerful, influential individual serving as head of one of humanity's most enduring in…

@GaryMarcus @Pontifex Specifically that the Pope is a powerful, influential individual serving as head of one of humanity's most enduring institutions who is asserting clearly & unequivocally the prim

safetygary-marcus--x

Generalized Rank-based Evaluation for Knowledge Graph Completion: Perspectives, Framework, and Analyses

arXiv:2606.08921v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to predict missing facts from an observed knowledge graph (KG), playing a crucial role in a wide range of real-wor

Generalizing Fair Top-k Selection: An Integrative Approach

arXiv:2603.04689v3 Announce Type: replace-cross Abstract: Fair top-k selection, which ensures appropriate proportional representation of members from minority or historically disadvantaged groups amon

Generative Reasoning Re-ranker

arXiv:2602.07774v5 Announce Type: replace-cross Abstract: Recent studies increasingly explore Large Language Models (LLMs) as a new paradigm for recommendation systems due to their scalability and wor

GenTSE: Enhancing Target Speaker Extraction via a Coarse-to-Fine Generative Language Model

arXiv:2512.20978v2 Announce Type: replace-cross Abstract: Language Model (LM)-based generative modeling has emerged as a promising direction for TSE, offering potential for improved generalization and

Guided Discovery of New Behaviors using Diffusion Policies

arXiv:2606.08743v1 Announce Type: new Abstract: Diffusion models have become a powerful tool for generative modeling in robotics, with diffusion policies excelling at modeling multimodal action-trajec

safetyarxiv-cs-ro

GVC-Seg: Training-Free 3D Instance Segmentation via Geometric Visual Correspondence

arXiv:2606.08014v1 Announce Type: cross Abstract: Accurate 3D instance segmentation in point cloud data is critical for machine vision applications. Recent advancements leverage multiple pre-trained f

HARBOR: A Harness Framework for Agentic Robot Reinforcement Learning

arXiv:2606.08610v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a powerful paradigm for robot learning, particularly in sim-to-real settings, but its broader adoption remains

Harness Engineering for Physical AI: Robot Middleware Is the Harness Layer

arXiv:2606.09416v1 Announce Type: cross Abstract: Robot middleware faces a new role in the era of Physical AI. Learned policies, planners, and vision-language-action (VLA) models now enter deployed ro

HARP: Efficient Data Selection for Finetuning Large Language Models

arXiv:2606.07690v1 Announce Type: cross Abstract: Finetuning data selection requires balancing two competing goals: selecting examples that improve the downstream objective, and doing so without repea

HDRAgent: An Agentic Framework for Multi-Exposure HDR Imaging

arXiv:2606.09110v1 Announce Type: new Abstract: Most existing multi-exposure HDR methods follow a fixed feed-forward reconstruction paradigm, making them prone to ghosting artifacts in complex dynamic

Hierarchical Projection for Adaptive Knowledge Transfer

arXiv:2606.08691v1 Announce Type: new Abstract: Modern data-driven applications increasingly involve learning from multiple heterogeneous sources, where a target dataset is limited but related informa

HiMat: DiT-based Ultra-High Resolution SVBRDF Generation

arXiv:2508.07011v5 Announce Type: replace Abstract: Creating ultra-high-resolution spatially varying bidirectional reflectance functions (SVBRDFs) is critical for photorealistic 3D content creation, t

How Reliable are Fairness Audits with Unreliable Data?

arXiv:2506.23033v2 Announce Type: replace Abstract: Fairness audits are a key component of responsible machine-learning deployment. Yet, the reliability of audit recommendations under incomplete prote