Search: “framework”

APIOT: Autonomous Vulnerability Management Across Bare-Metal Industrial OT Networks

arXiv:2605.02346v1 Announce Type: cross Abstract: Bare-metal operational technology (OT) devices -- especially the microcontrollers running Modbus/TCP and CoAP at the base of industrial control system

agentsarxiv-cs-ai

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Safety

Beyond Activation Alignment: The Geometry of Neural Sensitivity

DGX agent

arXiv:2605.03222v1 Announce Type: new Abstract: Activation-alignment measures such as Representational Similarity Analysis (RSA), Canonical Correlation Analysis (CCA), and Centered Kernel Alignment (C

safetyarxiv-cs-lg

6 May 2026

BifrostUMI: Bridging Robot-Free Demonstrations and Humanoid Whole-Body Manipulation

arXiv:2605.03452v1 Announce Type: new Abstract: High-quality data collection is a fundamental cornerstone for training humanoid whole-body visuomotor policies. Current data acquisition paradigms predo

safetyarxiv-cs-ro

Controllable and Verifiable Process Data Synthesis for Process Reward Models

arXiv:2605.02395v1 Announce Type: new Abstract: Process reward models (PRMs) rely on high-quality process supervision data, yet existing construction methods often provide limited control over error l

researcharxiv-cs-ai

CoVSpec: Efficient Device-Edge Co-Inference for Vision-Language Models via Speculative Decoding

arXiv:2605.02218v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong capabilities in multimodal perception and reasoning. However, deploying large VLMs on mobile devi

researcharxiv-cs-ai

DataEvolver: Let Your Data Build and Improve Itself via Goal-Driven Loop Agents

model-releasesarxiv-cs-ai

arXiv:2605.01789v1 Announce Type: new Abstract: Constructing controllable visual data is a major bottleneck for image editing and multimodal understanding. Useful supervision is rarely produced by a s

Disease Is a Spectral Perturbation

arXiv:2605.02949v1 Announce Type: new Abstract: We propose a novel method of understanding disease transformation from a healthy baseline with biomarker-level explainability. By modeling the biomarker

DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models

arXiv:2605.03877v1 Announce Type: new Abstract: Dataset distillation enables efficient training by distilling the information of large-scale datasets into significantly smaller synthetic datasets. Dif

safetyarxiv-cs-cv

Applications

Driving Style Recognition Like an Expert Using Semantic Privileged Information from Large Language Models

arXiv:2508.13881v2 Announce Type: replace Abstract: Existing driving style recognition systems largely depend on low-level sensor-derived features for training, neglecting the rich semantic reasoning

applicationsarxiv-cs-ro

Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response

arXiv:2510.12061v2 Announce Type: replace Abstract: Effective disaster response is essential for safeguarding lives and property. Existing statistical approaches often lack semantic context, generaliz

researcharxiv-cs-ai

Applications

Free Decompression with Algebraic Spectral Curves

arXiv:2605.03634v1 Announce Type: cross Abstract: Tools from random matrix theory have become central to deep learning theory, using spectral information to provide mechanisms for modeling generalizat

applicationsarxiv-cs-lg

FreeTimeGS++: Secrets of Dynamic Gaussian Splatting and Their Principles

arXiv:2605.03337v1 Announce Type: new Abstract: The recent surge in 4D Gaussian Splatting (4DGS) has achieved impressive dynamic scene reconstruction. While these methods demonstrate remarkable perfor

Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning

arXiv:2605.02913v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a central post-training tool for improving the reasoning abilities of large language models (LLMs). In these syst

agentsarxiv-cs-lg

Governing What the EU AI Act Excludes: Accountability for Autonomous AI Agents in Smart City Critical Infrastructure

arXiv:2605.01091v1 Announce Type: cross Abstract: When a traffic signal controller adjusts green phases and a grid manager curtails power on the same corridor, each system may comply with its own obli

Graph Convolutional Support Vector Regression for Robust Spatiotemporal Forecasting of Urban Air Pollution

arXiv:2605.03795v1 Announce Type: new Abstract: Urban air quality forecasting is challenging because pollutant concentrations are nonlinear, nonstationary, spatiotemporally dependent, and often affect

Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization

arXiv:2605.01482v1 Announce Type: new Abstract: Multi-Hop Fact Verification (MHFV) necessitates complex reasoning across disparate evidence, posing significant challenges for Large Language Models (LL

Label-Efficient School Detection from Aerial Imagery via Weakly Supervised Pretraining and Fine-Tuning

model-releasesarxiv-cs-cv

arXiv:2605.03968v1 Announce Type: new Abstract: Accurate school detection is essential for supporting education initiatives, including infrastructure planning and expanding internet connectivity to un

Learning Generalizable Action Representations via Pre-training AEMG

arXiv:2605.03462v1 Announce Type: new Abstract: A fundamental role in decoding human motor intent and enabling intuitive human-computer interaction is played by electromyography (EMG). However, its ge

LightSBB-M: Bridging Schrodinger and Bass for Generative Diffusion Modeling

model-releasesarxiv-cs-lg

arXiv:2601.19312v2 Announce Type: replace Abstract: The Schrodinger Bridge and Bass (SBB) formulation, which jointly controls drift and volatility, is an established extension of the classical Schrodi

MAGE: Safeguarding LLM Agents against Long-Horizon Threats via Shadow Memory

arXiv:2605.03228v1 Announce Type: cross Abstract: As large language model (LLM)-powered agents are increasingly deployed to perform complex, real-world tasks, they face a growing class of attacks that

safetyarxiv-cs-cl

Metadata, Wavelet, and Time Aware Diffusion Models for Satellite Image Super Resolution

arXiv:2506.23566v2 Announce Type: replace Abstract: The acquisition of high-resolution satellite imagery is often constrained by the spatial and temporal limitations of satellite sensors, as well as t

Multimodal Learning on Low-Quality Data with Conformal Predictive Self-Calibration

model-releasesarxiv-cs-cv

arXiv:2605.03820v1 Announce Type: new Abstract: Multimodal learning often grapples with the challenge of low-quality data, which predominantly manifests as two facets: modality imbalance and noisy cor

Poly-EPO: Training Exploratory Reasoning Models

arXiv:2604.17654v3 Announce Type: replace Abstract: Exploration is a cornerstone of learning from experience: it enables agents to find solutions to complex problems, generalize to novel ones, and sca

Quality-Aware Exploration Budget Allocation for Cooperative Multi-Agent Reinforcement Learning

arXiv:2605.01865v1 Announce Type: cross Abstract: Cooperative multi-agent reinforcement learning (MARL) requires agents to discover joint strategies in a combinatorially large state-action space, yet

agentsarxiv-cs-ai

Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution

arXiv:2505.00334v3 Announce Type: replace Abstract: Image Super-Resolution is a fundamental problem in computer vision with broad applications spacing from medical imaging to satellite analysis. The a

Safety and accuracy follow different scaling laws in clinical large language models

model-releasesarxiv-cs-cl

arXiv:2605.04039v1 Announce Type: new Abstract: Clinical LLMs are often scaled by increasing model size, context length, retrieval complexity, or inference-time compute, with the implicit expectation

Sample-Efficient Optimization over Generative Priors via Coarse Learnability

arXiv:2503.06917v5 Announce Type: replace Abstract: We study zeroth-order optimization where solutions must minimize a cost d(s) while maintaining high probability under a complex generative prior L(s

safetyarxiv-cs-lg

Sheaf-Theoretic Planning: A Categorical Foundation for Resilient Multi-Agent Autonomous Systems

arXiv:2605.01879v1 Announce Type: new Abstract: The challenge of engineering autonomous agents capable of navigating the stochastic and adversarial nature of the physical world has historically reside

agentsarxiv-cs-ai

SoDa2: Single-Stage Open-Set Domain Adaptation via Decoupled Alignment for Cross-Scene Hyperspectral Image Classification

arXiv:2605.03371v1 Announce Type: new Abstract: Cross-scene hyperspectral image (HSI) classification stands as a fundamental research topic in remote sensing, with extensive applications spanning vari

safetyarxiv-cs-cv

Steerable Adversarial Scenario Generation through Test-Time Preference Alignment

arXiv:2509.20102v2 Announce Type: cross Abstract: Adversarial scenario generation is a cost-effective approach for safety assessment of autonomous driving systems. However, existing methods are often

safetyarxiv-cs-ro

The Garden of Forking Paths: Narrative Arc-Conditioned Gameplay Planning

arXiv:2605.01245v1 Announce Type: cross Abstract: Narrative archetypes (e.g., Hero's Journey, Three-act structure) provide universal story structures that resonate across cultures and media and are im

Trojan Hippo: Weaponizing Agent Memory for Data Exfiltration

model-releasesarxiv-cs-ai

arXiv:2605.01970v2 Announce Type: cross Abstract: Memory systems enable otherwise-stateless LLM agents to persist user information across sessions, but also introduce a new attack surface. We characte

Uncertainty-Aware Trip Purpose Inference from GPS Trajectories via POI Semantic Zones and Pareto Calibration

arXiv:2605.01257v1 Announce Type: new Abstract: Large-scale GPS trajectory data offer rich observations of human mobility, yet assigning trip purposes to detected stops remains challenging due to the

WorldJen: An End-to-End Multi-Dimensional Benchmark for Generative Video Models

model-releasesarxiv-cs-cv

arXiv:2605.03475v1 Announce Type: new Abstract: Evaluating generative video models remains an open problem. Reference-based metrics such as Structural Similarity Index Measure (SSIM) and Peak Signal t

A PAC-Bayesian Analysis of Channel-Induced Degradation in Edge Inference

arXiv:2601.10915v2 Announce Type: replace-cross Abstract: In the emerging paradigm of edge learning, neural networks (NNs) are partitioned across distributed edge devices that collaboratively perform

A Theoretical Game of Attacks via Compositional Skills

arXiv:2605.01034v1 Announce Type: new Abstract: As large language models grow increasingly capable, concerns about their safe deployment have intensified. While numerous alignment strategies aim to re

safetyarxiv-cs-cl

Tutorials

A tutorial on learning from preferences and choices with Gaussian Processes

arXiv:2403.11782v5 Announce Type: replace Abstract: Preference modelling lies at the intersection of economics, decision theory, machine learning and statistics. By understanding individuals' preferen

tutorialsarxiv-cs-lg

Adversarial Imitation Learning with General Function Approximation: Theoretical Analysis and Practical Algorithms

arXiv:2605.01778v1 Announce Type: new Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network a

safetyarxiv-cs-lg

AgentXRay: White-Boxing Agentic Systems via Workflow Reconstruction

arXiv:2602.05353v3 Announce Type: replace-cross Abstract: Large Language Models have shown strong capabilities in complex problem solving, yet many agentic systems remain difficult to interpret and co

agentsarxiv-cs-cl

ANO: A Principled Approach to Robust Policy Optimization

arXiv:2605.02320v1 Announce Type: cross Abstract: Proximal Policy Optimization (PPO) dominates deep RL but faces a fundamental dilemma. Its 'hard clipping' mechanism discards valuable gradient informa

safetyarxiv-cs-lg

Applications

Arbitrarily Conditioned Hierarchical Flows for Spatiotemporal Events

arXiv:2605.01226v1 Announce Type: new Abstract: Events in spatiotemporal systems are ubiquitous, yet modeling their complex distributions remains challenging. Existing point process models often rely

applicationsarxiv-cs-lg

Auditing demographic bias in AI-based emergency police dispatch: a cross-lingual evaluation of eleven large language models

arXiv:2605.01451v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly being integrated into high-stakes public safety systems, including emergency call triage and dispatch decision

safetyarxiv-cs-cl

Automated In-the-Wild Data Collection for Continual AI Generated Image Detection

arXiv:2605.02567v1 Announce Type: new Abstract: The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existi

Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operations

arXiv:2507.21803v2 Announce Type: replace Abstract: Carbon Capture and Storage (CCS) stands as a pivotal technology for fostering a sustainable future. The process, which involves injecting supercriti

Behavior-Grounded Lane Representation Learning for Multi-Task Traffic Digital Twins

arXiv:2605.01901v1 Announce Type: new Abstract: Traffic digital twins are powerful tools for advanced traffic management, and most systems are built on static geometric representations. However, these

safetyarxiv-cs-cv

Causal Foundations of Collective Agency

arXiv:2605.00248v1 Announce Type: new Abstract: A key challenge for the safety of advanced AI systems is the possibility that multiple simpler agents might inadvertently form a collective agent with c

Compression as Adaptation: Implicit Visual Representation with Diffusion Foundation Models

arXiv:2603.07615v2 Announce Type: replace-cross Abstract: Modern visual generative models acquire rich visual knowledge through large-scale training, yet existing visual representations (such as pixel

Continuous quantification of viral plaque dynamics using ultra-large-area label-free imaging enables rapid antiviral susceptibility testing

arXiv:2605.01738v1 Announce Type: cross Abstract: The plaque reduction assay (PRA) remains the gold standard for antiviral susceptibility testing, evaluating drug potency by measuring reductions in pl