Search: “safety”

Reflective Flow Sampling Enhancement

arXiv:2603.06165v2 Announce Type: replace-cross Abstract: The growing demand for text-to-image generation has led to rapid advances in generative modeling. Recently, text-to-image diffusion models tra

Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes

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arXiv:2603.25562v2 Announce Type: replace-cross Abstract: On-policy distillation (OPD) is increasingly used in LLM post-training because it can leverage a teacher model to provide dense supervision on

safetyarxiv-cs-ai

28 Apr 2026

Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis

arXiv:2604.24198v1 Announce Type: cross Abstract: Process Reward Models (PRMs) have achieved remarkable success in augmenting the reasoning capabilities of Large Language Models (LLMs) within static d

RL Token: Bootstrapping Online RL with Vision-Language-Action Models

arXiv:2604.23073v1 Announce Type: new Abstract: Vision-language-action (VLA) models can learn to perform diverse manipulation skills 'out of the box,' but achieving the precision and speed that real-w

RouteGuard: Internal-Signal Detection of Skill Poisoning in LLM Agents

arXiv:2604.22888v1 Announce Type: cross Abstract: Agent skills introduce a new and more severe form of indirect injection for LLM agents: unlike traditional indirect prompt injection, attackers can hi

SAGE: Sparse Adaptive Guidance for Dependency-Aware Tabular Data Generation

arXiv:2604.24368v1 Announce Type: new Abstract: Generating high-fidelity synthetic tabular data remains a critical challenge for enhancing data availability in privacy-sensitive and low-resource domai

SARM: Stage-Aware Reward Modeling for Long Horizon Robot Manipulation

arXiv:2509.25358v4 Announce Type: replace Abstract: Large-scale robot learning has made progress on complex manipulation tasks, yet long horizon, contact rich problems, especially those involving defo

safetyarxiv-cs-ro

Scalable Production Scheduling: Linear Complexity via Unified Homogeneous Graphs

arXiv:2604.23841v1 Announce Type: cross Abstract: Efficiently solving the Job Shop Scheduling Problem in real-world industrial applications requires policies that are both computationally lean and top

SceneSelect: Selective Learning for Trajectory Scene Classification and Expert Scheduling

arXiv:2604.24514v1 Announce Type: new Abstract: Accurate trajectory prediction is fundamentally challenging due to high scene heterogeneity - the severe variance in motion velocity, spatial density, a

Scheduling Your LLM Reinforcement Learning with Reasoning Trees

arXiv:2510.24832v2 Announce Type: replace Abstract: Using Reinforcement Learning with Verifiable Rewards (RLVR) to optimize Large Language Models (LLMs) can be conceptualized as progressively editing

Seer: Language Instructed Video Prediction with Latent Diffusion Models

arXiv:2303.14897v4 Announce Type: replace Abstract: Imagining the future trajectory is the key for robots to make sound planning and successfully reach their goals. Therefore, text-conditioned video p

Self-Supervised Learning for Android Malware Detection on a Time-Stamped Dataset

arXiv:2604.23025v1 Announce Type: cross Abstract: Android malware detectors built with machine learning often suffer from temporal bias: models are trained and evaluated without respecting apps' actua

Self-Supervised Representation Learning via Hyperspherical Density Shaping

arXiv:2604.24498v1 Announce Type: new Abstract: Modern self-supervised representation learning methods often relies on empirical heuristics that are not theoretically grounded. In this study we propos

ShowFlow: From Robust Single Concept to Condition-Free Multi-Concept Generation

arXiv:2506.18493v2 Announce Type: replace Abstract: Customizing image generation remains a core challenge in controllable image synthesis. For single-concept generation, maintaining both identity pres

SMP: Reusable Score-Matching Motion Priors for Physics-Based Character Control

arXiv:2512.03028v3 Announce Type: replace-cross Abstract: Data-driven motion priors that can guide agents toward producing naturalistic behaviors play a pivotal role in creating life-like virtual char

StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery

arXiv:2604.22892v1 Announce Type: new Abstract: Feature selection in high-dimensional genomic data (d gg n) demands methods that are simultaneously accurate, sparse, and stable. Existing approaches ei

TCOD: Exploring Temporal Curriculum in On-Policy Distillation for Multi-turn Autonomous Agents

arXiv:2604.24005v1 Announce Type: cross Abstract: On-policy distillation (OPD) has shown strong potential for transferring reasoning ability from frontier or domain-specific models to smaller students

Text-Guided Multimodal Unified Industrial Anomaly Detection

arXiv:2604.22899v1 Announce Type: new Abstract: Industrial anomaly detection based on RGB-3D multimodal data has emerged as a mainstream paradigm for intelligent quality inspection. However, existing

The Collapse of Heterogeneity in Silicon Philosophers

arXiv:2604.23575v1 Announce Type: cross Abstract: Silicon samples are increasingly used as a low-cost substitute for human panels and have been shown to reproduce aggregate human opinion with high fid

The Consensus Trap: Dissecting Subjectivity and the 'Ground Truth' Illusion in Data Annotation

arXiv:2602.11318v3 Announce Type: replace Abstract: In machine learning, 'ground truth' refers to the assumed correct labels used to train and evaluate models. However, the foundational 'ground truth'

The Imbalanced User-AI Relationships as an Ethical Failure of Front-End Design in Healthcare AI

arXiv:2604.22767v1 Announce Type: cross Abstract: Ethical discourse on AI in healthcare has focused predominantly on back-end concerns such as bias, fairness and explainability, while the front-end in

Model Releases

The Kerimov-Alekberli Model: An Information-Geometric Framework for Real-Time System Stability

model-releasesarxiv-cs-ai

arXiv:2604.24083v1 Announce Type: new Abstract: This study introduces the Kerimov-Alekberli model, a novel information-geometric framework that redefines AI safety by formally linking non-equilibrium

The Swarm Intelligence Freeway-Urban Trajectories (SWIFTraj) Dataset -- Part II: A Graph-Based Approach for Trajectory Connection

arXiv:2602.21954v2 Announce Type: replace-cross Abstract: In Part I of this companion paper series, we introduced SWIFTraj, a new open-source vehicle trajectory dataset collected using a unmanned aeri

safetyarxiv-cs-ro

Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement

arXiv:2601.02018v2 Announce Type: replace Abstract: Segment Anything Models (SAMs), known for their exceptional zero-shot segmentation performance, have garnered significant attention in the research

Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisation

arXiv:2603.15941v2 Announce Type: replace Abstract: Automated diagnosis from chest computed tomography (CT) scans faces two persistent challenges in clinical deployment: distribution shift across acqu

Understanding Representation Gaps Across Scales in Tropical Tree Species Classification from Drone Imagery

arXiv:2604.23019v1 Announce Type: new Abstract: Accurate classification of tropical tree species from unoccupied aerial vehicle (UAV) imagery remains challenging due to high species diversity and stro

UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks

arXiv:2604.23141v1 Announce Type: cross Abstract: Emerging AR-LLM-based Social Engineering attack (e.g., SEAR) is at the edge of posing great threats to real-world social life. In such AR-LLM-SE attac

Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs

arXiv:2604.22893v1 Announce Type: cross Abstract: Traditional data valuation methods based on ``row-count imes quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that

V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think

arXiv:2604.23380v1 Announce Type: cross Abstract: Aligning denoising generative models with human preferences or verifiable rewards remains a key challenge. While policy-gradient online reinforcement

Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines

arXiv:2604.23001v1 Announce Type: cross Abstract: Despite remarkable progress in Vision--Language--Action (VLA) models, a central bottleneck remains underexamined: the data infrastructure that underli

Voxify3D: Pixel Art Meets Volumetric Rendering

arXiv:2512.07834v2 Announce Type: replace Abstract: Voxel art is a distinctive stylization widely used in games and digital media, yet automated generation from 3D meshes remains challenging due to co

When Annotators Agree but Labels Disagree: The Projection Problem in Stance Detection

arXiv:2603.24231v2 Announce Type: replace Abstract: Stance detection is nearly always formulated as classifying text into Favor, Against, or Neutral. This convention was inherited from debate analysis

World-R1: Reinforcing 3D Constraints for Text-to-Video Generation

arXiv:2604.24764v1 Announce Type: new Abstract: Recent video foundation models demonstrate impressive visual synthesis but frequently suffer from geometric inconsistencies. While existing methods atte

XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation

arXiv:2604.24623v1 Announce Type: new Abstract: Graph-based Retrieval-Augmented Generation (GraphRAG) extends traditional RAG by using knowledge graphs (KGs) to give large language models (LLMs) a str

Your Students Don't Use LLMs Like You Wish They Did

arXiv:2604.23486v1 Announce Type: new Abstract: Educational NLP systems are typically evaluated using engagement metrics and satisfaction surveys, which are at best a proxy for meeting pedagogical goa

Z^2-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models

arXiv:2604.23536v1 Announce Type: new Abstract: Diffusion models have achieved unprecedented success in text-aligned generation, largely driven by Classifier-Free Guidance (CFG). However, standard CFG

ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems

arXiv:2604.23878v1 Announce Type: new Abstract: Despite a century of empirical memory research, existing AI agent memory systems rely on system-engineering metaphors (virtual-memory paging, flat LLM s

AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning

arXiv:2511.14135v2 Announce Type: replace-cross Abstract: Fair workload enforcement in heterogeneous multi-agent systems that pursue shared objectives remains challenging. Fixed fairness penalties oft

Algorithmic Feature Highlighting for Human-AI Decision-Making

arXiv:2604.22236v1 Announce Type: cross Abstract: Human decision-makers often face choices about complex cases with many potentially relevant features, but limited bandwidth to inspect and integrate a

An Integrated Framework for Explainable, Fair, and Observable Hospital Readmission Prediction: Development and Validation on MIMIC-IV

arXiv:2604.22535v1 Announce Type: new Abstract: Objective: To propose and retrospectively validate an integrated framework addressing three barriers to clinical translation of readmission prediction:

Beyond Chain-of-Thought: Rewrite as a Universal Interface for Generative Multimodal Embeddings

arXiv:2604.22280v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have emerged as a promising foundation for universal multimodal embeddings. Recent studies have shown that reas

Calibrated Principal Component Regression

arXiv:2510.19020v2 Announce Type: replace-cross Abstract: We propose a new method for statistical inference in generalized linear models. In the overparameterized regime, Principal Component Regressio

CGC: Compositional Grounded Contrast for Fine-Grained Multi-Image Understanding

arXiv:2604.22498v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have advanced rapidly, they still face notable challenges in fine-grained multi-image understanding,

Clutter-Robust Vision-Language-Action Models through Object-Centric and Geometry Grounding

arXiv:2512.22519v2 Announce Type: replace Abstract: Recent Vision-Language-Action (VLA) models have made impressive progress toward general-purpose robotic manipulation by post-training large Vision-L

safetyarxiv-cs-ro

CognitiveTwin: Robust Multi-Modal Digital Twins for Predicting Cognitive Decline in Alzheimer's Disease

arXiv:2604.22428v1 Announce Type: new Abstract: Predicting individual cognitive decline in Alzheimer's disease (AD) is difficult due to the heterogeneity of disease progression. Reliable clinical tool

Concave Statistical Utility Maximization Bandits via Influence-Function Gradients

arXiv:2604.22140v1 Announce Type: cross Abstract: We study stochastic multi-armed bandits in which the objective is a statistical functional of the long-run reward distribution, rather than expected r

Conditional Diffusion Posterior Alignment for Sparse-View CT Reconstruction

arXiv:2604.21960v1 Announce Type: cross Abstract: Computed Tomography (CT) is a widely used imaging modality in medical and industrial applications. To limit radiation exposure and measurement time, t

Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding

arXiv:2604.22335v1 Announce Type: new Abstract: Large language models (LLMs) often produce content that contradicts or overlooks information provided in the input context, a phenomenon known as faithf