Search: “safety”

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation

arXiv:2607.05943v1 Announce Type: new Abstract: Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines cons

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SpatialFly: Implicit 3D Prior-Guided Visual Reparameterization for Continuous UAV Vision-and-Language Navigation

DGX agent

arXiv:2603.21046v2 Announce Type: replace-cross Abstract: UAVs play an important role in applications such as autonomous exploration, disaster response, and infrastructure inspection. However, UAV VLN

safetyarxiv-cs-ai

8 Jul 2026

Stability Annealing Selects the Implicit Bias of Smoothed Sign Descent: A Rate-Indexed Barrier Path on Separable Data

arXiv:2607.06013v1 Announce Type: new Abstract: Adaptive gradient methods can favor max-margin separators that differ from gradient descent, yet a fixed positive numerical stability constant eventuall

Statistical Adversaries: Natural Backdoor-like Features in Vision Datasets

arXiv:2607.05516v1 Announce Type: cross Abstract: Model-specific adversarial attacks have been extensively studied. We study a different failure mode: naturally occurring statistical signals in vision

Straight-Path Flow Matching for Incomplete Multi-View Clustering

arXiv:2607.06281v1 Announce Type: new Abstract: Incomplete Multi-View Clustering addresses the problem of clustering multi-modal data when certain views are missing. Recent end-to-end generative appro

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition

arXiv:2607.06185v1 Announce Type: new Abstract: Fine-grained image recognition poses a significant challenge due to the substantial expertise and effort required for manual annotation. Vision-language

Superman: Unifying Skeleton and Vision for Human Motion Perception and Generation

arXiv:2602.02401v2 Announce Type: replace Abstract: Human motion analysis tasks, such as temporal 3D pose estimation, motion prediction, and motion in-betweening, play an essential role in computer vi

The Jagged Global Economy: Frontier AI Unevenly Exposes National Economies

arXiv:2607.05404v1 Announce Type: cross Abstract: Frontier AI's labor-market effects matter to workers, firms, and policymakers, but current evidence generally comes from a handful of high-income econ

To Retain or to Adapt? Generalizing Continual Learning

arXiv:2607.05609v1 Announce Type: cross Abstract: The Continual Learning (CL) literature has long been driven by the goal of mitigating catastrophic forgetting. This objective rests on a pervasive, of

TurnOPD: Making On-Policy Distillation Turn-Aware for Efficient Long-Horizon Agent Training

arXiv:2607.05804v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student policy by matching a stronger teacher on the student's own trajectories, offering a promising framework fo

UniField: A Unified Field-Aware MRI Enhancement Framework

arXiv:2603.09223v2 Announce Type: replace Abstract: Magnetic Resonance Imaging (MRI) field-strength enhancement holds immense value for both clinical diagnostics and advanced research. However, existi

VEIL: How Visual Encoding Hijacking Induces Bias In Vision Models

arXiv:2607.05641v1 Announce Type: new Abstract: Rendering time series as chart images for CNN-based classification has become increasingly common in time-series classification (TSC). However, it remai

Volumetric Directional Diffusion: Anchoring Uncertainty Quantification in Anatomical Consensus for Ambiguous Medical Image Segmentation

arXiv:2603.04024v2 Announce Type: replace-cross Abstract: Ambiguous 3D medical image segmentation often involves boundaries where different expert delineations are non-identical yet clinically plausib

Whose fairness? Structural concentration in AI bias research

arXiv:2607.05574v1 Announce Type: cross Abstract: Artificial intelligence increasingly mediates consequential decisions in healthcare, law, and public services, and the field has responded with an ext

Width-Robust Learnability in Mean-Field Bayesian Neural Networks

arXiv:2607.05735v1 Announce Type: cross Abstract: Infinite-width limits are a standard way to reason about neural networks, but it is not automatic that the limiting learner has the same complexity-th

WordVoice: Explicit and Decoupled Multi-Dimensional Word-Level Control for LLM-Based TTS

arXiv:2607.06461v1 Announce Type: cross Abstract: While recent Large Language Model (LLM)-based Text-to-Speech (TTS) systems have achieved remarkable naturalness, they predominantly rely on implicit e

safetyarxiv-cs-cl

X-FEMR: A Token-level Explainable Approach for Electronic Health Records Foundation Models using Transformer-based Models

arXiv:2607.06163v1 Announce Type: cross Abstract: Foundation Models for Electronic Health Records (FEMRs) are pretrained on large-scale structured patient data, enabling them to convert longitudinal p

A Bayesian Framework for Evaluating Scenario Compatibility in Generative Population Synthesis

arXiv:2607.03190v1 Announce Type: cross Abstract: Scenario-based transportation analysis specifies future assumptions through aggregate population targets, whereas generative population synthesis mode

A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training

arXiv:2607.04574v1 Announce Type: cross Abstract: For LLM agents, supervised fine-tuning is not only about teacher labels' quality, but also about which interaction contexts those labels condition on.

A Hierarchy of Policy Learning Problems

arXiv:2607.03385v1 Announce Type: cross Abstract: Policy learning has received substantial attention with the goal of learning policies from observational data for decision-making. A majority of work

A Perception-Manipulation Robotics System for Food Cutting

arXiv:2607.04367v1 Announce Type: new Abstract: In the development of cooking robots, mastering the task of cutting is crucial. A significant challenge lies in the diverse properties of food, which ne

safetyarxiv-cs-ro

A Policy Decomposition Framework for Dynamic Order Fulfillment Operations

arXiv:2607.04056v1 Announce Type: cross Abstract: Modern supply chains span diverse operational environments, ranging from e-commerce distribution networks to customized production-to-order manufactur

A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning

arXiv:2606.16933v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) systems often degrade when operating conditions differ from those previously encountered, reflecting distributiona

ACE: Agentic Control for Embodied Manipulation via Zero-shot Workflow Reasoning

arXiv:2607.04162v1 Announce Type: cross Abstract: Open-ended tabletop manipulation requires agents to not only understand natural language but also adapt to dynamic environments and execution failures

ACPO: Adaptive Credit Policy Optimization via Fine-Grained Surrogate Entropy

arXiv:2607.03126v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has substantially improved the reasoning ability of large language models (LLMs), but sparse outcome rewards still make to

Adaptive Entropy-Driven Sensor Selection in a Camera-LiDAR Particle Filter for Single-Vessel Tracking

arXiv:2603.08457v2 Announce Type: replace-cross Abstract: Robust single-vessel tracking from fixed coastal platforms is hindered by modality-specific degradations: cameras suffer from illumination and

Adaptive Inference Batching using Policy Gradients

arXiv:2607.05272v1 Announce Type: cross Abstract: Inference serving systems must balance throughput and latency under bursty, heterogeneous workloads, yet the industry standard remains static batching

Adaptive Margin RLHF via Preference over Preferences

arXiv:2509.22851v4 Announce Type: replace-cross Abstract: Margin-based optimization is fundamental to improving generalization and robustness in classification tasks. In the context of reward model le

Adaptive Partitioning and Learning for Stochastic Control of Diffusion Processes

arXiv:2512.14991v2 Announce Type: replace Abstract: We study reinforcement learning for controlled diffusion processes with unbounded continuous state spaces, bounded continuous actions, and polynomia

Additive Causal Construction for Transferable and Reconfigurable Cross-System Learning in Multi-Source Image Fusion

arXiv:2607.02572v1 Announce Type: cross Abstract: In multi-source image fusion scenarios, heterogeneous inputs are typically driven by distinct generative mechanisms and can be viewed as a composition

ADP: Adversarial Dynamics Priors for Physically Grounded Humanoid Locomotion

arXiv:2607.03454v1 Announce Type: cross Abstract: In this paper, we propose Adversarial Dynamics Priors (ADP) for perturbation-resilient humanoid locomotion control. Existing motion prior-based method

AGL-1: The Enterprise AI Governance Layer as a Control Plane for Trusted Enterprise Intelligence

arXiv:2607.03516v1 Announce Type: cross Abstract: Enterprise artificial intelligence is moving from isolated experimentation toward operational dependency across copilots, retrieval-augmented generati

Aligning Language Models with Selective Prediction

arXiv:2607.03528v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as critical decision-making components in high-stakes real-world AI systems, rendering LLM reli

Alignment-Guided Largest Table Overlap Size Estimation

arXiv:2607.03049v1 Announce Type: new Abstract: Fast estimation of the size of the largest overlap between tables enables blocking and query-by-table retrieval in large table repositories. The first a

safetyarxiv-cs-cl

AnchorDream: Repurposing Video Diffusion for Embodiment-Aware Robot Data Synthesis

arXiv:2512.11797v2 Announce Type: replace-cross Abstract: The collection of large-scale and diverse robot demonstrations remains a major bottleneck for imitation learning, as real-world data acquisiti

Anticipatory Reinforcement Learning for Trajectory Tracking

arXiv:2607.03132v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) in industrial control often suffers from lag and overshoot due to purely reactive control based on the current trackin

AquaStereo: Enabling Underwater Stereo Matching via Depth-Conditioned Diffusion and Geometry Self-Distillation

arXiv:2607.04303v1 Announce Type: new Abstract: Learning-based stereo matching models struggle in underwater environments due to scarce in-domain data and the difficulty of extracting discriminative c

ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning

arXiv:2602.21534v3 Announce Type: replace Abstract: Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interacti

ASK in the Dark: Uncertainty-Gated LLM Assistance under Partial Observability

arXiv:2607.02686v1 Announce Type: new Abstract: Reinforcement learning agents operating under partial observability must act on incomplete information, making them natural candidates for guidance from

Athena-WBC: Capability-Aligned Policy Experts for Long-Tail Humanoid Whole-Body Control

arXiv:2607.04837v1 Announce Type: new Abstract: Large-scale humanoid motion-tracking controllers are commonly improved by reallocating training effort: difficult motions are sampled more often, isolat

safetyarxiv-cs-ro

Attention Limited Reward Learning

arXiv:2607.04590v1 Announce Type: new Abstract: Pairwise human comparisons are a primary interface through which modern AI systems learn human preferences. RLHF and related alignment pipelines typical

Attributing Emergence in Million-Agent Systems

arXiv:2605.11404v2 Announce Type: replace Abstract: Large language models (LLMs) can simulate human-like reasoning and decision-making in individual agents. LLM-powered multi-agent systems (MAS) combi

Aura: Consistent Multi-Subject Video Generation via VLM-Grounded Semantic Alignment

arXiv:2607.04311v1 Announce Type: new Abstract: Subject-driven and multi-element video generation are central to controllable video synthesis, but existing methods still struggle to preserve identity

Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems

arXiv:2607.04433v1 Announce Type: cross Abstract: The rapid integration of large language model-based agents into recommender systems has driven a shift from static, ranking-based pipelines toward aut

safetyarxiv-cs-cl

AViS-Mamba: Adaptive Visual Steering of Audio State-Space Dynamics for Violence Detection

arXiv:2604.03329v2 Announce Type: replace-cross Abstract: Automatic violence detection from video is challenging because violent interactions may be distant, occluded, or only partially visible. Audio

Benign Overfitting Does Not Occur in Diffusion Models

arXiv:2607.02671v1 Announce Type: cross Abstract: Benign overfitting and double descent have come to shape our understanding of generalization in deep learning, establishing that overfitting is not on

Beyond Independent Labels: Schwartz-Geometry Decoding for Human Value Detection

arXiv:2607.05052v1 Announce Type: cross Abstract: Human value detection is commonly formulated as sentence-level multi-label classification over the 19 refined Schwartz values, typically predicted as

Beyond Point-Attached Semantics: Object-Centric Semantic Fields for Generalizable Manipulation

arXiv:2607.03163v1 Announce Type: new Abstract: Generalizable robot manipulation requires stable 3D understanding of functional object parts, such as handles, tool heads, openings, and graspable regio

safetyarxiv-cs-ro