Search: “safety”

Tight Lower Bounds for the Multi-Secretary Problem via Bellman Certificates

arXiv:2607.02150v1 Announce Type: cross Abstract: This paper studies additive regret in the multi-secretary problem, defined as the gap between the expected offline prophet reward and the reward of th

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Towards Learning Representations of Policies in Two-Player Zero-Sum Imperfect-Information Games

DGX agent

arXiv:2607.01498v1 Announce Type: new Abstract: We investigate the problem of learning useful policy representations (embeddings) in two-player zero-sum imperfect-information games. We make three cont

safetyarxiv-cs-lg

3 Jul 2026

Transformer Geometry Observatory TGO-II: Representational Similarity Observatory

arXiv:2607.02386v1 Announce Type: cross Abstract: While Vision Transformers have achieved remarkable success across computer vision and language applications, the geometric evolution of their internal

Transport Discrepancy as a Reliability Signal for Vision-Language-Action Models

arXiv:2512.01715v2 Announce Type: replace Abstract: Vision-language-action (VLA) models that generate continuous action chunks via flow matching lack an internal signal for judging whether a given pre

VLAFlow: A Unified Training Framework for Vision-Language-Action Models via Co-training and Future Latent Alignment

arXiv:2607.01586v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) have recently advanced robotic manipulation, yet the effects of different robot-data pre-training paradigms remai

WaveLander: A Generalizable Hierarchical Control Framework for UAV Landing on Wave-Disturbed Platforms via Reinforcement Learning

arXiv:2607.01281v1 Announce Type: new Abstract: Autonomous landing of unmanned aerial vehicles (UAVs) on wave-disturbed marine platforms remains challenging due to stochastic platform motion, time-var

WBMM: Windowed Batch Matrix Multiplication for Efficient Large Receptive Field Convolution

arXiv:2607.02097v1 Announce Type: cross Abstract: Large kernel depthwise convolutions achieve strong performance but suffer from significant degradation as kernel size grows due to irregular memory ac

What LLM Agents Say When No One Is Watching: Social Structure and Latent Objective Emergence in Multi-Agent Debates

arXiv:2607.02507v1 Announce Type: new Abstract: LLM agents will increasingly act in socially structured settings where role, audience, and relational context can shape what is advantageous or costly t

When Sample Selection Bias Precipitates Model Collapse

arXiv:2606.13732v2 Announce Type: replace Abstract: The proliferation of recursive training on synthetic data can alleviate data scarcity but risks model collapse, where repeated training erodes distr

When Should Service Agents Reconsider? Difficulty-Routed Control in Customer-Service Operations

arXiv:2607.01426v1 Announce Type: new Abstract: Autonomous customer-service agents are shifting from conversational interfaces toward operational execution roles: they retrieve firm records, apply ser

Wind-Aware Reinforcement Learning Control of a Small Quadrotor Using Learned Onboard Wind Estimation in Simulated Atmospheric Turbulence

arXiv:2607.01528v1 Announce Type: new Abstract: Small multirotor aircraft are increasingly tasked with operations in the atmospheric boundary layer, where turbulent winds comparable to the vehicle's a

WorldSample: Closed-loop Real-robot RL with World Modelling

arXiv:2607.02431v1 Announce Type: cross Abstract: Reinforcement learning (RL) can overcome the demonstration-coverage limitation of imitation learning (IL) by allowing robots to improve through trial-

A Category Theory Account of AI Identity

arXiv:2607.00220v1 Announce Type: cross Abstract: Artificial intelligence (AI) systems are routinely modified after deployment through retraining and changes in their environments. These transformatio

A Filtered Mixture-of-Generators for Fully Synthetic Survival Training

arXiv:2607.00127v1 Announce Type: new Abstract: Survival analysis models time-to-event data, but in clinical settings training data are costly and scarce: events accrue over years of follow-up, cohort

A Mechanism-Driven Theory of Phase Transitions in Active Learning

arXiv:2607.00144v1 Announce Type: cross Abstract: Active learning (AL) performance is known to be budget-dependent, yet regimes are typically defined by heuristic label counts that fail to generalize

A Multi-Resolution Finite-Volume Inspired Deep Learning Framework for Spatiotemporal Dynamics Prediction

arXiv:2607.00460v1 Announce Type: cross Abstract: Predicting complex spatiotemporal dynamics in physical processes often demands computationally expensive numerical methods or data-driven neural netwo

Local Ai

A Two-stage Transformer Framework for Temporal Localization of Distracted Driver Behaviors

arXiv:2603.21048v2 Announce Type: replace-cross Abstract: The identification of hazardous driving behaviors from in-cabin video streams is essential for enhancing road safety and supporting the detect

local-aiarxiv-cs-ai

Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization

arXiv:2607.00531v1 Announce Type: cross Abstract: Scientific reasoning is an increasingly important capability of large language models, yet improving the robustness and efficiency of training such re

Active Spatial Guidance: Eliminating Injected Positional Mechanisms in Vision Transformers

arXiv:2607.00580v1 Announce Type: new Abstract: Vision Transformers (ViTs) commonly rely on injected positional mechanisms to address self-attention's permutation invariance. Motivated by the spatial

Aligning Sentence Embeddings to Human Concepts via Sparse Autoencoders

arXiv:2607.00023v1 Announce Type: cross Abstract: Dense sentence embeddings are fundamental to modern Retrieval-Augmented Generation (RAG) systems but suffer from a lack of interpretability due to fea

ASPIRE: Agentic /Skills Discovery for Robotics

arXiv:2607.00272v1 Announce Type: cross Abstract: Traditional robot programming is challenging: it requires orchestrating multimodal perception, managing physical contact dynamics, and handling divers

Attribute-Prompted Kernel Hashing for Unsupervised Data-Efficient Cross-Modal Retrieval

arXiv:2607.00379v1 Announce Type: cross Abstract: Unsupervised cross-modal hashing enables efficient retrieval of semantically related instances across different modalities without requiring manual se

AutoSpeed: Annotation-Free Stage-Adaptive Motion Speed Learning for Robot Manipulation

arXiv:2607.01051v1 Announce Type: new Abstract: Different stages of manipulation tasks exhibit varying levels of difficulty, suggesting stage-dependent motion speeds and temporal prediction horizons.

Bounded Morality: Defining the Space of Moral Computation

arXiv:2607.00002v1 Announce Type: new Abstract: Moral cognition has traditionally been modeled as adherence to fixed ethical theories--deontology, consequentialism, virtue ethics--implemented as stati

BrainFIBRE: A Foundation Model via Information Decomposition for Brain Microstructure

arXiv:2607.00573v1 Announce Type: new Abstract: Diffusion MRI probes brain microstructure with particular sensitivity to early cerebrovascular and neurodegenerative changes. Neurite Orientation Disper

Caption Bottleneck Models

arXiv:2607.00578v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide interpretability by routing predictions through a layer of human-understandable concepts. However, defining an

ClinRAG-GRAPH: Clinical-prior Retrieval-Augmented Graph Model with Domain Adversarial Learning for Breast pCR Prediction

arXiv:2607.00798v1 Announce Type: new Abstract: Neoadjuvant chemotherapy (NAC) response prediction is clinically important for treatment stratification in breast cancer. However, robust pre-treatment

Constructive Alignment: Governing Preference Dynamics in Human-AI Interaction

arXiv:2607.00001v1 Announce Type: new Abstract: Most approaches to AI alignment treat human preferences as fixed targets to be inferred and optimized. This assumption conflicts with extensive empirica

Continuous Speculative Decoding for Autoregressive Image Generation

arXiv:2411.11925v3 Announce Type: replace Abstract: Continuous visual autoregressive (AR) models have demonstrated promising performance in image generation, but their inherently sequential nature res

Dataset Biases and Shortcut Learning in Motion-Based AI-Generated Video Detection

arXiv:2607.00948v1 Announce Type: new Abstract: The visual quality of AI-generated videos has improved drastically in recent years, making it increasingly difficult for humans to distinguish between r

Diffusion-GR2: Diffusion Generative Reasoning Re-ranker

arXiv:2607.01170v1 Announce Type: cross Abstract: Generative reasoning re-rankers achieve strong recommendation accuracy by emitting a chain-of-thought before re-ordering a candidate list, but they ar

Distill to Detect: Exposing Stealth Biases in LLMs through Cartridge Distillation

arXiv:2607.01208v1 Announce Type: cross Abstract: Language models deployed in high-stakes roles can potentially favor certain entities, brands, or viewpoints, steering user decisions at scale. Such pr

Domain Arithmetic: One-Shot VLA Adaptation under Environmental Shifts

arXiv:2607.00666v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models often fail to perform the same learned tasks under environmental shifts, such as changes in camera pose and shifts

Dual-Informed Vertical Expansion for Multi-Objective Node Selection in Anytime Conflict-Based Search

arXiv:2607.00156v1 Announce Type: new Abstract: Conflict-Based Search (CBS) is a leading exact algorithm for Multi-Agent Path Finding (MAPF), but its high-level node-selection rule is usually treated

ELMP: Efficient Learning for Motion Planning via Analytical Policy Gradients

arXiv:2607.00215v1 Announce Type: new Abstract: Neural Motion Planners (NMPs) enable fast reactive motion generation, but adapting them to new environments typically requires recollecting large expert

Enhancing Hardware Fault Tolerance in Machines with Reinforcement Learning Policy Gradient Algorithms

arXiv:2407.15283v2 Announce Type: replace-cross Abstract: Industry is moving toward autonomous, network-connected machines that detect and adapt to changing conditions, including hardware faults. Conv

EPO: Boosting 3D Foundation Models with Edge-based Pose Optimization

arXiv:2607.00579v1 Announce Type: new Abstract: We introduce extbf{Edge-based Pose Optimization (EPO)}, a trackless geometric optimization framework specifically designed to boost the Structure-from-M

EquiSteer: Cross-Attention Steering Towards a Fairer Text-Guided Image Generation

arXiv:2607.01147v1 Announce Type: new Abstract: Text-to-image diffusion models power everyday creative tasks, but they still reproduce the demographic biases in their training data. On common prompts

FAR: Failure-Aware Retry for Test-Time Recovery and Continual Policy Improvement

arXiv:2607.01111v1 Announce Type: cross Abstract: Robot policies inevitably encounter failures when deployed in real environments. Naive retries often repeat the same mistakes, while many existing rec

ForAug: Mitigating Biases in Image Classification via Controlled Image Compositions

arXiv:2503.09399v4 Announce Type: replace-cross Abstract: Large-scale image classification datasets exhibit strong compositional biases: objects tend to be centered, appear at characteristic scales, a

FrameONE: Hierarchical Motion Modeling for Universal Multi-View Echocardiographic Keyframe Detection

arXiv:2607.00748v1 Announce Type: new Abstract: Accurate detection of end-systole (ES) and end-diastole (ED) frames is fundamental to echocardiographic assessment. Existing methods are typically devel

From Pixels to Temporal Correlations: Learning Informative Representations for Reinforcement Learning Pre-training

arXiv:2607.00811v1 Announce Type: new Abstract: Unsupervised pre-training on large-scale datasets has demonstrated significant potential for improving the sample efficiency and performance of Reinforc

From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning

arXiv:2603.10263v2 Announce Type: replace-cross Abstract: We introduce Distribution Contractive Reinforcement Learning (DICE-RL), a framework that uses reinforcement learning (RL) as a 'distribution c

From World Models to World Action Models: A Concise Tutorial for Robotics

arXiv:2607.00836v1 Announce Type: cross Abstract: World models are increasingly used in embodied intelligence and generative simulation, yet their scope remains ambiguous across communities. This tuto

Gauging, Measuring, and Controlling Critic Complexity in Actor-Critic Reinforcement Learning

arXiv:2607.00452v1 Announce Type: cross Abstract: Actor-critic methods depend on learned critics, but critic quality is often evaluated only indirectly through return, temporal-difference error, or va

GaussianFusion: Unified 3D Gaussian Representation for Multi-Modal Fusion Perception

arXiv:2607.00746v1 Announce Type: cross Abstract: The bird's-eye view (BEV) representation enables multi-sensor features to be fused within a unified space, serving as the primary approach for achievi

Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination

arXiv:2607.00924v1 Announce Type: new Abstract: Accelerating materials discovery requires AI systems that can generate scientifically valid hypotheses through multi-step, domain-grounded reasoning. St

GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity

arXiv:2607.00152v1 Announce Type: cross Abstract: Three of the most popular methods for training language models to reason look like three different tricks. They are not. All three adjust a single num