Search: “safety”

Policy Gradients for Cumulative Prospect Theory in Reinforcement Learning

arXiv:2410.02605v5 Announce Type: replace Abstract: We derive a policy gradient theorem for Cumulative Prospect Theory (CPT) objectives in finite-horizon Reinforcement Learning (RL), generalizing the

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Prevalence calibration as shortcut mitigation

DGX agent

arXiv:2609.07922v1 Announce Type: cross Abstract: Shortcut learning denotes the widespread situation in which a classifier exploits spurious correlations rather than diagnostic features. Existing miti

safetyarxiv-cs-cv

9 Sept 2026

PRG-Fusion: Orchestrating Generative Priors with Reconstruction Evidence for Driving View Synthesis

arXiv:2609.06948v1 Announce Type: new Abstract: Synthesizing photorealistic driving videos along specified trajectories is essential for scalable closed-loop simulation. Reconstruction-based methods l

Provable Pluralistic Alignment: Multi-Party RLHF under Offline Human Feedback

arXiv:2403.05006v2 Announce Type: replace Abstract: Pluralistic alignment requires learning from feedback that reflects persistent and potentially conflicting stakeholder preferences while ultimately

Proximity-CLIP: Text-Guided Semantic Proximity Learning for Zero-Shot Anomaly Detection

arXiv:2609.07229v1 Announce Type: new Abstract: Vision-language models offer a promising approach for zero-shot anomaly detection (ZSAD). However, due to object-centric bias, normal and anomalous text

Proxy Policy Steering

arXiv:2609.09148v1 Announce Type: new Abstract: Generalist robot policies carry broad manipulation priors from large-scale data, but specializing them to a new task remains the deployment bottleneck.

Q-Guided Stein Variational Model Predictive Control via RL-informed Policy Prior

arXiv:2507.06625v4 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) enables reliable trajectory optimization under dynamics constraints, but often depends on accurate dynamics mod

RAFM-SER++: A Lightweight Multimodal Emotion Recognition Framework for Real-Time Behavioral Monitoring in Surveillance Systems

arXiv:2609.07409v1 Announce Type: cross Abstract: Recent multimodal Speech Emotion Recognition (SER) systems achieve high accuracy through interaction-heavy cross-modal transformers, but their computa

RAH-VLA: Resolution-Adaptive Hierarchical Vision-Language Alignment for Multimodal Remote Sensing Understanding

arXiv:2512.23243v3 Announce Type: replace Abstract: Multimodal vision-language modeling has emerged as a promising paradigm for remote sensing (RS) image understanding. However, existing methods are l

RAIDAL: Redundancy-Aware Information Density Active Learning for CTC-Based Continuous Sign Language Recognition

arXiv:2609.06843v1 Announce Type: new Abstract: Continuous sign language recognition (CSLR) is a key technology for accessibility, yet its development remains limited by the high cost of annotating co

RefGuard: Identity-Aware Language-Guided Robot Manipulation via Joint Target-Anchor-Frame Grounding

arXiv:2609.06221v1 Announce Type: new Abstract: Vision-language-action (VLA) models have substantially advanced language-guided robot manipulation, yet reliable execution still hinges on identifying w

RelightFormer: Feed-forward Generative Transformer for Multiview Object Relighting

arXiv:2609.07414v1 Announce Type: new Abstract: Image relighting is traditionally tackled via complex inverse rendering pipelines, which suffer from ill-posed optimization, or single-image generative

Remotely Detectable Keyed Communication through Motion

arXiv:2609.08920v1 Announce Type: new Abstract: Messages from electronic devices are conventionally received as text, audio, or radio signals. But robots move with rich, articulate motion in the real

Representation Learning for Sample-Efficient CATE Estimation by Leveraging Multiple Outcomes

arXiv:2609.06294v1 Announce Type: new Abstract: Estimating conditional average treatment effects (CATE) enables efficient targeting of interventions, but many applications have limited experimental sa

Residual-augmented flow matching operators for probabilistic partial differential equations

arXiv:2512.12749v3 Announce Type: replace-cross Abstract: Learning surrogate models for physical systems with latent uncertainty remains challenging in data-scarce regimes: deterministic neural operat

ReST-RL: Reinforcing LLM Reasoning through Unified Self-Training and Value-Guided Search

arXiv:2508.19576v3 Announce Type: replace-cross Abstract: With respect to improving the reasoning accuracy of LLMs, the representative reinforcement learning (RL) method - Group Relative Policy Optimi

REVA-PO: Stabilizing Reinforcement Learning for Chest X-ray Report Generation

arXiv:2607.10147v2 Announce Type: replace Abstract: Automated chest X-ray report generation has recently benefited from reinforcement learning (RL) and large language models. However, RL training ofte

Risk-Conditioned Fine-Tuning of Large Language Models

arXiv:2609.08064v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in settings where rare but severe harmful generations can have significant consequences. Existing

RoboDreamer: Anticipatory Humanoid Locomotion with Predictive State-Space Models

arXiv:2609.07096v1 Announce Type: new Abstract: Humanoid locomotion requires control policies that remain stable under imperfect sensing while exploiting temporal context for consistent motion. We pre

Robots Influencing Humans to Reveal their Goals during Collaboration and Competition

arXiv:2609.05519v1 Announce Type: new Abstract: We propose a unified strategy for fast goal inference in human-robot interaction. The core idea is to drive the human toward Critical Decision Points (C

Routing Dense Layouts with History-Aware Offline Reinforcement Learning using LSTM

arXiv:2609.08232v1 Announce Type: cross Abstract: Detailed routing remains a dominant runtime bottleneck in physical design due to increasing complexity of design rules. Modern routers can struggle to

Scaling 3D Generative Priors to Large-Scale Scene Meshes from Multi-View Images

arXiv:2609.06385v1 Announce Type: new Abstract: Pretrained 3D generative models produce detailed geometry and appearance but are primarily designed for object-centric generation within a limited spati

Second-Order Smooth Planning with Optimal-Transport Bellman Smoothing

arXiv:2609.06484v1 Announce Type: new Abstract: Planning with a generative model aims to estimate the value of a state using as few simulator calls as possible. SmoothCruiser achieves problem-independ

SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models

arXiv:2609.05533v1 Announce Type: new Abstract: Long-horizon manipulation is partially observable: the information needed to choose the next action may appear only in observations from minutes earlier

SkillX: Unified Multi-Skill Policy Learning for Humanoid Soccer

arXiv:2609.06718v1 Announce Type: new Abstract: Humanoid soccer is a challenging testbed for dynamic whole-body control, requiring robots to coordinate balance, locomotion, object interaction, and ski

SLA-Safe Energy Control for AI-Native NG-RAN Using Stability-Aware Constrained PPO

arXiv:2609.05861v1 Announce Type: cross Abstract: One important AI-for-RAN use case is energy saving, in which radio resources and cell energy modes must be dynamically controlled without violating us

SMaRT-Tug: Structured Multi-Agent Reinforcement Learning for Physics-Based Tugboat-Barge Collaborative Manipulation

arXiv:2609.07445v1 Announce Type: new Abstract: Autonomous tugboating is central for automating maritime operations such as port logistics and vessel maneuvering, where multiple tugboats must cooperat

Spatiotemporal Heterogeneity of AI-Driven Traffic Flow Patterns and Land Use Interaction: A GeoAI-Based Analysis of Multimodal Urban Mobility

arXiv:2603.05581v2 Announce Type: replace Abstract: Urban traffic flow is governed by the complex, nonlinear interaction between land use configuration and spatiotemporally heterogeneous mobility dema

Spectral Prioritized Sweeping in Nonstationary Reinforcement Learning

arXiv:2609.06186v1 Announce Type: new Abstract: Prioritized Sweeping (PS) accelerates model-based reinforcement learning by selecting backups according to Bellman residual magnitude. In nonstationary

SPOT: Spatial Perception-Oriented Long-Horizon Humanoid Teleoperation

arXiv:2609.07933v1 Announce Type: new Abstract: High-quality demonstration data is becoming a central bottleneck for training general-purpose humanoid robots. While recent humanoid teleoperation syste

Stable-MM-R1: Anchoring Multimodal Reasoning Dynamics via Entropy-Guided Stratification

arXiv:2609.07148v1 Announce Type: cross Abstract: While Reinforcement Learning (RL) effectively incentivizes reasoning in Large Language Models, current pipelines are hindered by training instability

Streaming Hierarchical Inference with Tabular Foundation Models

arXiv:2609.07956v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) have recently demonstrated strong predictive performance through in-context learning, but their deployment in high-thro

Structural Entropy-Driven Graph Diffusion Generation for One-Shot Federated Graph Learning

arXiv:2609.06499v1 Announce Type: new Abstract: One-shot federated graph learning (FGL) requires the server to estimate client contributions from highly compressed information, yet conventional volume

Sub-6 GHz Over-the-Air AMC via Curriculum Fine-Tuned CNN-Transformers

arXiv:2609.07726v1 Announce Type: cross Abstract: Automatic modulation classification (AMC) models are frequently trained and validated on synthetic or channel-cabled data, leaving open the question o

SUN: Reaching for Novelty in Reinforcement Learning

arXiv:2609.08642v1 Announce Type: new Abstract: Exploration in reinforcement learning (RL) remains a fundamental challenge. Recent goal-conditioned RL strategies (which select goals to encourage broad

Supervised Cross-Modal Feature Alignment for Zero-Wearable Freezing of Gait Detection in Parkinsonism

arXiv:2609.08317v1 Announce Type: new Abstract: Objective assessment of Freezing of Gait (FoG) in Parkinson's disease (PD) relies predominantly on wearable Inertial Measurement Units (IMUs). While IMU

SwiftExplorer: Training-free Diffusion Model Alignment with Swift Diversity Exploration

arXiv:2609.06651v1 Announce Type: new Abstract: Diffusion models have general generative abilities but struggle to align with specific objectives. Fine-tuning can improve alignment, yet its training c

SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators

arXiv:2609.09155v1 Announce Type: new Abstract: World models are increasingly used as policy-in-the-loop imagination environments, where reliable rollouts require fine-grained controllability with res

TDDN: Text-aligned Diffused DINO Network for Puzzle Understanding

arXiv:2609.07937v1 Announce Type: new Abstract: Structured visual reasoning, such as image puzzles, demands fine-grained visual perception, an ability current Vision Language Models (VLMs) lack. VLMs

Temporal-Causal Inference for Reinforcement Learning via Automata Learning

arXiv:2609.07461v1 Announce Type: new Abstract: We consider reinforcement learning in environments with dynamics that undergo an irreversible phase transition governed by a hidden temporal pattern. Th

Temporal Consistency Improves Generalization in Contextual Offline Meta Reinforcement Learning

arXiv:2603.02935v2 Announce Type: replace Abstract: Offline meta-reinforcement learning seeks to learn a policy that generalizes to new related tasks online. Context-based methods infer a task represe

Test-Time Weak-to-Strong Alignment: Transferring Implicit Rewards from Weak to Strong Flow Models

arXiv:2609.05968v1 Announce Type: new Abstract: Aligning a text-to-image generation flow model with a reward makes it follow objectives that the training data alone does not provide. Alignment fine-tu

TFTrack: A Template-Free Framework for Efficient 3D Point Cloud Tracking

arXiv:2609.07738v1 Announce Type: new Abstract: LiDAR-based 3D Single Object Tracking (3D SOT) is critical for robotic perception and navigation and aims to localize dynamic objects across frames in s

The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation

arXiv:2609.08901v1 Announce Type: new Abstract: Approximate machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. We identify

Model Releases

The Price of Consistency: Exploiting Visual Anchors for Multimodal Jailbreaking in Video Generation

model-releasesarxiv-cs-cv

arXiv:2609.07216v1 Announce Type: new Abstract: The rapid evolution of video generation has shifted the paradigm from pure text-driven to multi-conditional controllable generation, with reference imag

The Role of Uncertainty in Assessing the Fairness of Machine Learning Models

arXiv:2609.07959v1 Announce Type: cross Abstract: Machine learning models are widely used in clinical applications, social media, law enforcement and critical infrastructure. Verifying whether their o

Thinking with Cameras: Active Visual Reasoning via Dynamic Viewpoint Control for Surveillance Video Understanding

arXiv:2609.06475v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have recently achieved remarkable progress in general-purpose video understanding. However, their application to su

ThinkPrior: Zero-Rollout Difficulty Priors for Cold-Start Prompt Selection in RLVR

arXiv:2609.09075v1 Announce Type: new Abstract: In reinforcement learning with verifiable rewards (RLVR) trained with group relative policy optimization (GRPO), the KL-free reward-advantage term studi