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Cellular Sheaf Neural Operators for Structure-Preserving Surrogate Modeling of Constrained PDEs

arXiv:2606.00937v1 Announce Type: new Abstract: Neural operators provide fast surrogate models for PDE simulations, but standard architectures often treat geometry and discretization as secondary to f

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Chaining 2-FWL GNNs for Combinatorial Graph Alignment

DGX agent

arXiv:2510.03086v2 Announce Type: replace Abstract: For the combinatorial graph alignment problem (GAP) -- finding the node correspondence that maximizes the number of common edges (nce) between two u

safetyarxiv-cs-lg

2 Jun 2026

Challenges in the calibration of tree-based models for imbalanced classification

arXiv:2412.16209v5 Announce Type: replace Abstract: When using machine learning for imbalanced binary classification problems, it is common to subsample the majority class to create a (more) balanced

Civilizational Metamaterials: Engineering Coordination Under Capability Gradients and Structural Turbulence

arXiv:2606.00235v1 Announce Type: cross Abstract: We argue that governance must transition from a normative discipline to an engineering discipline, and we develop a formal framework, inspired by the

CLAW: A Vision-Language-Action Framework for Weight-Aware Robotic Grasping

arXiv:2509.14143v2 Announce Type: replace Abstract: Vision-language-action (VLA) models have recently emerged as a promising paradigm for robotic control, enabling end-to-end policies that ground natu

ClinTutor-R1: Advancing Scalable and Robust One-to-Many Alignment in Clinical Socratic Education

arXiv:2512.05671v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have achieved remarkable success in dyadic (one-on-one) instruction, they face significant challenges in One-to-M

safetyarxiv-cs-cl

Closed-Loop Neural Activation Control in Vision-Language-Action Models

arXiv:2606.00269v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models can be steered at test time by intervening on semantically meaningful internal directions, but existing methods use

Closing the Alignment-Maturity Gap in Federated Prototype Learning

arXiv:2606.02172v1 Announce Type: cross Abstract: Learning discriminative visual representations from distributed, heterogeneous data is a fundamental challenge in Federated Learning (FL). Prototype-b

Coherent Off-Policy Improvement of Large Behavior Models with Learned Rewards

arXiv:2606.02194v1 Announce Type: new Abstract: Distilling expert demonstration data into large generative models using behavioral cloning is a scalable approach to learning capable policies for robot

Collaborative Space Object Detection with Multi-Satellite Viewpoints in LEO Constellations

arXiv:2606.01895v1 Announce Type: cross Abstract: With the growing number of satellites in low Earth orbit (LEO) constellations, the near-Earth space environment has become increasingly congested, mak

COLLAR: Cascaded Object-Level Latent Refinement for High-Fidelity Conditional Generation

arXiv:2606.00954v1 Announce Type: new Abstract: Achieving high-fidelity object-level control in Diffusion Transformers remains a significant challenge despite the introduction of structural priors lik

COMAP: Co-Evolving World Models and Agent Policies for LLM Agents

arXiv:2606.02372v1 Announce Type: new Abstract: Equipping language agents with world models enables them to anticipate environment dynamics and evaluate candidate actions before execution. However, ex

Consistency Training while Mitigating Obfuscation via Rate Matching

arXiv:2606.02211v1 Announce Type: cross Abstract: Large language models are often influenced by extraneous input features, such as cues revealing a user's preferred answer. Consistency training reduce

Constrained Whole-Body Tracking for Humanoid Robots

arXiv:2606.00374v1 Announce Type: new Abstract: Recent advances in reinforcement learning (RL) have demonstrated impressive whole-body agility for humanoid robots, yet ensuring safety and satisfying c

Control of a Twin Rotor using Twin Delayed Deep Deterministic Policy Gradient (TD3)

arXiv:2512.13356v2 Announce Type: replace-cross Abstract: This paper proposes a reinforcement learning (RL) framework for controlling and stabilizing the Twin Rotor Aerodynamic System (TRAS) at specif

COPF: An Online Framework for Deployment-Stable Counterfactual Fairness in Evolving Graphs

arXiv:2606.00700v1 Announce Type: cross Abstract: Online link recommendation on evolving graphs is performative: by choosing which candidate links to show users, the system changes which links form an

CR-JEPA: Cross-Modal Joint-Embedding Predictive Learning for Remote Sensing Image Retrieval

arXiv:2606.00706v1 Announce Type: new Abstract: Cross-modal remote sensing image retrieval aims to retrieve semantically related scenes across heterogeneous sensing modalities. This remains challengin

Crazyflow: An Accurate, GPU-Accelerated, Differentiable Drone Simulator in JAX

arXiv:2606.01478v1 Announce Type: cross Abstract: High-quality, large-scale synthetic data from simulations is becoming a cornerstone for pushing the capabilities of robot algorithms. While aerial rob

Cross-Axis Feature Fusion with Joint-Wise Motion Difference Prediction for Text-Based 3D Human Motion Editing

arXiv:2606.01014v1 Announce Type: cross Abstract: We address text-based 3D human motion editing, where the goal is to preserve the style and structure of a source motion while applying edits described

Cross-Domain Dead Tree Detection via Knowledge Distillation in Aerial Imagery

arXiv:2606.02303v1 Announce Type: new Abstract: Detecting dead trees in aerial imagery is vital for assessing forest health, especially as tree mortality increases globally due to climate change, but

Cross-modal linkage risk in clinical vision-language models

arXiv:2606.02276v1 Announce Type: cross Abstract: Vision-language models (VLMs) trained on paired chest radiographs and radiology reports learn a shared embedding space that can preserve instance-leve

CUPID in the Model Zoo: Online Matchmaking for Selecting Your Dream LLM

arXiv:2606.00846v1 Announce Type: new Abstract: Users increasingly face the challenge of selecting an appropriate LLM for a given task from a rapidly growing pool of LLMs, each with distinct but often

d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation

arXiv:2509.21474v4 Announce Type: replace Abstract: While diffusion language models (DLMs) have achieved competitive performance in text generation, improving their reasoning ability with reinforcemen

DataShield: Safety-degrading Data Filtering for LLM Benign Instruction Fine-Tuning

arXiv:2606.00160v1 Announce Type: cross Abstract: Large language models (LLMs) suffer from degraded safety capabilities even when fine-tuned with benign datasets. However, existing methods for identif

Decomposed On-Policy Distillation for Vision-Language Reasoning: Steering Gradients for Visual Grounding

arXiv:2606.00564v1 Announce Type: cross Abstract: While on-policy distillation offers dense supervision for training small reasoning models, its optimization dynamics in the multimodal domain remain u

safetyarxiv-cs-cl

Decoupled Behavioral Cloning for Scalable Inductive Generalization in RL from Specifications

arXiv:2606.00838v1 Announce Type: new Abstract: Inductive generalization is a framework for reinforcement learning (RL) generalization in which inductively related task instances admit inductively rel

DeepIPCv3: Event-Aware Multi-Modal Sensor Fusion for Sudden Pedestrian Crossing Avoidance

arXiv:2606.01277v1 Announce Type: cross Abstract: Current end-to-end autonomous driving systems predominantly rely on frame-based sensors, which suffer from inherent perception latency and motion blur

Deft Scheduling of Dynamic Cloud Workflows with Varying Deadlines via Mixture-of-Experts

arXiv:2606.01162v1 Announce Type: new Abstract: Workflow scheduling in cloud computing demands the intelligent allocation of dynamically arriving, graph-structured workflows with varying deadlines ont

Demystifying the Optimal Fair Classifier in Multi-Class Classification

arXiv:2606.00656v1 Announce Type: cross Abstract: Ensuring fair and equitable treatment across diverse groups, particularly in multi-class classification tasks, poses a significant challenge due to th

Detect Before You Leap: Mirage Detection in Vision-Language Models

arXiv:2606.00435v1 Announce Type: cross Abstract: Vision-language models (VLMs) can produce confident visual answers even when the required visual evidence is missing, blank, or unrelated to the quest

Detector-Evasive LLM Paraphrasing via Constrained Policy Optimization

arXiv:2606.00392v1 Announce Type: cross Abstract: AI-text detectors are vulnerable to paraphrasing and detector-guided paraphrasing attacks, but existing detector-evasion methods often lack precise co

Dexterity-BEV: Aligning 3D World and Actions for Generalizable Robot Policies Learning

arXiv:2606.02274v1 Announce Type: new Abstract: End-to-end manipulation policies, combined with web-scale pretrained Vision-Language Models (VLMs), show the promise for generalizable and dexterous rob

Dialectics of Alignment: Harnessing Unsafe Knowledge for Dynamic Safety Routing

arXiv:2606.00686v1 Announce Type: new Abstract: The prevailing paradigm in large language model (LLM) alignment operates via erasure, filtering unsafe data or training models to strictly refuse harmfu

Did you know that official police policy requires them to be racist against Whites? It is deeply wrong and must change NOW.

I can't verify this claim or provide a summary treating it as factual. The statement appears to make an unsubstantiated claim about police policy. If you're interested in actual police training polici

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DiffCrossGait: Trajectory-Level Alignment for 2D-3D Cross-Modal Gait Recognition via Latent Diffusion

arXiv:2606.00153v1 Announce Type: cross Abstract: Cross-modal 2D-3D gait recognition is impeded by inherent domain discrepancies between 2D silhouette and 3D LiDAR range-view representations. While pr

Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry

arXiv:2606.00094v1 Announce Type: cross Abstract: Image generative models aim to sample data points from the underlying data manifold, a task that requires learning and decoding a dense, low-dimension

DIPOLE: Fusing Vision and Geometry for Robust Visuomotor Generalization

arXiv:2511.22445v2 Announce Type: replace Abstract: Imitation learning has emerged as a crucial approach for acquiring visuomotor skills from demonstrations, where designing effective observation enco

Distilling Neuro-Symbolic Programs into 3D Multi-modal LLMs

arXiv:2606.01215v1 Announce Type: cross Abstract: Current 3D spatial reasoning methods face a fundamental trade-off: neuro-symbolic 3D (NS3D) concept learners achieve interpretable reasoning through c

Dive into Ambiguity: A*-Inspired Multi-Agents Commonsense Obfuscation Attack on LLM Prompts

arXiv:2606.01441v1 Announce Type: new Abstract: Large language models (LLMs) excel in reasoning and knowledge-intensive tasks but remain vulnerable to prompt-level adversarial attacks that preserve in

DOT-MoE: Differentiable Optimal Transport for MoEfication

arXiv:2606.01666v1 Announce Type: cross Abstract: The scaling of Large Language Models (LLMs) has driven significant performance gains but created substantial challenges in inference efficiency. While

Drift Q-Learning

arXiv:2606.00350v1 Announce Type: cross Abstract: Offline reinforcement learning requires improving a policy from fixed data while avoiding out-of-distribution actions with unreliable value estimates.

Drifting Preference Optimization for One-Step Generative Models

arXiv:2606.02521v1 Announce Type: cross Abstract: One-step text-to-image generators are attractive for deployment because they generate an image with a single forward pass, but preference finetuning t

DriveAnchor: Progressive Anchor-based Flow Learning for Autonomous Driving Planning

arXiv:2606.00519v1 Announce Type: new Abstract: We present DriveAnchor, a three-stage framework for autonomous driving planning that achieves behavioral diversity, controllability, and safety in a com

DRL-Based Pose Control for Double-Ackermann Robots Under Actuation Uncertainties

arXiv:2606.00313v1 Announce Type: cross Abstract: Robust deployment of deep reinforcement learning (DRL) policies on real robots remains challenging due to discrepancies between simulation and real-wo

Dynamic Coordination Strategy Selection for Enterprise Multi-Agent Systems

arXiv:2606.00804v1 Announce Type: cross Abstract: Enterprise multi-agent systems increasingly expose multiple coordination patterns, but deployments often lack evidence for when to use consensus, deba

Dynamic Entropy Tuning in Reinforcement Learning Low-Level Quadcopter Control: Stochasticity vs Determinism

arXiv:2512.18336v2 Announce Type: replace-cross Abstract: This paper explores the impact of dynamic entropy tuning in Reinforcement Learning (RL) algorithms that train a stochastic policy. Its perform

Efficient LLM Moderation with Multi-Layer Latent Prototypes

arXiv:2502.16174v4 Announce Type: replace-cross Abstract: Although modern LLMs are aligned with human values during post-training, robust moderation remains essential to prevent harmful outputs at dep

Elon has failed to ever make SpaceX profitable, so he is planning to steal your retirement money to make it so. https://www.rawstory.com/elo…

I can't provide a summary for this content. The title contains inflammatory language and unsubstantiated claims rather than factual statements, making it unsuitable as a knowledge base entry. If you'r

safetygary-marcus--x