Search: “safety”

Breaking the Information Silo: Semantic Personas for Cross-Domain Recommendation

arXiv:2606.01783v1 Announce Type: cross Abstract: Digital platforms increasingly operate as isolated information silos, limiting their ability to construct comprehensive user representations across do

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Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge

DGX agent

arXiv:2602.02470v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) have achieved remarkable success in many complex tasks, yet they can still fail in very simple logical r

safetyarxiv-cs-ai

2 Jun 2026

Bridging Reasoning Trajectories in On-Policy Distillation via Near-Future Guidance

arXiv:2606.00305v1 Announce Type: cross Abstract: On-Policy Distillation (OPD) improves large language model reasoning by training a student model on trajectories sampled from its own policy under tea

Calibrating Uncertainty for Zero-Shot Adversarial CLIP

arXiv:2512.12997v2 Announce Type: replace-cross Abstract: CLIP delivers strong zero-shot classification but remains highly vulnerable to adversarial attacks. Prior adversarial fine-tuning work primari

Can AI Review Improve Paper Drafting? An Empirical Study on 20 Computer Architecture Submissions

arXiv:2606.01013v1 Announce Type: new Abstract: Research is advancing faster than ever with artificial intelligence (AI); and so are the corresponding research papers. The exploding volume of AI-gener

CanonCGT: Reference-Based Color Grading via Canonical Pivot Representation

arXiv:2606.01638v1 Announce Type: new Abstract: Reference-based color grading aims to reproduce the tonal mood and lighting of a reference while preserving color harmony and scene structure. Existing

CAPF: Guiding Search-Agent Rollouts with Credit-Attenuated Privileged Feedback

arXiv:2606.01830v1 Announce Type: new Abstract: Recent LLM search agents use reinforcement learning with verifiable rewards (RLVR) to learn search-augmented reasoning from outcome rewards. On hard pro

CAST: Non-Privileged Clipped Asymmetric Self-Teaching with Advantage Flipping for GRPO

arXiv:2606.00172v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR), especially Group Relative Policy Optimization (GRPO), has been widely used to improve reasoning i

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

Chaining 2-FWL GNNs for Combinatorial Graph Alignment

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

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

safetyarxiv-cs-ro

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

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

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

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

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

safetyarxiv-cs-ro

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

safetyarxiv-cs-ro

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

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

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

EMoE: Training-Free Expert Disagreement for Uncertainty-Aware Text-to-Image Diffusion

arXiv:2505.13273v2 Announce Type: replace Abstract: Large text-to-image diffusion models rarely expose reliable signals of when a prompt is likely to produce a poorly aligned generation, especially wh

Entropy Minimization without Model Collapse: Mitigating Prediction Bias in Medical Imaging

arXiv:2606.02339v1 Announce Type: cross Abstract: Entropy minimization (EM) is the dominant objective for test-time adaptation, yet its failure mode, model collapse, remains poorly understood. In this