Search: “safety”

SEAD: Competence-Aware On-Policy Distillation via Entropy-Guided Supervision

arXiv:2606.28562v1 Announce Type: new Abstract: On-policy distillation (OPD) has a property absent in offline distillation and RL: teacher supervision quality depends on student competence. Incoherent

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Seeing Touch from Motion: A Unified Modality-Aware Visuo-Tactile Policy with Tactile Motion Correlation

DGX agent

arXiv:2606.29941v1 Announce Type: cross Abstract: Visuo-Tactile policies leveraging optical tactile sensors have shown great promise in contact-rich manipulation. These sensors achieve high spatial re

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30 Jun 2026

Sequential Fairness Auditing with Limited Output Access

arXiv:2606.30338v1 Announce Type: new Abstract: External evaluations are becoming increasingly central to the governance of AI systems. In practice, however, independent auditors often have limited ac

SGD Provably Prioritizes a Shortcut Spurious Feature in the XOR Model

arXiv:2606.30444v1 Announce Type: cross Abstract: Neural networks are known to be susceptible to over-reliance on spurious correlations. However, the precise mechanism by which models exploit shortcut

SIR: Structured Image Representations for Explainable Robot Learning

arXiv:2606.30101v1 Announce Type: cross Abstract: Existing robot policies based on learned visual embeddings lack explicit structure and are sensitive to visual distractions. Thus, the representations

SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport

arXiv:2602.23353v2 Announce Type: replace-cross Abstract: The Platonic Representation Hypothesis posits that neural networks trained on different modalities converge toward a shared statistical model

SP-CACW: Convergence-Aware Client Weighting for Selfish Personalized Learning

arXiv:2606.29322v1 Announce Type: new Abstract: Collaborative learning is sustainable only when it benefits each participant. Standard federated learning optimizes a global average objective, which ca

SPARC: Scalable Path-Specific Counterfactual Fairness via Causal Conditional Independence

arXiv:2412.04739v2 Announce Type: replace Abstract: Deep learning models exhibit fairness concerns when predictions are inadvertently influenced by sensitive attributes. However, existing attempts to

SpecMind: Cognitively Inspired, Interactive Multi-Turn Framework for Postcondition Inference

arXiv:2602.20610v3 Announce Type: replace-cross Abstract: Specifications are vital for ensuring program correctness, yet writing them manually remains challenging and time-intensive. Recent large lang

Spectral phase transitions and trainability in neural network learning dynamics

arXiv:2606.28486v1 Announce Type: cross Abstract: The emergence of low-dimensional structures in the spectra of neural network weight matrices is a common empirical feature of trained models, but the

Sphere-VIO: Fast and Robust Visual-Inertial Odometry via Unified Spherical Representation for Heterogeneous Multi-Camera Systems

arXiv:2606.29910v1 Announce Type: new Abstract: Multi-camera visual-inertial odometry (VIO) overcomes the inherent limitations of pure visual systems by expanding the field of view. However, existing

SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models

arXiv:2510.12784v2 Announce Type: replace-cross Abstract: Recently, remarkable progress has been made in Unified Multimodal Models (UMMs), which integrate vision-language generation and understanding

StackingNet: Collective Inference Across Independent AI Foundation Models

arXiv:2602.13792v2 Announce Type: replace Abstract: Artificial intelligence built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems r

Staged Hybridisation for Visual Quantum Reinforcement Learning via Knowledge Distillation

arXiv:2606.30520v1 Announce Type: cross Abstract: Visual environments are a demanding setting for quantum reinforcement learning (QRL): high-dimensional observations, unstable RL optimisation, and con

STEAM: Self-Supervised Temporal Ensemble Advantage Modeling for Real-World Robot Learning

arXiv:2606.29834v1 Announce Type: new Abstract: Real-world robot learning increasingly relies on heterogeneous data, but demonstrations and rollouts often mix useful progress with stalls, corrections,

Structure-Preserving Document Translation via Multi-Stage LLM Pipeline: A Case Study in Marathi

arXiv:2606.28796v1 Announce Type: new Abstract: Government documents in India are predominantly issued in regional languages such as Marathi, creating substantial accessibility barriers for non-native

TacGen: Touch Is a Necessary Dimension of Physical-World Representation -- Addressing Tactile Data Scarcity with Scalable Vision-to-Touch Alignment and Generation

arXiv:2606.29173v1 Announce Type: new Abstract: Touch resolves the physical-property ambiguity left by vision: exploratory contact recovers shape, texture, compliance, and material, and visuo-haptic o

TAP-VLA: Tactile Annotation Prompting for Vision Language Action Models

arXiv:2606.29089v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models demonstrate impressive reasoning over visual, semantic, and spatial task variations by leveraging large-scale vision

TERC: A Transfer Entropy Redundancy Criterion for State Variable Selection in Reinforcement Learning

arXiv:2401.11512v2 Announce Type: replace-cross Abstract: Identifying the most suitable variables to represent the state is a fundamental challenge in Reinforcement Learning (RL). These variables must

TerraDiT: Point-Conditioned Diffusion Transformer for Satellite Image Synthesis

arXiv:2603.02172v2 Announce Type: replace Abstract: We introduce TerraDiT, a diffusion transformer designed for text-to-satellite image generation with point-based control. Existing controlled satelli

The Crowded Embedding Space: A Mean-Field Mechanism for Emergent Marginalization in Retrieval-Augmented Agents

arXiv:2606.28343v1 Announce Type: cross Abstract: Retrieval-augmented generative agents rely on retrieval for grounding, yet are typically evaluated on a query-by-query basis. This isolates interactio

The Mirage of Optimizing Training Policies: Monotonic Inference Policies as the Real Objective for LLM Reinforcement Learning

arXiv:2606.29526v1 Announce Type: new Abstract: Reinforcement learning (RL) has gained growing attention in large language model (LLM) post-training, yet RL training remains fragile and can suffer fro

The Two Genie Game: Adoption and Welfare in Audit-Grounded AI Governance

arXiv:2606.28710v1 Announce Type: new Abstract: We ask under what conditions an agent with a harm-minimizing policy can displace an approval-seeking (RLHF) agent in a competitive market, and when that

Theory of Continual Learning Against Data Poisoning Attacks

arXiv:2606.29841v1 Announce Type: new Abstract: Continual learning (CL), where a model is trained on a sequence of data tasks, is increasingly being adopted across key fields such as large language mo

Timesteps of Mamba Align with Human Reading Times

arXiv:2606.29904v1 Announce Type: new Abstract: This study demonstrates an alignment of per-word processing time in a popular state-space language model Mamba and human readers. In Mamba, the recurren

To Use or not to Use Muon: How Simplicity Bias in Optimizers Matters

arXiv:2603.00742v2 Announce Type: replace Abstract: While Adam has long been the ubiquitous default optimizer for deep neural networks, Muon has recently seen rapid adoption due to its superior traini

Towards Physical Intuitions for Alignment Dynamics: A Case Study With Randomness Crystallization

arXiv:2606.29933v1 Announce Type: new Abstract: The alignment of language models is typically studied through the lens of capability benchmarks, but the dynamics of how models change during post-train

TrafficAlign: Aligning Large Language Models for Traffic Scenario Generation

arXiv:2606.29097v1 Announce Type: new Abstract: Recent research has investigated the use of large language models (LLMs) to generate traffic scenarios for autonomous driving. However, pretrained LLMs

Transformer-Based Active Learning for Data-Efficient Vaccine Epitope Selection in PRRS

arXiv:2606.28659v1 Announce Type: cross Abstract: High-fidelity molecular docking simulations can produce biologically relevant estimates of epitope-receptor binding affinity but are computationally e

Trust Your Instincts: Confidence-Driven Test-Time RL for Vision-Language-Action Models

arXiv:2606.29892v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become indispensable for pushing Vision-Language-Action Models (VLAs) beyond static imitation learning. However, exist

Uncovering Salience-Driven Dynamics in Consumer Confidence with Generative Social Simulation

arXiv:2606.30395v1 Announce Type: cross Abstract: Consumer confidence is typically modeled as a persistent macroeconomic index, yet its movements arise from households that interpret economic informat

UniGP: Taming Diffusion Transformer for Prior-Preserved Unified Generation and Perception

arXiv:2606.30332v1 Announce Type: new Abstract: Recent advances in diffusion models have shown impressive performance in controllable image generation and dense prediction tasks. However, existing app

UniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation

arXiv:2603.22282v2 Announce Type: replace-cross Abstract: We present UniMotion, to our knowledge the first unified framework for simultaneous understanding and generation of human motion, natural lang

Using Large Language Models as Low-Cost Statistical Estimators for Human-Response Data

arXiv:2606.30372v1 Announce Type: new Abstract: Quantitative research across the social and behavioral sciences depends on human subject experiments that are expensive, slow, and subject to sampling b

Value-Action Alignment in Large Language Models under Privacy-Prosocial Conflict

arXiv:2601.03546v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to simulate decision-making tasks involving personal data sharing, where privacy concerns a

Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs

arXiv:2606.28401v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong performance in visual understanding, yet they still suffer from hallucinations, generating content that

Vision-Language-Action Models: Experimental Insights from a Real-World UR5 Platform

arXiv:2606.30456v1 Announce Type: cross Abstract: This project investigates whether recent Vision-Language-Action (VLA) models can be transferred from controlled research benchmarks to a real-world ro

Vivid-VR: Distilling Concepts from Text-to-Video Diffusion Transformer for Photorealistic Video Restoration

arXiv:2508.14483v4 Announce Type: replace Abstract: We present Vivid-VR, a DiT-based generative video restoration method built upon an advanced T2V foundation model, where ControlNet is leveraged to c

VLK: Learning Humanoid Loco-Manipulation from Synthetic Interactions in Reconstructed Scenes

arXiv:2606.30645v1 Announce Type: cross Abstract: Perception-based humanoid loco-manipulation requires connecting egocentric observations and task instructions to whole-body motion. Learning this mapp

VLOD-TTA: Test-Time Adaptation of Vision-Language Object Detectors

arXiv:2510.00458v3 Announce Type: replace Abstract: Vision-language object detectors (VLODs) such as YOLO-World and Grounding DINO exhibit strong zero-shot generalization, but their performance degrad

When Does Online Imitation Learning Help in LLM Post-Training? The Role of (Non-)Realizability Beyond Horizon

arXiv:2606.30445v1 Announce Type: new Abstract: Online imitation learning (IL), particularly on-policy distillation, has emerged as a strong LLM post-training approach, often outperforming offline sup

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection

arXiv:2606.30587v1 Announce Type: cross Abstract: Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs a

WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL

arXiv:2602.13977v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) promises to unlock capabilities beyond imitation learning for Vision--Language--Action (VLA) models, but its requi

X-Mind: Efficient Visual Chain-of-Thought via Predictive World Model for End-to-End Driving

arXiv:2606.28758v1 Announce Type: cross Abstract: Predicting future states is essential for autonomous agents, yet current Vision-Language-Action (VLA) models fundamentally lack this capability, relyi

X-Morph: Human Motion Priors for Scalable Robot Learning Across Morphologies

arXiv:2606.30290v1 Announce Type: new Abstract: Recent progress in humanoid behavior models has been driven in large part by abundant human motion data, but comparable motion data is scarce for non-hu

X-Tokenizer: A Multimodal Action Tokenizer for Vision-Language-Action Pretraining

arXiv:2606.14752v2 Announce Type: replace-cross Abstract: Modern Vision-Language-Action (VLA) models must bridge pretrained vision-language reasoning and precise continuous robot control. Existing act

Agent-Native Immune System: Architecture, Taxonomy, and Engineering

arXiv:2606.28270v1 Announce Type: new Abstract: The transition from static chat bots to autonomous agents--equipped with persistent memory, tool-use protocols, and multi-agent collaboration--has funda

29 Jun 2026

ATOD: Annealed Turn-aware On-policy Distillation for Multi-turn Autonomous Agents

arXiv:2606.27814v1 Announce Type: new Abstract: Training small language-model agents for long-horizon interactive tasks requires both fast imitation and reward-driven improvement. On-policy distillati