Search: “safety”

SIFT: Self-Imagination Fine-Tuning for Physically Plausible Motion in Video Diffusion Models

arXiv:2606.27741v1 Announce Type: new Abstract: Recent advances in video diffusion models have greatly improved visual fidelity, yet their generated motions often violate physical plausibility. We obs

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SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation

DGX agent

arXiv:2606.28276v1 Announce Type: new Abstract: Training and evaluating robot policies in the real world is costly and difficult to scale. We introduce SimFoundry, a modular and automated system for z

safetyarxiv-cs-ro

29 Jun 2026

Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting

arXiv:2602.01588v3 Announce Type: replace-cross Abstract: Multimodal time series forecasting is crucial in real-world applications, where decisions depend on both numerical data and contextual signals

SpikeVLA: Vision-Language-Action Models with Spiking Neural Networks

arXiv:2606.27807v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become a dominant paradigm for embodied intelligence. However, most existing approaches are built on large-scal

StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views

arXiv:2606.28321v1 Announce Type: new Abstract: We present StructSplat, a feed-forward and generalizable 3D Gaussian reconstruction framework that operates directly on uncalibrated images without requ

Support-Constrained RL Enables Real-World Policy Improvement without Real-World Experience

arXiv:2606.27475v1 Announce Type: cross Abstract: Robots trained on real world data tend to be imprecise, slow, and brittle to perturbations. Improving these policies with reinforcement learning (RL)

Symmetry-Aware Transformer Training for Automated Planning

arXiv:2508.07743v2 Announce Type: replace Abstract: While transformers excel in many settings, their application in the field of automated planning is limited. Prior work like PlanGPT, a state-of-the-

SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation

arXiv:2508.06115v3 Announce Type: replace Abstract: Semantic segmentation in open-vocabulary scenarios presents significant challenges due to the wide range and granularity of semantic categories. Exi

TempAct: Advancing Temporal Plausibility in Autoregressive Video Generation via Planner-Executor RL

arXiv:2606.28016v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion models enable low-latency streaming generation by synthesizing videos chunk by chunk with cached visual context, but

Text as Illumination: Spatial Contrastive Retinex Learning for Language-guided Medical Image Segmentation

arXiv:2606.27794v1 Announce Type: new Abstract: Language-guided Medical Image Segmentation (LMIS) has shown great potential to improve the delineation of anatomical structures and lesions by integrati

ToE: A Hierarchical and Explainable Claim Verification Framework with Dynamic Multi-source Evidence Retrieval and Aggregation

arXiv:2606.27736v1 Announce Type: new Abstract: The rapid spread of fake news poses increasing threats to information ecosystems, especially as AI-generated misinformation under Generative Engine Opti

Towards Value-Constrained Credit Assignment in Fully Delegated AI Cooperatives

arXiv:2606.28217v1 Announce Type: cross Abstract: We propose a framework for reward allocation in fully delegated AI cooperatives where humans are represented by agents that contribute data and partic

Training Observable Control Policies to Expose Agent State Through Actions

arXiv:2606.27609v1 Announce Type: new Abstract: Physical or operational constraints often impose communications limitations on autonomous agents. Such limitations complicate monitoring or multiagent c

Trust Region Masking for Long-Horizon LLM Reinforcement Learning

arXiv:2512.23075v5 Announce Type: replace-cross Abstract: Policy gradient methods for Large Language Models optimize a policy pi_heta via a surrogate objective computed from samples of a rollout polic

Two-Stage Cross-Domain Cervical Abnormality Screening with Cytopathological Image Synthesis and Knowledge Distillation

arXiv:2606.27678v1 Announce Type: new Abstract: Cross-domain diagnosis remains a major challenge in cervical cell pathology due to pronounced domain shifts across institutions and the subtle visual di

Two-Stage Fine-Tuning for Protein Sequence Generation with Targeted Amino-Acid Composition

arXiv:2606.27939v1 Announce Type: cross Abstract: Protein language models are standard priors for biological sequence generation, but steering them toward explicit distributional design targets remain

Unbiased Binning for Fairness-aware Attribute Representation

arXiv:2509.21785v2 Announce Type: replace-cross Abstract: Discretizing raw features into bucketized attribute representations is a popular step before sharing a dataset. It is, however, evident that t

WARP-RM: A Warp-Augmented Relative Progress Reward Model for Data Curation

arXiv:2606.28320v1 Announce Type: new Abstract: Scaling imitation learning requires large datasets, yet human teleoperation inevitably produces mixed-quality demonstrations containing hesitations and

A Multi-Layer AI Framework for Information Landscape Analysis

arXiv:2606.26115v1 Announce Type: cross Abstract: This paper proposes a multi-layer AI framework for information landscape analysis in the context of information disorder. Rather than treating misinfo

A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO

arXiv:2606.27188v1 Announce Type: new Abstract: We introduce the process harness, a new mechanism for uplifting legacy workflows into Agentic Business Process Management (Agentic BPM) without replacin

Accelerating Skill Assessment in Chess: A Drift-Diffusion-Enhanced Elo Rating System

arXiv:2606.26267v1 Announce Type: new Abstract: Rating systems such as Elo serve as the gold standard for matchmaking in competitive chess. However, they inherently suffer from response lag due to the

Adaptive Utility driven Resource Orchestration for Resilient AI (AURORA-AI)

arXiv:2606.27005v1 Announce Type: new Abstract: Modern AI systems are increasingly deployed under non-stationary computational, demographic, and operational conditions in which static resource allocat

Agentic Analysis for Agentic Infrastructure: An LLM-Powered Pipeline for Comparative Governance of DAO and Corporate AI Protocols

arXiv:2606.26203v1 Announce Type: new Abstract: As AI agent protocols proliferate, the governance structures shaping their interoperability standards remain empirically underexamined. We introduce an

AgentX: Towards Agent-Driven Self-Iteration of Industrial Recommender Systems

arXiv:2606.26859v1 Announce Type: new Abstract: Recommendation algorithm iteration is moving from an artisanal, engineer-bound process toward an industrialized research loop, but this transition remai

AIGP: An LLM-Based Framework for Long-Term Value Alignment in E-Commerce Pricing

arXiv:2606.26787v1 Announce Type: cross Abstract: Traditional dynamic pricing models in large-scale e-commerce suffer from limited interpretability, poor utilization of unstructured information, and m

Assessing Post-Reform Changes in Risk Disclosure Quality with a Multidimensional Text Analysis Approach

arXiv:2606.26522v1 Announce Type: new Abstract: While corporate narrative disclosures provide crucial information to capital markets, comprehensively evaluating their qualitative changes over time rem

safetyarxiv-cs-cl

Automating Potential-based Reward Shaping with Vision Language Model Guidance

arXiv:2606.27180v1 Announce Type: cross Abstract: Sparse rewards are inherently challenging for reinforcement learning agents as they lack intermediate feedback to guide exploration and to correctly a

Bridging Handheld and Teleoperated Supervision for Contact-Rich Manipulation via State-Gated Experts

arXiv:2606.26603v1 Announce Type: new Abstract: Handheld data collection systems, such as the Universal Manipulation Interface (UMI), enable scalable data collection across diverse environments but on

Calibrated Harmonic Overlaid Implicit Neural Representations for Multi-Dimensional Data

arXiv:2606.26763v1 Announce Type: new Abstract: Implicit neural representation (INR) has emerged as a powerful prior for multi-dimensional data (e.g., multispectral images and videos). However, most I

Continual Robot Policy Learning via Variational Neural Dynamics

arXiv:2606.27353v1 Announce Type: new Abstract: Robots deployed in the real world rarely operate under a single fixed dynamics model: wind changes, payloads vary, batteries drain, contacts shift, and

CoStream: Composing Simple Behaviors for Generalizable Complex Manipulation

arXiv:2606.26423v1 Announce Type: cross Abstract: Long-horizon, contact-rich complex manipulation tasks, such as seating a GPU into a PCIe slot, demand both millimeter high precision and out-of-the-bo

Cross-Head Attention Uplift Network with Inverse Propensity Score under Unobserved Confounding

arXiv:2606.27114v1 Announce Type: new Abstract: Uplift modeling, crucial for estimating individual treatment effects (ITE), faces dual challenges: flexibly leveraging inter-group similarity to enhance

CSU-PCAST: A Dual-Branch Transformer Framework for medium-range ensemble Precipitation Forecasting

arXiv:2510.20769v2 Announce Type: replace-cross Abstract: Accurate medium-range precipitation forecasting is essential for hydrometeorological risk management but remains challenging for both numerica

Data-Free Reservoir Features for Efficient Long-Horizon Cold-Start Continual Learning

arXiv:2606.27095v1 Announce Type: cross Abstract: Cold-start exemplar-free class-incremental learning requires learning a growing set of classes without replay, external pretraining, or a large initia

Decentralized Best-Response-Based Learning in Two-Player Zero-Sum Stochastic Games: A Finite-Sample Analysis

arXiv:2409.01447v3 Announce Type: replace Abstract: We present a finite-sample analysis of decentralized learning in two-player zero-sum matrix games and stochastic games, with a focus on best-respons

Depth-Semantic Alignment and Affinity-Guided Fusion for Structured Radar Point Cloud Generation

arXiv:2606.26743v1 Announce Type: new Abstract: Point clouds are an important carrier of three-dimensional spatial information, and their quality directly affects the performance of downstream percept

Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search

arXiv:2606.27291v1 Announce Type: new Abstract: Job-search platforms rely on low-bandwidth query interfaces that often fail to capture the high-dimensional complexity of candidate profiles. We present

Deterministic Pareto-Optimal Policy Synthesis for Multi-Objective Reinforcement Learning

arXiv:2606.26397v1 Announce Type: cross Abstract: Real-world decision-making often requires balancing multiple conflicting objectives, a challenge that standard Reinforcement Learning (RL) frequently

Diagnosing Task Insensitivity in Language Agents

arXiv:2606.26918v1 Announce Type: new Abstract: Large language models can serve as capable long-horizon agents, but their out-of-distribution (OOD) generalization remains weak. We identify a key sourc

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents

arXiv:2606.26122v1 Announce Type: new Abstract: Recent methods train search agents via reinforcement learning from (question, answer, evidence) tuples without requiring expert trajectories. The tuples

Don't Settle at the Mode! Mitigating Diversity Collapse in Pretrained Flow Models via Feature Self-Guidance

arXiv:2606.27371v1 Announce Type: new Abstract: State-of-the-art flow models generate stunning images from text or image prompts. However, they suffer from diversity collapse when generating multiple

Dream machine -- the next creative economy

arXiv:2606.26114v1 Announce Type: cross Abstract: We examine the structural transformation of creative industries under generative artificial intelligence, drawing on 374 primary sources spanning poli

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation

arXiv:2606.27268v1 Announce Type: cross Abstract: Recently, a few works have made early attempts to study test-time scaling for embodied tasks. However, two major challenges remain unsolved: (1) reaso

Effective Covariance Dynamics in Solvable High-Dimensional GANs

arXiv:2606.27246v1 Announce Type: new Abstract: We study a solvable high-dimensional model of generative adversarial network (GAN) training in which a linear generator learns a low-dimensional subspac

EVOM: Agentic Meta-Evolution of Actor-Critic Architectures for Reinforcement Learning

arXiv:2606.26327v1 Announce Type: cross Abstract: In actor-critic reinforcement learning, network architectures are typically manually designed. Automating this design is challenging because each cand

Finding the Time to Think: Learning Planning Budgets in Real-Time RL

arXiv:2606.26463v1 Announce Type: new Abstract: Deliberating takes time. In real-time settings, that time is not free. Standard reinforcement learning (RL) sidesteps this as the environment waits inde

Forecasting With LLMs: Improved Generalization Through Feature Steering

arXiv:2606.27199v1 Announce Type: new Abstract: Successful forecasting involves identifying patterns between historical and future states of the world which generalize to future observations. We apply

safetyarxiv-cs-cl

From Hallucination to Grounding: Diagnosing Visual Spatial Intelligence via CRISP

arXiv:2606.26535v1 Announce Type: cross Abstract: Current VLM evaluations often conflate language priors with genuine spatial reasoning. To address this, we introduce CRISP, a novel structural-diagnos