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arXiv:2605.26454v1 Announce Type: new Abstract: Large language models (LLMs) learn undesirable properties during pretraining, including dangerous knowledge and toxic text generation. Just as post-trai

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Olaf-World: Orienting Latent Actions for Video World Modeling

DGX agent

arXiv:2602.10104v2 Announce Type: replace-cross Abstract: Scaling action-controllable world models is limited by the scarcity of action labels. While latent action learning promises to extract control

safetyarxiv-cs-ai

27 May 2026

SeDT: Sentence-Transformer Decision-Transformer Conditioning for Multi-Turn Conversation Reliability

arXiv:2605.26788v1 Announce Type: cross Abstract: Large language models (LLMs) achieve impressive performance when a task is fully specified in a single turn, yet the same models lose up to 39% of tha

SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2603.28730v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown impressive capabilities across diverse tasks, motivating efforts to leverage these models to supervis

To model human linguistic prediction, make LLMs less superhuman

arXiv:2510.05141v2 Announce Type: replace Abstract: When we read, we make predictions about upcoming words; these predictions influence our reading behavior. The success of large language models (LLMs

safetyarxiv-cs-cl

A Multimodal 3D Foundation Model for Light Sheet Fluorescence Microscopy Enables Few-Shot Segmentation, Classification, and Deblurring

arXiv:2605.26026v1 Announce Type: cross Abstract: Light sheet fluorescence microscopy (LSM) enables high-resolution, three-dimensional (3D) imaging of biological specimens, providing rich volumetric d

safetyarxiv-cs-ai

AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery

arXiv:2604.05550v2 Announce Type: replace Abstract: Artificial intelligence research increasingly depends on prolonged cycles of reproduction, debugging, and iterative refinement to achieve State-Of-T

agentsarxiv-cs-cl

E3AD: An Emotion-Aware Vision-Language-Action Model for Human-Centric End-to-End Autonomous Driving

arXiv:2512.04733v2 Announce Type: replace-cross Abstract: End-to-end autonomous driving (AD) systems increasingly adopt vision-language-action (VLA) models, yet they typically ignore the passenger's e

safetyarxiv-cs-ai

ERNIE-Image Technical Report

model-releasesarxiv-cs-lg

arXiv:2605.25347v1 Announce Type: cross Abstract: We introduce ERNIE-Image, an open-source text-to-image generation model built upon an 8B single-stream DiT architecture. ERNIE-Image aims to bridge th

Hadamard Representation: Scaffolding Performance Across Model-free RL

model-releasesarxiv-cs-lg

arXiv:2406.09079v5 Announce Type: replace Abstract: Deep reinforcement learning agents progressively lose representational capacity during training: neurons become dormant, removing active capacity fr

Learning to Reason Efficiently with A* Post-Training

arXiv:2605.24597v1 Announce Type: new Abstract: Many applications of large language models (LLMs) require deductive reasoning, yet models frequently produce incorrect or redundant inference steps. We

Logic-Guided Vector Fields for Constrained Generative Modeling

arXiv:2602.02009v2 Announce Type: replace Abstract: Neuro-symbolic systems aim to combine the expressive structure of symbolic logic with the flexibility of neural learning; yet, generative models typ

MCPXKIT: The Unified Toolkit for Analyzing Model Context Protocol Security

arXiv:2508.12538v2 Announce Type: replace-cross Abstract: The Model Context Protocol (MCP) has emerged as a universal standard that enables AI agents to seamlessly connect with external tools, signifi

agentsarxiv-cs-ai

Understanding and Mitigating Premature Confidence for Better LLM Reasoning

arXiv:2605.24396v1 Announce Type: new Abstract: Long chains of thought (CoT) from current language models frequently contain logical gaps and unjustified leaps, limiting the gains from additional test

Universal Activation Verbalizer: A Unified Framework for Cross-Model Activation Explanation

arXiv:2605.25903v1 Announce Type: new Abstract: Activation verbalization explains hidden representations in natural language, but existing methods are mostly limited to self-explanation, where each mo

researcharxiv-cs-cl

World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy

arXiv:2602.06508v2 Announce Type: replace Abstract: Reinforcement learning (RL) can refine Vision-Language-Action (VLA) policies beyond behavior cloning, but real-world RL remains expensive due to ext

safetyarxiv-cs-ro

Decomposing and Measuring Evaluation Awareness

arXiv:2605.23055v1 Announce Type: cross Abstract: Frontier language models sometimes recognize that they are being evaluated and adjust their behavior, undermining validity of benchmark results. Yet t

From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills

arXiv:2605.23899v1 Announce Type: new Abstract: Language agents increasingly improve by reusing skills -- structured procedural artifacts distilled from past experience. In particular, domain-level an

agentsarxiv-cs-ai

It's the humans, not the data: Geopolitical bias in LLMs originates in post-training, amplified by the language of the prompt

arXiv:2605.23825v1 Announce Type: cross Abstract: It has generally been assumed that geopolitical bias in language models originates from the training data used during the pre-training phase. We teste

Reading Calibrated Uncertainty from Language Model Trajectories

arXiv:2605.22864v1 Announce Type: new Abstract: The maximum softmax probability (MSP) represents a default approach when evaluating uncertainty quantification for language model generation with struct

WMAttack: Automated Attack Search for Adversarial Evaluation of World-Model Agents

arXiv:2605.23220v1 Announce Type: new Abstract: Despite the growing use of world models as decision-making agents, their adversarial robustness remains underexplored due to the lack of dedicated autom

World Machine: Towards Generative World Modeling for Time-Series

arXiv:2605.23025v1 Announce Type: new Abstract: World models represent a paradigm shift in generative AI, pursuing predictive understanding and controllable simulation of environments in a structured

Local Ai

EnCAgg: Enhanced Clustering Aggregation for Robust Federated Learning against Dynamic Model Poisoning

arXiv:2605.22506v1 Announce Type: cross Abstract: Federated learning faces increasing threats from model poisoning attacks, which harms its application to improve privacy. Existing defense methods typ

local-aiarxiv-cs-lg

23 May 2026

Generative Modeling by Value-Driven Transport

arXiv:2605.22507v1 Announce Type: new Abstract: We propose a new framework for generative modeling based on a discrete-time stochastic control formulation of measure transport. Adapting classic result

safetyarxiv-cs-lg

23 May 2026

An Open Multi-Center Whole-Body FDG PET/CT Foundation Model for Tumor Segmentation

arXiv:2605.21835v1 Announce Type: cross Abstract: The synergistic interpretation of anatomical information from computed tomography (CT) and metabolic information from positron emission tomography (PE

22 May 2026

In Silico Modeling of the RAMPHO Buffer: Dissociating Informational and Energetic Masking via Phonetic Entropy in Deep Neural Networks

arXiv:2605.22465v1 Announce Type: new Abstract: The fundamental challenge of listening in multi-talker environments is a cognitive bottleneck, defined by the Ease of Language Understanding (ELU) model

researcharxiv-cs-cl

22 May 2026

AirfoilGen: A valid-by-construction and performance-aware latent diffusion model for airfoil generation

arXiv:2605.20303v1 Announce Type: new Abstract: Airfoil shape design is a fundamental task in aerospace engineering, with a direct impact on flight stability and fuel consumption. Deep learning has re

Applications

CoarseSoundNet: Building a reliable model for ecological soundscape analysis

arXiv:2605.21143v1 Announce Type: cross Abstract: A soundscape is composed of three types of sound: biophony (sounds made by animals), geophony (natural abiotic sounds) and anthropophony (sounds made

applicationsarxiv-cs-lg

Generation of Heterogeneous PET Images from Uniform Organ Activity Maps Using a Pretrained Domain-Adapted Diffusion Model

arXiv:2605.20267v1 Announce Type: new Abstract: Synthetic PET images are valuable for quantitative imaging workflow development, scalable virtual imaging trials, and deep learning model training, but

Large-Step Training Dynamics of a Two-Factor Linear Transformer Model

model-releasesarxiv-cs-lg

arXiv:2605.21292v1 Announce Type: cross Abstract: Gradient-flow analyses show that simplified linear transformers can learn the in-context linear-regression algorithm, but they do not explain the fini

Oracle Supervision Transfers for Hyperparameter Prediction in Model-Based Image Denoising

arXiv:2605.20479v1 Announce Type: new Abstract: Hyperparameter prediction is a critical practical bottleneck for model-based image denoisers, ranging from classical TV/TGV variational solvers to moder

Uni-Edit: Intelligent Editing Is A General Task For Unified Model Tuning

arXiv:2605.21487v1 Announce Type: new Abstract: Currently, enhancing Unified Multimodal Models (UMMs) with image understanding, generation, and editing capabilities mainly relies on mixed multi-task t

A Geometric Analysis of Small-sized Language Model Hallucinations

arXiv:2602.14778v3 Announce Type: replace-cross Abstract: Hallucinations -- plausible but factually incorrect responses -- pose a major challenge to the reliability of Large Language Models (LLMs), es

agentsarxiv-cs-ai

An Objective Performance Evaluation of the LSTM Networks in Time Series Classification

arXiv:2605.19311v1 Announce Type: new Abstract: The rapid adoption of deep learning has increasingly led to data-driven models replacing classical model-based algorithms, even in domains governed by w

Distilling Linearized Behavior for Effective Task Arithmetic

arXiv:2605.18993v1 Announce Type: cross Abstract: Task vector composition has emerged as a promising paradigm for editing pre-trained models, enabling model merging through addition and unlearning thr

Does Your Wildfire Prediction Model Actually Work, or Just Score Well?

arXiv:2605.18911v1 Announce Type: cross Abstract: Wildfire prediction is important for early warning and resource allocation, yet existing Earth foundation models (Earth FMs) are pretrained for genera

researcharxiv-cs-ai

Generative Auto-Bidding with Unified Modeling and Exploration

arXiv:2605.19457v1 Announce Type: new Abstract: Automated bidding is central to modern digital advertising. Early rule-based methods lacked adaptability, while subsequent Reinforcement Learning approa

safetyarxiv-cs-ai

Tutorials

Heterogeneity-Aware Dataset Scheduling for Efficient Audio Large Language Model Training

arXiv:2605.19101v1 Announce Type: cross Abstract: Training general-purpose Audio Large Language Models (ALLMs) across diverse datasets is essential for holistic audio understanding, yet it faces signi

tutorialsarxiv-cs-lg

Local Ai

Hierarchical Schedule Optimization for Fast and Robust Diffusion Model Sampling

arXiv:2511.11688v3 Announce Type: replace-cross Abstract: Diffusion probabilistic models have set a new standard for generative fidelity but are hindered by a slow iterative sampling process. A powerf

local-aiarxiv-cs-cv

Multi-Scale Generative Modeling with Heat Dissipation Flow Matching

arXiv:2605.19371v1 Announce Type: cross Abstract: Diffusion models are widely used in image generation, with most relying on noise-based corruption and denoising. A distinct branch instead uses blur a

researcharxiv-cs-ai

StampFormer: A Physics-Guided Material-Geometry-Coupled Multimodal Model for Rapid Prediction of Physical Fields in Sheet Metal Stamping

arXiv:2605.18835v1 Announce Type: new Abstract: Traditional sheet metal forming relies on time-consuming and expensive Finite Element Analysis (FEA) for design validation, a process that significantly

SWEET: Sparse World Modeling with Image Editing for Embodied Task Execution

arXiv:2605.19319v1 Announce Type: new Abstract: Visual prediction has emerged as a promising paradigm for embodied control, where future observations are generated and then translated into actions. Ho

A Novel Model for 3D Motion Planning for a Generalized Dubins Vehicle with Pitch and Yaw Rate Constraints

arXiv:2509.24143v2 Announce Type: replace Abstract: In this paper, we propose a new modeling approach and a fast algorithm for 3D motion planning, applicable for fixed-wing unmanned aerial vehicles. T

researcharxiv-cs-ro

BELIEF: Structured Evidence Modeling and Uncertainty-Aware Fusion for Biomedical Question Answering

arXiv:2605.17435v1 Announce Type: new Abstract: Biomedical question answering often requires decisions from retrieved literature whose relevance, quality, and support for candidate answers are uneven.

researcharxiv-cs-cl

Beyond the Final Actor: Modeling the Dual Roles of Creator and Editor for Fine-Grained LLM-Generated Text Detection

arXiv:2604.04932v3 Announce Type: replace Abstract: The misuse of large language models (LLMs) requires precise detection of synthetic text. Existing works mainly follow binary or ternary classificati

safetyarxiv-cs-cl

Exploring Trust Calibration in XAI - The Impact of Exposing Model Limitations to Lay Users

arXiv:2605.18036v1 Announce Type: cross Abstract: Trust calibration -- aligning user trust judgment with model capability -- is crucial for safe deployment of explainable AI (XAI), yet is often evalua

researcharxiv-cs-ai

Local Ai

Global Prior Meets Local Consistency: Dual-Memory Augmented Vision-Language-Action Model for Efficient Robotic Manipulation

arXiv:2602.20200v2 Announce Type: replace-cross Abstract: Hierarchical Vision-Language-Action (VLA) models have rapidly become a dominant paradigm for robotic manipulation. It typically comprising a V

local-aiarxiv-cs-ai

HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference

arXiv:2506.23287v3 Announce Type: replace Abstract: In single-cell research, tracing and analyzing high-throughput single-cell differentiation trajectories is crucial for understanding biological proc