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CT-1: Vision-Language-Camera Models Transfer Spatial Reasoning Knowledge to Camera-Controllable Video Generation

arXiv:2604.09201v1 Announce Type: new Abstract: Camera-controllable video generation aims to synthesize videos with flexible and physically plausible camera movements. However, existing methods either

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Decomposing the Delta: What Do Models Actually Learn from Preference Pairs?

DGX agent

arXiv:2604.08723v1 Announce Type: cross Abstract: Preference optimization methods such as DPO and KTO are widely used for aligning language models, yet little is understood about what properties of pr

tutorialsarxiv-cs-ai

13 Apr 2026

Degradation-Robust Fusion: An Efficient Degradation-Aware Diffusion Framework for Multimodal Image Fusion in Arbitrary Degradation Scenarios

arXiv:2604.08922v1 Announce Type: new Abstract: Complex degradations like noise, blur, and low resolution are typical challenges in real world image fusion tasks, limiting the performance and practica

Detection and Characterization of Coordinated Online Behavior: A Survey

arXiv:2408.01257v2 Announce Type: replace-cross Abstract: Coordination is a fundamental aspect of life. The advent of social media has made it integral also to online human interactions, such as those

Drift and selection in LLM text ecosystems

arXiv:2604.08554v1 Announce Type: cross Abstract: The public text record -- the material from which both people and AI systems now learn -- is increasingly shaped by its own outputs. Generated text en

Generative View Stitching

arXiv:2510.24718v3 Announce Type: replace Abstract: Autoregressive video diffusion models are capable of long rollouts that are stable and consistent with history, but they are unable to guide the cur

Learning General Representation of 12-Lead Electrocardiogram with a Joint-Embedding Predictive Architecture

arXiv:2410.08559v5 Announce Type: replace-cross Abstract: Electrocardiogram (ECG) captures the heart's electrical signals, offering valuable information for diagnosing cardiac conditions. However, the

LEGO: Latent-space Exploration for Geometry-aware Optimization of Humanoid Kinematic Design

arXiv:2604.08636v1 Announce Type: cross Abstract: Designing robot morphologies and kinematics has traditionally relied on human intuition, with little systematic foundation. Motion-design co-optimizat

M-IDoL: Information Decomposition for Modality-Specific and Diverse Representation Learning in Medical Foundation Model

arXiv:2604.08936v1 Announce Type: new Abstract: Medical foundation models (MFMs) aim to learn universal representations from multimodal medical images that can generalize effectively to diverse downst

Mind the Gap Between Spatial Reasoning and Acting! Step-by-Step Evaluation of Agents With Spatial-Gym

arXiv:2604.09338v1 Announce Type: new Abstract: Spatial reasoning is central to navigation and robotics, yet measuring model capabilities on these tasks remains difficult. Existing benchmarks evaluate

MV3DIS: Multi-View Mask Matching via 3D Guides for Zero-Shot 3D Instance Segmentation

arXiv:2604.08916v1 Announce Type: new Abstract: Conventional 3D instance segmentation methods rely on labor-intensive 3D annotations for supervised training, which limits their scalability and general

OmniPrism: Learning Disentangled Visual Concept for Image Generation

arXiv:2412.12242v2 Announce Type: replace-cross Abstract: Creative visual concept generation often draws inspiration from specific concepts in a reference image to produce relevant outcomes. However,

Physically Grounded 3D Generative Reconstruction under Hand Occlusion using Proprioception and Multi-Contact Touch

arXiv:2604.09100v1 Announce Type: new Abstract: We propose a multimodal, physically grounded approach for metric-scale amodal object reconstruction and pose estimation under severe hand occlusion. Unl

RetinexDualV2: Physically-Grounded Dual Retinex for Generalized UHD Image Restoration

arXiv:2603.27979v2 Announce Type: replace Abstract: We propose RetinexDualV2, a unified, physically grounded dual-branch framework for diverse Ultra-High-Definition (UHD) image restoration. Unlike gen

Sample-Efficient Neurosymbolic Deep Reinforcement Learning

arXiv:2601.02850v2 Announce Type: replace Abstract: Reinforcement Learning (RL) is a well-established framework for sequential decision-making in complex environments. However, state-of-the-art Deep R

ShelfGaussian: Shelf-Supervised Open-Vocabulary Gaussian-based 3D Scene Understanding

arXiv:2512.03370v3 Announce Type: replace Abstract: We introduce ShelfGaussian, an open-vocabulary multi-modal Gaussian-based 3D scene understanding framework supervised by off-the-shelf vision founda

SkillFactory: Self-Distillation For Learning Cognitive Behaviors

arXiv:2512.04072v2 Announce Type: replace-cross Abstract: Reasoning models leveraging long chains of thought employ various cognitive skills, such as verification of their answers, backtracking, retry

Training-free, Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models

arXiv:2604.09227v1 Announce Type: cross Abstract: Image generative models have become indispensable tools to yield exquisite high-resolution (HR) images for everyone, ranging from general users to pro

What Matters in Virtual Try-Off? Dual-UNet Diffusion Model For Garment Reconstruction

arXiv:2604.08716v1 Announce Type: new Abstract: Virtual Try-On (VTON) has seen rapid advancements, providing a strong foundation for generative fashion tasks. However, the inverse problem, Virtual Try

WOMBET: World Model-based Experience Transfer for Robust and Sample-efficient Reinforcement Learning

arXiv:2604.08958v1 Announce Type: cross Abstract: Reinforcement learning (RL) in robotics is often limited by the cost and risk of data collection, motivating experience transfer from a source task to

You Can't Fight in Here! This is BBS!

arXiv:2604.09501v1 Announce Type: new Abstract: Norm, the formal theoretical linguist, and Claudette, the computational language scientist, have a lovely time discussing whether modern language models

tutorialsarxiv-cs-cl

A comparative analysis of machine learning models in SHAP analysis

arXiv:2604.07258v1 Announce Type: new Abstract: In this growing age of data and technology, large black-box models are becoming the norm due to their ability to handle vast amounts of data and learn i

A Severity-Based Curriculum Learning Strategy for Arabic Medical Text Generation

arXiv:2604.06365v1 Announce Type: cross Abstract: Arabic medical text generation is increasingly needed to help users interpret symptoms and access general health guidance in their native language. Ne

Adversarial Flow Models

arXiv:2511.22475v2 Announce Type: replace-cross Abstract: We present adversarial flow models, a class of generative models that belongs to both the adversarial and flow families. Our method supports n

Amortized Filtering and Smoothing with Conditional Normalizing Flows

arXiv:2604.07169v1 Announce Type: cross Abstract: Bayesian filtering and smoothing for high-dimensional nonlinear dynamical systems are fundamental yet challenging problems in many areas of science an

Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenes

arXiv:2410.22177v2 Announce Type: replace-cross Abstract: As more applications of large language models (LLMs) for 3D content for immersive environments emerge, it is crucial to study user behaviour t

Attribution-Driven Explainable Intrusion Detection with Encoder-Based Large Language Models

arXiv:2604.06266v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) improves network flexibility but also increases the need for reliable and interpretable intrusion detection. Large L

BADiff: Bandwidth Adaptive Diffusion Model

arXiv:2510.21366v3 Announce Type: replace Abstract: In this work, we propose a novel framework to enable diffusion models to adapt their generation quality based on real-time network bandwidth constra

Balanced Diffusion-Guided Fusion for Multimodal Remote Sensing Classification

arXiv:2509.23310v3 Announce Type: replace Abstract: Deep learning-based techniques for the analysis of multimodal remote sensing data have become popular due to their ability to effectively integrate

Conditional flow matching for physics-constrained inverse problems with finite training data

arXiv:2603.14135v3 Announce Type: replace-cross Abstract: This study presents a conditional flow matching framework for solving physics-constrained Bayesian inverse problems. In this setting, samples

Coordinate-Based Dual-Constrained Autoregressive Motion Generation

arXiv:2604.08088v1 Announce Type: new Abstract: Text-to-motion generation has attracted increasing attention in the research community recently, with potential applications in animation, virtual reali

Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video

arXiv:2604.07786v1 Announce Type: new Abstract: Talking face generation has gained significant attention as a core application of generative models. To enhance the expressiveness and realism of synthe

DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models

arXiv:2306.14685v5 Announce Type: replace-cross Abstract: We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide

Diffusion Processes on Implicit Manifolds

arXiv:2604.07213v1 Announce Type: new Abstract: High-dimensional data are often modeled as lying near a low-dimensional manifold. We study how to construct diffusion processes on this data manifold in

'Don't Be Afraid, Just Learn': Insights from Industry Practitioners to Prepare Software Engineers in the Age of Generative AI

arXiv:2604.06342v1 Announce Type: cross Abstract: Although tension between university curricula and industry expectations has existed in some form for decades, the rapid integration of generative AI (

Don't Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget

arXiv:2402.02249v3 Announce Type: replace Abstract: We study how to best spend a budget of noisy labels to compare the accuracy of two binary classifiers. It's common practice to collect and aggregate

ELC: Evidential Lifelong Classifier for Uncertainty Aware Radar Pulse Classification

arXiv:2604.06958v1 Announce Type: cross Abstract: Reliable radar pulse classification is essential in Electromagnetic Warfare for situational awareness and decision support. Deep Neural Networks have

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis

arXiv:2604.07180v1 Announce Type: cross Abstract: We propose a geometric framework for longitudinal multi-parametric MRI analysis based on patient-specific energy modelling in sequence space. Rather t

EPIR: An Efficient Patch Tokenization, Integration and Representation Framework for Micro-expression Recognition

arXiv:2604.08106v1 Announce Type: new Abstract: Micro-expression recognition can obtain the real emotion of the individual at the current moment. Although deep learning-based methods, especially Trans

EventWeave: A Dynamic Framework for Capturing Core and Supporting Events in Dialogue Systems

arXiv:2503.23078v3 Announce Type: replace Abstract: Large language models have improved dialogue systems, but often process conversational turns in isolation, overlooking the event structures that gui

tutorialsarxiv-cs-cl

ExplainFuzz: Explainable and Constraint-Conditioned Test Generation with Probabilistic Circuits

arXiv:2604.06559v1 Announce Type: cross Abstract: Understanding and explaining the structure of generated test inputs is essential for effective software testing and debugging. Existing approaches--in

Exploring Temporal Representation in Neural Processes for Multimodal Action Prediction

arXiv:2604.08418v1 Announce Type: new Abstract: Inspired by the human ability to understand and predict others, we study the applicability of Conditional Neural Processes (CNP) to the task of self-sup

tutorialsarxiv-cs-ro

Face2Scene: Using Facial Degradation as an Oracle for Diffusion-Based Scene Restoration

arXiv:2603.16570v2 Announce Type: replace Abstract: Recent advances in image restoration have enabled high-fidelity recovery of faces from degraded inputs using reference-based face restoration models

Few-Shot Incremental 3D Object Detection in Dynamic Indoor Environments

arXiv:2604.07997v1 Announce Type: new Abstract: Incremental 3D object perception is a critical step toward embodied intelligence in dynamic indoor environments. However, existing incremental 3D detect

Generalization Under Scrutiny: Cross-Domain Detection Progresses, Pitfalls, and Persistent Challenges

arXiv:2604.08230v1 Announce Type: new Abstract: Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to vari

How to sketch a learning algorithm

arXiv:2604.07328v1 Announce Type: new Abstract: How does the choice of training data influence an AI model? This question is of central importance to interpretability, privacy, and basic science. At i

Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement

arXiv:2507.08390v4 Announce Type: replace Abstract: Discrete diffusion models have recently emerged as strong alternatives to autoregressive language models, matching their performance through large-s

Learning is Forgetting: LLM Training As Lossy Compression

arXiv:2604.07569v1 Announce Type: cross Abstract: Despite the increasing prevalence of large language models (LLMs), we still have a limited understanding of how their representational spaces are stru

tutorialsarxiv-cs-cl