Search: “tutorials”

NGPS: Structure-Preserving Self-Supervised Denoising via Neighbor-Guided Patch Sampling

arXiv:2606.23200v1 Announce Type: cross Abstract: Neighboring-slice self-supervised denoising is attractive for volumetric medical imaging, yet inter-slice misalignment breaks anatomical correspondenc

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Tutorials

Non-Adversarial Imitation Learning Provably Free of Compounding Errors: The Value Flow Mechanism

DGX agent

arXiv:2603.22713v2 Announce Type: replace Abstract: Adversarial imitation learning (AIL) achieves high-quality imitation by mitigating compounding errors inherent to behavioral cloning (BC), yet its a

tutorialsarxiv-cs-lg

23 Jun 2026

NullFlow: One-Step Generative Reconstruction

arXiv:2606.22696v1 Announce Type: new Abstract: We propose NullFlow, a principled framework for one-step generative image reconstruction. Our key idea is to confine the generative flow to a measuremen

On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies

arXiv:2606.17276v3 Announce Type: replace-cross Abstract: Generative recommendation (GR) has emerged as a promising direction for recommender systems. Recently, large language models (LLMs) have been

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation

arXiv:2602.24121v2 Announce Type: replace Abstract: Current methods in robot learning are fundamentally bottlenecked by one or more of: hand-designed rewards, simulation modeling, or action supervisio

tutorialsarxiv-cs-ro

PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation

arXiv:2512.24551v4 Announce Type: replace Abstract: Recent advances in text-to-video (T2V) generation have achieved good visual quality, yet synthesizing videos that faithfully follow physical laws re

Poisson2Gaussian: Noise Gaussianization to Enhance Image Denoising

arXiv:2606.23098v1 Announce Type: new Abstract: The quantum nature of light determines the inherent Poisson stochasticity of photon detection, which is ubiquitous in photography, microscopy, and astro

Predictive Gaze Is Preserved but Reorganized toward Monitoring during Robot-Mediated Manipulation

arXiv:2606.21920v1 Announce Type: new Abstract: Goal-directed eye movements are a fundamental component of visuomotor control, enabling humans to anticipate and guide their actions. Whether this antic

tutorialsarxiv-cs-ro

Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently

arXiv:2606.22938v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated that reinforcement fine-tuning of pretrained base models can lead to significant gains

Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining

arXiv:2601.19756v2 Announce Type: replace Abstract: The empirical success of deep learning is often attributed to deep networks' ability to exploit hierarchical structure in data, constructing increas

Rethinking Prototype-based Similarity Learning for Few-Shot Object Detection

arXiv:2606.23069v1 Announce Type: new Abstract: Few-shot object detection aims to detect novel object categories from only a few labeled examples, avoiding costly large-scale annotation. Recent protot

Scalable Bayesian Additive Models for Stellar Flare Detection via Amortized Gaussian Process Inference and Hidden Markov Models

arXiv:2606.22601v1 Announce Type: cross Abstract: Gaussian Processes (GPs) are a powerful tool for Bayesian time-series modeling, yet their cubic computational cost remains a severe barrier for applic

Scalable Training of Spatially Grounded 2D Vision-Language Models for Radiology

arXiv:2606.20477v2 Announce Type: replace Abstract: We study how to train visually grounded vision-language models (VLMs) for radiology without manual spatial annotations. We introduce RefRad2D, a lar

Selective Ensemble Based on Preference-Directed Multi-Objective Bandits

arXiv:2606.21929v1 Announce Type: new Abstract: Selective ensemble for modern machine learning systems requires choosing promising model candidates under limited evaluation budgets, while downstream t

Sparse Point-Guided Fusion of Supervised and Self-Supervised Learning Model for Seaweed Segmentation

arXiv:2606.21026v1 Announce Type: new Abstract: The ocean plays a critical role in sustainable development, particularly in climate change mitigation. Among marine ecosystems, blue carbon ecosystems a

Spectral GS-SLAM: Observability-Aware, Degeneracy-Robust Tracking for Real-Time 3D Gaussian Splatting SLAM

arXiv:2606.21258v1 Announce Type: cross Abstract: Recent 3DGS-SLAM systems enable real-time operation by leveraging conventional feature matching or ICP-based tracking, thereby avoiding the heavy dens

Structural Assessment for Understanding and Guiding Dataset Distillation in Discrete Token Space

arXiv:2606.21705v1 Announce Type: new Abstract: Dataset distillation (DD) has proven to reduce training cost while preserving accuracy. While promising, the factors that make one distilled dataset mor

The New Associationism: Lessons from Deep Learning

arXiv:2606.20600v1 Announce Type: cross Abstract: What can the success of modern AI tell us about how humans learn? This paper argues that taking AI seriously as a model of human learning supports a m

VT-DUDA: Visual Token Conditioning for Diffusion-guided Unsupervised Domain Adaptation

arXiv:2606.21700v1 Announce Type: new Abstract: Unsupervised domain adaptation (UDA) aims to learn a target-domain classifier from labeled source data and unlabeled target data under distribution shif

What Do Lorentz-Equivariant Jet Taggers Learn?

arXiv:2606.21790v1 Announce Type: new Abstract: We study what Lorentz-equivariant jet taggers learn internally, using equivariance tests, linear probes and grade ablations across five models including

What Do Neural Networks Learn for TDOA Estimation? A Cross-Architecture Probing Study

arXiv:2606.22020v1 Announce Type: cross Abstract: Neural networks outperform classical GCC-PHAT for Time-Difference-of-Arrival (TDOA) estimation in noise and reverberation, yet their internal strategy

What Does a Chemical Language Model Know About Molecules?

arXiv:2606.23443v1 Announce Type: new Abstract: Chemical language models (cLMs) are widely assumed to learn surface-level syntactic patterns rather than learning meaningful molecular semantics. Here,

Words as Difference Makers: How Large Language Models Determine Causal Structure in Text

arXiv:2606.22430v1 Announce Type: cross Abstract: Because large language models (LLMs) are impressively successful in predicting text, it appears that they must have access to a 'world model' represen

Accurate and Resource-Efficient Federated Continual Learning

arXiv:2606.11480v1 Announce Type: new Abstract: Federated continual learning (FCL) must learn from distributed task streams under limited resources, such as communication, computation, memory, and lab

AGE-MIL: Anchor-Guided Evidence Learning for Patient-Level Prediction

arXiv:2606.12126v1 Announce Type: new Abstract: Existing computational pathology methods predominantly operate within whole-slide image (WSI)-level multiple instance learning (MIL) paradigms, while pa

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal

arXiv:2606.12360v1 Announce Type: new Abstract: Language-model post-training is the main stage at which model behavior is shaped, yet it still largely involves optimization of scalar rewards that summ

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching

arXiv:2606.11583v1 Announce Type: new Abstract: Text-attributed graphs (TAGs) underlie real-world applications such as citation networks, social media, and e-commerce. Few-shot graph learning on TAGs

CredibleDFGO: Differentiable Factor Graph Optimization with Credibility Supervision

arXiv:2605.06100v2 Announce Type: replace-cross Abstract: Global navigation satellite system (GNSS) positioning is widely used for urban navigation, but the covariance reported by the GNSS solver is o

DeepRHP: A Hybrid Variational Autoencoder for Designing Random Heteropolymers as Protein Mimics

arXiv:2606.11651v1 Announce Type: new Abstract: Synthetic random heteropolymers (RHPs), consisting of a predefined set of monomers, offer an approach toward the design of protein-like materials. These

DepthMaster: Unified Monocular Depth Estimation for Perspective and Panoramic Images

arXiv:2606.12368v1 Announce Type: new Abstract: While monocular depth estimation has achieved significant progress, achieving generalized metric depth estimation for both narrow field-of-view (FoV) pe

FitVTON: Fit-aware Virtual Try-On via Body-Garment Size Control

arXiv:2606.12012v1 Announce Type: new Abstract: While diffusion-based virtual try-on has achieved impressive visual realism, most methods treat the task as 2D inpainting, prioritizing texture preserva

FOCUS: DLLMs Know How to Tame Their Compute Bound

arXiv:2601.23278v2 Announce Type: replace-cross Abstract: Diffusion Large Language Models (DLLMs) offer a compelling alternative to Auto-Regressive models, but their deployment is constrained by high

tutorialsarxiv-cs-cl

How Low Can You Go? Active Learning for Sparse Model Discovery in the Ultra-Low-Data Limit

arXiv:2606.12182v1 Announce Type: new Abstract: Identifying the governing equations of complex dynamical systems remains a fundamental challenge across science and engineering. While early approaches

Information-Theoretic Decomposition for Multimodal Interaction Learning

arXiv:2606.11614v1 Announce Type: cross Abstract: Multimodal learning hinges on capturing redundant, unique, and synergistic information across modalities, which collectively constitute multimodal int

Integral Formulation of QENDy for Robust Nonlinear System Identification

arXiv:2606.11629v1 Announce Type: cross Abstract: This manuscript proposes an integral formulation of the newly defined quadratic embedding method for identifying nonlinear systems (QENDy). In the ori

Learning Patterns and Abstractions from Perceptual Sequences

arXiv:2503.10973v2 Announce Type: replace Abstract: Cognition swiftly breaks high-dimensional sensory streams into familiar parts and uncovers their relations. Why do structures emerge, and how do the

Mechanical Field Networks: Structured Neural Dynamics for Multivariate Systems

arXiv:2606.11251v1 Announce Type: new Abstract: Many multivariate dynamical systems are observed only through trajectories, leaving the mechanisms governing their joint dynamics hidden. Existing appro

Nonslop: A Gamified Experiment in Human-AI Collaborative Writing

arXiv:2606.12350v1 Announce Type: new Abstract: The rapid proliferation of large language models (LLMs) raises critical questions about human creativity and individual expression in an era of AI-assis

Planning under Distribution Shifts with Causal POMDPs

arXiv:2602.23545v2 Announce Type: replace Abstract: In the real world, planning is often challenged by distribution shifts. As such, a model of the environment obtained under one set of conditions may

Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!

arXiv:2504.09762v4 Announce Type: replace Abstract: Intermediate token generation (ITG), where a model produces output before the solution, has become a standard method to improve the performance of l

Probabilistic Salary Prediction with Graph Attention Networks and a Mixture Density Network

arXiv:2606.11663v1 Announce Type: cross Abstract: Accurate salary prediction is critical for bridging the information gap between employers and job seekers in modern labor markets. Existing approaches

Quantum Occam Learning: Sample-Supported Expressibility for Circuit-Based Quantum Learning

arXiv:2606.12211v1 Announce Type: cross Abstract: A central principle in quantum machine learning is that an ansatz should be expressive enough to represent the quantum data of interest. Yet, the expr

Rule Taxonomy and Evolution in AI IDEs: A Mining and Survey Study

arXiv:2606.12231v1 Announce Type: cross Abstract: The adoption of AI-powered Integrated Development Environments (AI IDEs) has introduced 'Rules' as a novel software artifact, allowing developers to p

SOMA-SQL: Resolving Multi-Source Ambiguity in NL-to-SQL via Synthetic Log and Execution Probing

arXiv:2606.11424v1 Announce Type: new Abstract: Natural language interfaces to databases aim to translate user questions into executable SQL, yet remain brittle in real-world settings where questions

tutorialsarxiv-cs-cl

TaskFusion: Continual Anomaly Detection for Heterogeneous Tabular Data

arXiv:2606.11844v1 Announce Type: new Abstract: Continual anomaly detection in tabular data is challenging and remains largely underexplored, particularly in settings with heterogeneous feature schema

TopoCap: Learning Topology-Agnostic Motion Priors for Monocular Video-to-Animation

arXiv:2606.12153v1 Announce Type: new Abstract: The explosion of generative 3D assets has created a massive demand for animation, yet current motion capture methods remain brittle, restricted to speci

When is Your LLM Steerable?

arXiv:2606.11599v1 Announce Type: new Abstract: Activation steering offers a lightweight approach to control language models' behavior at inference time, but whether it succeeds or fails heavily depen

tutorialsarxiv-cs-cl

A Bayesian Network Approach for Enhancing Security-Focused Decision Support Systems

arXiv:2606.10782v1 Announce Type: cross Abstract: The adoption and integration of heterogeneous stacks in most of today's open-source based networks brings clear benefits like interoperability and ava