tutorials

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster

arXiv:2605.18204v1 Announce Type: cross Abstract: Discrete diffusion models are a powerful class of generative models with strong performance across many domains. For efficiency, however, discrete dif

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From Prediction to Intervention: The Evolution of AI in Biomedicine

DGX agent

arXiv:2605.16293v1 Announce Type: cross Abstract: Artificial intelligence has advanced rapidly in biomedicine through large-scale multimodal data integration, enabling increasingly accurate prediction

tutorialsarxiv-cs-ai

19 May 2026

Generating Pretraining Tokens from Organic Data for Data-Bound Scaling

arXiv:2605.17849v1 Announce Type: cross Abstract: LLM pretraining is shifting from a compute-bound to a data-bound regime, where available human (organic) text falls far short of scaling demands. Howe

Generative Adversarial Learning from Deterministic Processes

arXiv:2605.18425v1 Announce Type: new Abstract: Physical AI is being successfully applied to data which does not follow the traditional paradigm of independent and identically distributed (i.i.d.) sam

GUIDE-VAE: Advancing Data Generation with User Information and Pattern Dictionaries

arXiv:2411.03936v2 Announce Type: replace Abstract: Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires emplo

High-Resolution Reference Image Assisted Volumetric Super-Resolution of Cardiac Diffusion Weighted Imaging

arXiv:2310.20389v2 Announce Type: replace-cross Abstract: Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human hear

How Class Ontology and Data Scale Affect Audio Transfer Learning

arXiv:2603.25476v2 Announce Type: replace Abstract: Transfer learning is a crucial concept within deep learning that allows artificial neural networks to benefit from a large pre-training data basis w

How to Build Real-Time Fraud Detection using Spark Real-Time Mode and Lakebase

This Databricks guide demonstrates how to implement real-time fraud detection systems by leveraging Spark Real-Time Mode and Lakebase to process and analyze streaming data for identifying fraudulent t

tutorialsdatabricks

How to run evals for the model router

tutorialsmicrosoft-foundry

Walk through running quality, cost, and latency evaluations for the Foundry model router using an open-source GitHub repo designed for router-aware eval pipelines. The post How to run evals for the mo

How to safeguard AI workloads with Unity AI Gateway Guardrails

Unity AI Gateway Guardrails is a Databricks feature designed to protect AI workloads by implementing safety measures and policy controls within the Unity Catalog framework. The tool enables organizati

tutorialsdatabricks

InvDesFlow-AL: active learning-based workflow for inverse design of functional materials

arXiv:2505.09203v2 Announce Type: replace-cross Abstract: Developing inverse design methods for functional materials with specific properties is critical to advancing fields like renewable energy, cat

Inventorship in AI-Assisted Inventions: Designing an Experiment to Shape Case Law

arXiv:2605.16528v1 Announce Type: cross Abstract: The latest improvements in artificial intelligence (AI) raise new challenges for intellectual property laws, particularly concerning the inventorship

Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning

arXiv:2605.16318v1 Announce Type: new Abstract: Building and maintaining state to learn policies and value functions is critical for deploying reinforcement learning (RL) agents in the real world. Rec

iPOE: Interpretable Prompt Optimization via Explanations

arXiv:2605.18113v1 Announce Type: new Abstract: Prompt optimization has often been framed as a discrete search problem to find high-performing and robust instructions for an LLM. However, the search r

tutorialsarxiv-cs-cl

Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits

arXiv:2602.15405v2 Announce Type: replace Abstract: Robust classification in noisy environments remains a fundamental challenge in machine learning. Standard approaches typically treat signal enhancem

L-Drive: Beyond a Single Mapping-Latent Context Drives Time Series Forecasting

arXiv:2605.17730v1 Announce Type: cross Abstract: Mainstream methods for multivariate time-series forecasting largely follow the Direct-Mapping paradigm. They learn a unified mapping from history to t

Learning from Historical Activations in Graph Neural Networks

arXiv:2601.01123v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have demonstrated remarkable success in various domains such as social networks, molecular chemistry, and more. A

Learning What Evaluators Value: A Reliable Approach to Modeling Evaluator Preferences

arXiv:2605.16615v1 Announce Type: new Abstract: In many applications, human and LLM evaluators use assessments of relevant criteria to create an overall evaluation for an item or individual. For examp

Leveraging Latent Visual Reasoning in Silence

arXiv:2605.18641v1 Announce Type: new Abstract: Latent visual reasoning involves visual evidence more directly in multimodal reasoning by inserting continuous latent tokens before textual generation.

LLM-Based Intelligent Notification Composition: From Static Personalization to Context-Aware Persuasive Messaging

arXiv:2605.16264v1 Announce Type: cross Abstract: Push notifications remain among the most direct channels through which digital platforms engage users, yet existing approaches have invested heavily i

tutorialsarxiv-cs-cl

llms.txt validation will be supported in Chrome devtools :)

tutorialsjeremy-howard--x

Chrome DevTools will add support for validating llms.txt files, enabling developers to check the validity and correctness of their llms.txt configurations directly within the browser's developer tools

Machine Learning Enabled Graph Analysis of Particulate Composites: Application to Solid-state Battery Cathodes

arXiv:2512.16085v2 Announce Type: replace-cross Abstract: Particulate composites underpin many solid-state chemical and electrochemical systems, where microstructural features such as multiphase bound

Machines Learn Number Fields, But How? The Case of Galois Groups

arXiv:2508.06670v2 Announce Type: replace-cross Abstract: By applying interpretable machine learning methods such as decision trees, we study how simple models can classify the Galois groups of Galois

Maximum Likelihood Decoding of Quantum Error Correction Codes

arXiv:2605.17230v1 Announce Type: cross Abstract: Quantum error correction (QEC) is indispensable for realizing fault-tolerant quantum computation, yet its effectiveness hinges critically on the class

Meta-Learning Guided Pruning for Few-Shot Plant Pathology on Edge Devices

arXiv:2601.02353v3 Announce Type: replace Abstract: Farmers in remote areas need quick and reliable methods for identifying plant diseases, yet they often lack access to laboratories or high-performan

Mind the Gap: Learning Modality-Agnostic Representations with a Cross-Modality UNet

arXiv:2605.16887v1 Announce Type: new Abstract: Cross-modality recognition has many important applications in science, law enforcement and entertainment. Popular methods to bridge the modality gap inc

Multiscale Supervised Unbalanced Optimal Transport Flow Matching

arXiv:2605.16529v1 Announce Type: new Abstract: Unbalanced optimal transport (UOT) provides a principled framework for modeling single-cell transitions and birth-death dynamics, but its high computati

MusicSynth: An Automated Pipeline for Generating Violin Fingerboard Animations from Sheet Music Using Optical Music Recognition

arXiv:2605.17181v1 Announce Type: cross Abstract: Learning the violin is harder than it looks. Unlike piano keys or guitar frets, the violin neck has no markings at all, so a beginner cannot tell by l

Observation-Aligned Mask Priors for Learning Physical Dynamics from Authentic Occlusions

arXiv:2605.16818v1 Announce Type: cross Abstract: Learning physical dynamics directly from incomplete observations is challenging because authentic occlusions are structured, sample-dependent, and oft

Online Algorithms with Unreliable Guidance

arXiv:2602.20706v2 Announce Type: replace Abstract: This paper introduces online algorithms with unreliable guidance (OAG), a model for ML-augmented online decision-making that cleanly separates the p

PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoning

arXiv:2601.08679v3 Announce Type: replace Abstract: As users increasingly expect LLMs to align with their preferences, personalized information becomes valuable. However, personalized information can

PhysSkin: Real-Time and Generalizable Physics-Based Animation via Self-Supervised Neural Skinning

arXiv:2603.23194v2 Announce Type: replace-cross Abstract: Achieving real-time physics-based animation that generalizes across diverse 3D shapes and discretizations remains a fundamental challenge. We

PLATO Hand: Shaping Contact Behavior with Fingernails for Precise Manipulation

arXiv:2602.05156v2 Announce Type: replace Abstract: We present the PLATO Hand, a dexterous robotic hand with a hybrid fingertip that combines a rigid fingernail, embedded distal phalanx, and compliant

tutorialsarxiv-cs-ro

PromptDecipher: Supporting AI Tutor Authoring Through Editable Simulated Interactions

arXiv:2605.16605v1 Announce Type: cross Abstract: Chatbots have long been explored as tools to support learning, and recent advances in large language models have significantly expanded the availabili

RaBiT: Residual-Aware Binarization Training for Accurate and Efficient LLMs

arXiv:2602.05367v2 Announce Type: replace Abstract: Efficient deployment of large language models (LLMs) requires extreme quantization, forcing a critical trade-off between low-bit efficiency and perf

RadJEPA: Radiology Encoder for Chest X-Rays via Joint Embedding Predictive Architecture

arXiv:2601.15891v2 Announce Type: replace Abstract: Recent advances in medical vision language models guide the learning of visual representations; however, this form of supervision is constrained by

Reasoning Can Be Restored by Correcting a Few Decision Tokens

arXiv:2605.16874v1 Announce Type: new Abstract: Large reasoning models (LRMs) substantially outperform their base LLM counterparts on challenging reasoning benchmarks, yet it remains poorly understood

RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation

arXiv:2605.17522v1 Announce Type: new Abstract: Planning and acting in 3D environments is a fundamental capability for robotic manipulation in the real world. Although prior work has explored predicti

tutorialsarxiv-cs-ro

Rover: Context-aware Conflict Resolution with LLM

arXiv:2605.17279v1 Announce Type: cross Abstract: Code merging is a significant challenge, particularly in large-scale projects. Existing solutions, including program analysis and machine learning, sh

scHelix: Asymmetric Dual-Stream Integration via Explicit Gene-Level Disentanglement

arXiv:2605.18576v1 Announce Type: new Abstract: A critical challenge in single-cell RNA sequencing (scRNA-seq) integration is resolving the tension between eliminating batch effects and maintaining bi

Self-supervised local learning rules learn the hidden hierarchical structure of high-dimensional data

arXiv:2605.18557v1 Announce Type: new Abstract: The brain learns abstract representations of high-dimensional sensory input, but the plasticity rules that enable such learning are unknown. We study bi

SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs

arXiv:2512.04746v2 Announce Type: replace-cross Abstract: Extremely low-bit quantization is critical for efficiently deploying Large Language Models (LLMs), yet it often leads to severe performance de

Single Image Reflection Removal with Patch Reflectance Prior

arXiv:2312.03798v2 Announce Type: replace Abstract: Single Image Reflection Removal (SIRR) in real-world images is a challenging task due to diverse image degradations occurring on the glass surface d

Sparse Autoencoders are Topic Models

arXiv:2511.16309v2 Announce Type: replace Abstract: Sparse autoencoders (SAEs) are used to analyze embeddings, but their role and practical value are debated. We propose a new perspective on SAEs by d

Sparse Deep Additive Model with Interactions: Enhancing Interpretability and Predictability

arXiv:2509.23068v2 Announce Type: replace-cross Abstract: Recent advances in deep learning highlight the need for personalized models that can learn from small samples, handle high-dimensional feature

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation

arXiv:2605.18267v1 Announce Type: new Abstract: Normalizing flows (NFs) provide exact likelihoods and deterministic invertible sampling, but have historically lagged behind diffusion models for large-

StAD: Stein Amortized Divergence for Fast Likelihoods with Diffusion and Flow

arXiv:2605.16486v1 Announce Type: cross Abstract: Diffusion and flow-based models are ubiquitously used for generative modelling and density estimation. They admit a deterministic probability flow ord

Starve to Perceive: Taming Lazy Perception in VLMs with Constrained Visual Bandwidth

arXiv:2605.18603v1 Announce Type: new Abstract: Vision-Language Models (VLMs) deployed as situated agents in high-resolution visual environments require active perception -- the ability to dynamically