Search: “tutorials”

Beyond Patient Invariance: Learning Cardiac Dynamics via Action-Conditioned JEPAs

arXiv:2604.22618v1 Announce Type: new Abstract: Self-supervised learning in healthcare has largely relied on invariance-based objectives, which maximize similarity between different views of the same

CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting

DGX agent

arXiv:2604.22636v1 Announce Type: cross Abstract: Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual sett

tutorialsarxiv-cs-lg

27 Apr 2026

Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions

arXiv:2512.20831v2 Announce Type: replace Abstract: Real-world sequential decision-making often involves parameterized action spaces that require both, decisions regarding discrete actions and decisio

Distilling Vision Transformers for Distortion-Robust Representation Learning

arXiv:2604.22529v1 Announce Type: new Abstract: Self-supervised learning has achieved remarkable success in learning visual representations from clean data, yet remains challenging when clean observat

Evidence of an Emergent 'Self' in Continual Robot Learning

arXiv:2603.24350v2 Announce Type: replace-cross Abstract: A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a 'sel

GCImOpt: Learning efficient goal-conditioned policies by imitating optimal trajectories

arXiv:2604.22724v1 Announce Type: new Abstract: Imitation learning is a well-established approach for machine-learning-based control. However, its applicability depends on having access to demonstrati

tutorialsarxiv-cs-ro

GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms

arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th

How to build scalable web apps with OpenAI's Privacy Filter

This article likely discusses techniques for building web applications that integrate OpenAI's APIs while maintaining user privacy through filtering mechanisms. It probably covers implementation strat

tutorialshugging-face

It just takes a little time and care to engage with the work of new folks in the field -- but it can make a big difference :D

tutorialsjeremy-howard--x

It just takes a little time and care to engage with the work of new folks in the field -- but it can make a big difference :D On a more personal note, I'm grateful to @jeremyphoward for helping me bre

jBOT: Semantic Jet Representation Clustering Emerges from Self-Distillation

arXiv:2601.11719v3 Announce Type: replace Abstract: Self-supervised learning, in the context of foundation model training, is a powerful pre-training method for learning feature representations withou

Join the new AI Agents Vibe Coding Course from Google and Kaggle

Google and Kaggle are offering a free five-day AI Agents Intensive course running June 15–19, 2026. The course teaches 'vibe coding' to create programs using natural language, with hands-on projects t

tutorialsgoogle-ai

last week we dropped a super comprehensive guide on runtime requirements for long running agents! this week i'll be diving into each require…

tutorialsharrison-chase--x

last week we dropped a super comprehensive guide on runtime requirements for long running agents! this week i'll be diving into each requirement and runtime capability that meets it, here's the lineup

Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data

arXiv:2604.22212v1 Announce Type: cross Abstract: In spite of the utility of 3-D electron back-scattered diffraction (EBSD) microscopy, the data collection process can be time-consuming with serial-se

One Shot Learning for Edge Detection on Point Clouds

arXiv:2604.22354v1 Announce Type: new Abstract: Each scanner possesses its unique characteristics and exhibits its distinct sampling error distribution. Training a network on a dataset that includes d

PASR: Pose-Aware 3D Shape Retrieval from Occluded Single Views

arXiv:2604.22658v1 Announce Type: new Abstract: Single-view 3D shape retrieval is a fundamental yet challenging task that is increasingly important with the growth of available 3D data. Existing appro

Pliable rejection sampling

arXiv:2604.22385v1 Announce Type: cross Abstract: Rejection sampling is a technique for sampling from difficult distributions. However, its use is limited due to a high rejection rate. Common adaptive

Pre-trained Large Language Models Learn Hidden Markov Models In-context

arXiv:2506.07298v3 Announce Type: replace-cross Abstract: Hidden Markov Models (HMMs) are foundational tools for modeling sequential data with latent Markovian structure, yet fitting them to real-worl

PrivSTRUCT: Untangling Data Purpose Compliance of Privacy Policies in Google Play Store

arXiv:2604.22157v1 Announce Type: cross Abstract: Existing research typically treats privacy policies as flat, uniform text, extracting information without regard for the document's logical hierarchy.

Structure-Guided Diffusion Model for EEG-Based Visual Cognition Reconstruction

arXiv:2604.22649v1 Announce Type: cross Abstract: Objective: Decoding visual information from electroencephalography (EEG) is an important problem in neuroscience and brain-computer interface (BCI) re

the difference is that we don’t hype giving 12 year-olds bulldozers. of course it’s a kind of user error when a model destroys all of us…

the difference is that we don’t *hype* giving 12 year-olds bulldozers. *of course* it’s a kind of user error when a model destroys all of user’s data and they didn’t have a backup. that’s the point. v

tutorialsgary-marcus--x

Useful nonrobust features are ubiquitous in biomedical images

arXiv:2604.22579v1 Announce Type: cross Abstract: We study whether deep networks for medical imaging learn useful nonrobust features - predictive input patterns that are not human interpretable and hi

“AI: it feels most impressive when you don’t know much about the subject, don’t care or don’t have a clear idea of what the you want… Once y…

“AI: it feels most impressive when you don’t know much about the subject, don’t care or don’t have a clear idea of what the you want… Once you know what something should feel or look like, it becomes

tutorialsgary-marcus--x

ChatGPT's GPT Image 2 is actually incredible. Full visual breakdown of how to fix my desk setup. I refuse to get rid of my second monitor (I…

tutorialsallie-k--miller--x

ChatGPT's GPT Image 2 is actually incredible. Full visual breakdown of how to fix my desk setup. I refuse to get rid of my second monitor (I need 3 for live zoom client workshops), but this was the ki

Fieri Iussit https://x.com/emollick/status/1969993499157446943?s=20

tutorialsethan-mollick--x

Fieri Iussit https://x.com/emollick/status/1969993499157446943?s=20 My modest proposal for how to acknowledge AI work is to use the Latin phase 'Fieri Iussit,' which means 'commanded to be made,' a co

Our principles

OpenAI's core principles outline the company's commitment to developing artificial intelligence safely and beneficially, emphasizing responsible AI development and deployment. These principles likely

tutorialsopenai

Great paper on improving proactive agents. (bookmark it) Proactive agents act before you do. But how do you evaluate something that's suppos…

Great paper on improving proactive agents. (bookmark it) Proactive agents act before you do. But how do you evaluate something that's supposed to anticipate needs you haven't expressed? This work intr

tutorialsdair-ai--x

25 Apr 2026

Model Risk Management in 2026: A Banker’s Guide to the Revised Interagency Guidance

This guide addresses updated regulatory requirements for model risk management in banking institutions, likely covering the 2026 revisions to interagency guidance issued by banking regulators. It prov

tutorialsdatabricks

25 Apr 2026

There's still time to submit. The applications coming in are pretty good, the bar is high.

tutorialscristobal-valenzuela--x

There's still time to submit. The applications coming in are pretty good, the bar is high. Two weeks to pitch a show you wish existed. $100K in cash prizes. Bring your biggest, most ambitious ideas to

25 Apr 2026

A Comprehensive Guide to Differential Privacy: From Theory to User Expectations

arXiv:2509.03294v3 Announce Type: replace-cross Abstract: The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurit

Adaptive Instruction Composition for Automated LLM Red-Teaming

arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin

Architecture of an AI-Based Automated Course of Action Generation System for Military Operations

arXiv:2604.20862v1 Announce Type: new Abstract: The automation system for Course of Action (CoA) planning is an essential element in future warfare. As maneuver speeds increase, surveillance ranges ex

Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks

arXiv:2305.01626v4 Announce Type: replace-cross Abstract: Computational models of syntax are predominantly text-based. Here we propose that the most basic first step in the evolution of syntax can be

Design, Modelling and Experimental Evaluation of a Tendon-driven Wrist Abduction-Adduction Mechanism for an upper limb exoskeleton

arXiv:2604.20893v1 Announce Type: new Abstract: Wrist exoskeletons play a vital role in rehabilitation and assistive applications, yet conventional actuation mechanisms such as electric motors or pneu

tutorialsarxiv-cs-ro

DualSplat: Robust 3D Gaussian Splatting via Pseudo-Mask Bootstrapping from Reconstruction Failures

arXiv:2604.21631v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) achieves real-time photorealistic rendering, its performance degrades significantly when training images contain tran

Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI

arXiv:2604.21300v1 Announce Type: new Abstract: Learning robust representations of authorial style is crucial for authorship attribution and AI-generated text detection. However, existing methods ofte

tutorialsarxiv-cs-cl

Exploring Continual Fine-Tuning for Enhancing Language Ability in Large Language Model

arXiv:2410.16006v3 Announce Type: replace Abstract: A common challenge towards the adaptability of Large Language Models (LLMs) is their ability to learn new languages over time without hampering the

tutorialsarxiv-cs-cl

Graph Neural Network-Informed Predictive Flows for Faster Ford-Fulkerson and PAC-Learnability

arXiv:2604.21175v1 Announce Type: new Abstract: We propose a learning-augmented framework for accelerating max-flow computation and image segmentation by integrating Graph Neural Networks (GNNs) with

Information Bottleneck-Guided Heterogeneous Graph Learning for Interpretable Neurodevelopmental Disorder Diagnosis

arXiv:2502.20769v3 Announce Type: replace Abstract: Developing interpretable models for neurodevelopmental disorders (NDDs) diagnosis presents significant challenges in effectively encoding, decoding,

JEPAMatch: Geometric Representation Shaping for Semi-Supervised Learning

arXiv:2604.21046v1 Announce Type: new Abstract: Semi-supervised learning has emerged as a powerful paradigm for leveraging large amounts of unlabeled data to improve the performance of machine learnin

Learn Weightlessness: Imitate Non-Self-Stabilizing Motions on Humanoid Robot

arXiv:2604.21351v1 Announce Type: new Abstract: The integration of imitation and reinforcement learning has enabled remarkable advances in humanoid whole-body control, facilitating diverse human-like

tutorialsarxiv-cs-ro

Learning Linear Regression with Low-Rank Tasks in-Context

arXiv:2510.04548v2 Announce Type: replace-cross Abstract: In-context learning (ICL) is a key building block of modern large language models, yet its theoretical mechanisms remain poorly understood. It

Learning to Emulate Chaos: Adversarial Optimal Transport Regularization

arXiv:2604.21097v1 Announce Type: cross Abstract: Chaos arises in many complex dynamical systems, from weather to power grids, but is difficult to accurately model using data-driven emulators, includi

Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation

arXiv:2604.20858v1 Announce Type: cross Abstract: Sequential recommendation has rapidly advanced in click-through rate prediction due to its ability to model dynamic user interests. A key challenge, h

Preconditioned DeltaNet: Curvature-aware Sequence Modeling for Linear Recurrences

arXiv:2604.21100v1 Announce Type: new Abstract: To address the increasing long-context compute limitations of softmax attention, several subquadratic recurrent operators have been developed. This work

PrismaDV: Automated Task-Aware Data Unit Test Generation

arXiv:2604.21765v1 Announce Type: new Abstract: Data is a central resource for modern enterprises, and data validation is essential for ensuring the reliability of downstream applications. However, ex

Reshoot-Anything: A Self-Supervised Model for In-the-Wild Video Reshooting

arXiv:2604.21776v1 Announce Type: new Abstract: Precise camera control for reshooting dynamic videos is bottlenecked by the severe scarcity of paired multi-view data for non-rigid scenes. We overcome

S1-VL: Scientific Multimodal Reasoning Model with Thinking-with-Images

arXiv:2604.21409v1 Announce Type: new Abstract: We present S1-VL, a multimodal reasoning model for scientific domains that natively supports two complementary reasoning paradigms: Scientific Reasoning

Sapiens2

arXiv:2604.21681v1 Announce Type: new Abstract: We present Sapiens2, a model family of high-resolution transformers for human-centric vision focused on generalization, versatility, and high-fidelity o