tutorials

This post right here officer Let me know when your engineers ship 8x LESS code

tutorialsjeremy-howard--x

This post likely discusses Jeremy Howard's commentary on software engineering efficiency and the goal of shipping significantly reduced code volumes—possibly advocating for more concise, optimized cod

4 Jun 2026

Tutorials

Today we're launching the Main Street AI Accelerator with the U.S. Small Business Administration. We're committing $25M in Computer credits,…

DGX agent

Today we're launching the Main Street AI Accelerator with the U.S. Small Business Administration. We're committing 25M in Computer credits, 250 each for up to 100,000 eligible companies, in honor of A

tutorialsperplexity--x

4 Jun 2026

We built a cool project that shows you how to compose our core document intelligence primitives into a reusable pipeline that turn your docu…

We built a cool project that shows you how to compose our core document intelligence primitives into a reusable pipeline that turn your documents into machine-readable data. Come check it out! https:/

tutorialsjerry-liu--x

4 Jun 2026

what makes building on replit different? it all happens in one place. → describe your idea in plain english, get working software → generate…

what makes building on replit different? it all happens in one place. → describe your idea in plain english, get working software → generate UI, add auth + databases, deploy → collaborate with your te

tutorialsreplit--x

4 Jun 2026

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners

arXiv:2606.03685v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) improves end-to-end classical planning in large language models (LLMs), but do these models also learn to represent and r

A few months ago, I found an anonymous sockpuppet account linked to the OpenAI/a16z super PAC. Now, @TaylorLorenz and I have uncovered two m…

tutorialsjeremy-howard--x

A few months ago, I found an anonymous sockpuppet account linked to the OpenAI/a16z super PAC. Now, @TaylorLorenz and I have uncovered two more — and they're even more brazen than the first. https://x

A Locally Deployed RAG-Based Academic Advising System for Course Selection

arXiv:2606.02983v1 Announce Type: new Abstract: The correct sequence of courses in the curriculum based on prerequisites between courses is of great importance for students to develop their knowledge

tutorialsarxiv-cs-cl

A Systematic Evaluation of Current Architectures in Wind Power Forecasting

arXiv:2606.02849v1 Announce Type: new Abstract: Interval wind speed forecasting is essential for the efficient integration of wind energy into power systems, as it accounts for the inherent uncertaint

AI-Generated Traces for Novice Programmers: Learning Effects and Learner Differences in a Multi-Institutional Study

arXiv:2606.03288v1 Announce Type: cross Abstract: Introductory programming (CS1) courses often struggle to support students' understanding of program execution. While visualizations can make execution

Causal Evidence of Stack Representations in Modeling Counter Languages Using Transformers

arXiv:2606.03398v1 Announce Type: cross Abstract: Formal languages have proven to be effective conduits to understand the inner mechanisms of transformers. Past work has shown that transformers traine

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures

arXiv:2606.02912v1 Announce Type: cross Abstract: Forecasting seismic waveforms beyond observed data remains challenging due to the nonlinear, dispersive, and multi-scale nature of seismic wave propag

Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering

arXiv:2606.03269v1 Announce Type: new Abstract: Visual Question Answering (VQA) is the task of answering questions about images, requiring the integration of multimodal input and reasoning. Modular ap

Expanding the Reach of Document Translation – New Capabilities Announced at Microsoft Build

tutorialsmicrosoft-foundry

Learn how new Document Translation capabilities in Azure Translator, available in Foundry Tools, help developers translate images, PDFs, Office files, DITA, XLIFF, and future LLM-powered document work

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

arXiv:2606.03050v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised

FFR: Forward-Forward Learning for Regression

arXiv:2606.03927v1 Announce Type: cross Abstract: The Forward-Forward (FF) algorithm offers a computationally efficient and biologically plausible alternative to backpropagation (BP) by training neura

Formalizing the Binding Problem

arXiv:2606.03976v1 Announce Type: cross Abstract: Representations of the world, arguably, contain information about features (e.g. something is blue, something is a circle) but also information about

From Video to Control: A Survey of Learning Manipulation Interfaces from Temporal Visual Data

arXiv:2604.04974v2 Announce Type: replace Abstract: Video is a scalable observation of physical dynamics: it captures how objects move, how contact unfolds, and how scenes evolve under interaction --

tutorialsarxiv-cs-ro

Fundamental’s Large Tabular Model NEXUS is now available on Amazon SageMaker JumpStart

Fundamental's NEXUS is a foundation model designed specifically for tabular data, trained on billions of tabular datasets using Amazon SageMaker HyperPod to understand non-linear relationships across

tutorialsaws-ml-blog

Grounding Functional Similarity by Invariance-Aware Model Stitching

arXiv:2505.20142v2 Announce Type: replace Abstract: In deep learning, functional similarity evaluation quantifies the extent to which independently trained models learn similar input--output relations

GS-ROR^2: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Reconstruction

arXiv:2406.18544v4 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has shown a powerful capability for novel view synthesis due to its detailed expressive ability and highly efficient re

Hierarchical RBF-KAN and RBF-SKAN Architectures for Multidimensional Function Approximation and Random Field Learning

arXiv:2606.02936v1 Announce Type: new Abstract: In this manuscript, we propose and analyze hierarchical Kolmogorov--Arnold neural network architectures employing radial basis functions as activation f

HiSE: A Lightweight Hierarchical Semantic Explainer for Heterogeneous Graph Neural Networks

arXiv:2606.03495v1 Announce Type: new Abstract: Heterogeneous graph neural networks (HGNNs) have demonstrated remarkable performance in modeling complex relational data, however their interpretability

How to build self-driving AI operations on Amazon Bedrock at scale

In this post, we introduce Amazon Bedrock Ops Alert, a three-layer automated monitoring solution that proactively detects operational issues, dynamically adjusts alarm thresholds, classifies alarms by

tutorialsaws-ml-blog

IDO: Incongruity-aware Distribution Optimization for Multimodal Fake News Detection

arXiv:2606.03418v1 Announce Type: new Abstract: Multimodal fake news detection aims to identify the authenticity of news. Existing multimodal fake news detection methods mainly focus on cross-modal co

Introduction to optimization methods for training SciML models

arXiv:2601.10222v2 Announce Type: replace-cross Abstract: Optimization is central to both modern machine learning (ML) and scientific machine learning (SciML), yet the structure of the underlying opti

Learn When and Where to Connect: Adaptive Virtual Nodes for Dynamic Message Passing on Graphs

arXiv:2606.03068v1 Announce Type: cross Abstract: While Virtual Nodes (VNs) are often utilized in Message Passing Neural Networks (MPNNs) to facilitate effective message passing, existing VN-based met

Learning Coherent Representations: A Topological Approach to Interpretability

arXiv:2606.02841v1 Announce Type: new Abstract: Deep neural networks learn representations where individual features often lack interpretable meaning; a single neuron may activate for scattered, unrel

Learning without training: The implicit dynamics of in-context learning

arXiv:2507.16003v4 Announce Type: replace Abstract: One of the most striking features of Large Language Models (LLMs) is their ability to learn in-context. Namely at inference time an LLM is able to l

tutorialsarxiv-cs-cl

Lethe: Adapter-Augmented Dual-Stream Update for Persistent Knowledge Erasure in Federated Unlearning

arXiv:2601.22601v2 Announce Type: replace Abstract: Federated unlearning (FU) aims to erase designated client-level, class-level, or sample-level knowledge from a global model. Existing studies common

Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden States

arXiv:2606.02907v1 Announce Type: cross Abstract: Linear probing of large language model (LLM) hidden states is widely used to claim that models learn distinct representations for different reasoning

Nice primer on post-training reasoning data. (bookmark it) This is one of the first primers to pull the scattered post-training reasoning-da…

Nice primer on post-training reasoning data. (bookmark it) This is one of the first primers to pull the scattered post-training reasoning-data literature into one place, synthesizing over 150 public s

tutorialsdair-ai--x

Oscillatory State-Space Models as Inductive Biases for Physics-Informed Neural PDE Solvers

arXiv:2606.02623v1 Announce Type: cross Abstract: Solving time-dependent partial differential equations (PDEs) is an important problem in computational science and engineering. Physics-informed neural

Perplexity Computer is for growing businesses. Computer connects to 400+ tools for every type of company, including Intuit QuickBooks, Verce…

Perplexity Computer is for growing businesses. Computer connects to 400+ tools for every type of company, including Intuit QuickBooks, Vercel, Shopify, Canva, and more. Learn more about how people are

tutorialsperplexity--x

Physics-informed diffusion models in spectral space

arXiv:2602.09708v2 Announce Type: replace-cross Abstract: We propose physics-informed spectral diffusion (PISD), a methodology that combines generative latent diffusion models with physics-informed ma

PRISM: Rethinking Atmospheric Scattering Reconstruction as a Unified Understanding and Restoration Model for Real-world Dehazing

arXiv:2604.07048v2 Announce Type: replace Abstract: Real-world image dehazing (RID) aims to remove haze-induced degradation from real scenes. This task remains challenging due to non-uniform haze dist

PURGE: Projected Unlearning via Retain-Guided Erasure

arXiv:2606.03808v1 Announce Type: cross Abstract: We propose PURGE, a machine unlearning algorithm built on a simple but an under-exploited observation: continual learning (CL) and machine unlearning

Re-Evaluating Continual Learning with Few-Shot Adaptation

arXiv:2606.03843v1 Announce Type: cross Abstract: Continual learning methods aim to maximize the stability and plasticity of machine learning models that are trained on a sequence of tasks. The standa

Reasoning over Grammar: Can Synthetic Linguistic Reasoning Traces Enhance Low-Resource Machine Translation?

arXiv:2606.03782v1 Announce Type: new Abstract: Large language models (LLMs) offer a promising approach to machine translation (MT) for extremely low-resource languages by incorporating linguistic res

tutorialsarxiv-cs-cl

Reducing container cold start times using SOCI index on DLAMI and DLC

In this post, we look at how to use SOCI on publicly available Deep Learning AMIs and Containers, when to use the various SOCI modes provided by the tool, and how to quickly and efficiently use this t

tutorialsaws-ml-blog

SAIL: Sound Abstract Interpreters with LLMs

arXiv:2511.13663v2 Announce Type: replace-cross Abstract: How to construct globally sound abstract interpreters to safely approximate program behaviors remains a bottleneck in abstract interpretation.

SaluNet: Enabling Total Plasticity in Normalization-Free Deep Networks

arXiv:2606.02927v1 Announce Type: new Abstract: Normalization layers such as BatchNorm and LayerNorm have long been considered essential for stable training in deep networks. This work demonstrates th

Text-to-Image Models Need Less from Text Encoders Than You Think

arXiv:2606.03715v1 Announce Type: new Abstract: Text-to-image models rely on text prompts as their primary interface to human intent. Prompts are encoded by a text encoder into embeddings that conditi

the best agents aren't just built with the best models: they're built with harnesses purpose-built for the task at hand here's a guide on ho…

tutorialsharrison-chase--x

the best agents aren't just built with the best models: they're built with harnesses purpose-built for the task at hand here's a guide on how to build a harness that's really good at feeding the model

THE PROMPT THAT REPLACES YOUR WORKFLOW AUDIT: You are my business transformation strategist. I want you to find the real AI-era business tra…

tutorialsallie-k--miller--x

THE PROMPT THAT REPLACES YOUR WORKFLOW AUDIT: You are my business transformation strategist. I want you to find the real AI-era business transformation hiding inside my work by starting from goals, bu

Toward Gripper-Integrated Active Electrosense for Pre-Contact Sensing in Underwater Soft Grippers

arXiv:2606.03204v1 Announce Type: new Abstract: Underwater manipulation often occurs under degraded visibility due to turbidity, glare, and gripper occlusion, limiting the reliability of vision-based

tutorialsarxiv-cs-ro

Transformer-Guided Content-Adaptive Graph Learning for Hyperspectral Unmixing

arXiv:2509.03376v2 Announce Type: replace Abstract: Hyperspectral unmixing (HU) targets to decompose each mixed pixel in remote sensing images into a set of endmembers and their corresponding abundanc

Video-Mirai: Autoregressive Video Diffusion Models Need Foresight

arXiv:2606.03971v1 Announce Type: new Abstract: Causal video generators must predict from the past, but they need not learn only from it. In streaming autoregressive video diffusion, each emitted segm

Visual Graph Scaffolds for Structural Reasoning in Large Language Models

arXiv:2606.02673v1 Announce Type: new Abstract: Graphs have been used to enhance large language models (LLMs) for structured reasoning, mostly as external knowledge sources are provided to models at t