Search: “tutorials”

Imp-ACT: Adaptive Impedance Control and Action Chunking with Transformers to Learn Contact-Rich Manipulation from Demonstrations

arXiv:2609.31225v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to balance accurate motion tracking with compliant interaction, yet most visual-action policies leave complian

tutorialsarxiv-cs-ro

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Improving Molecular-Morphology Contrastive Pretraining using Deep-Learning-based Morphology Profiles

DGX agent

arXiv:2609.30433v1 Announce Type: new Abstract: Recent advancements in image-based profiling techniques have enabled the collection of high-volume cell morphology data, allowing new molecular embeddin

tutorialsarxiv-cs-lg

28 Sept 2026

LLPR: Location-aware learning and physics-based reconstruction for raindrop removal from a single image

arXiv:2609.30758v1 Announce Type: new Abstract: Raindrops can cause occlusion and distortion in the background scenes due to their adherence to windows or camera lenses. Existing raindrop removal meth

OpenAI, loosely paraphrased: sure my poorly trained pit bull has been biting all the neighbor kids, and, yeah, i unleashed it before finishi…

OpenAI, loosely paraphrased: sure my poorly trained pit bull has been biting all the neighbor kids, and, yeah, i unleashed it before finishing the fence, and i actually don’t know how to train pit bul

tutorialsgary-marcus--x

Probabilistic Robustness-driven Universal Adversarial Perturbations with Explainability against Deep Reinforcement Learning-based Intrusion Detection System

arXiv:2609.30605v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) enables adaptive intrusion detection in dynamic network environments but also exposes intrusion detection systems (IDS

Retrainable physics-integrated neural differentiable modeling of sintering across material systems

arXiv:2609.31518v1 Announce Type: cross Abstract: Sintering is widely used to manufacture ceramics, but coupled densification and grain growth, material-dependent kinetics, and sparse measurements com

SoGuDiff: Socially Guided Diffusion for Steerable, Norm-Grounded Robot Navigation

arXiv:2609.30560v1 Announce Type: new Abstract: Beyond collision avoidance, socially competent robot navigation requires adherence to implicit social conventions that vary across contexts, cultures, a

tutorialsarxiv-cs-ro

Spatial Information Bottleneck for Interpretable Visual Recognition

arXiv:2511.09239v2 Announce Type: replace Abstract: Deep neural networks typically learn spatially entangled representations that conflate discriminative foreground features with spurious background c

Stable initialization without the CLT

arXiv:2609.30633v1 Announce Type: new Abstract: Successful training of deep neural networks is highly dependent on the distribution of the initial weights. If the weights are too large, network traini

Structure-Guided Masked Autoencoders for Ultra-High Resolution Scientific Image Understanding

arXiv:2609.30682v1 Announce Type: new Abstract: Self-supervised pre-training with Vision Transformers, including Masked Autoencoders (MAE), is difficult to apply to gigapixel scientific images. Random

Why Clipping Matters in AdaGrad? Toward a High-Probability Theory under Generalized Smoothness

arXiv:2609.30276v1 Announce Type: new Abstract: We analyze the original same-step coordinate-wise AdaGrad under generalized smoothness and heavy-tailed noise with bounded variance. In this setting, lo

WorldTS: World Modeling for Multimodal Covariate-aware Time Series Forecasting

arXiv:2609.31162v1 Announce Type: new Abstract: Time series forecasting is typically framed as learning a direct mapping from historical to future observations in the observation space. However, seque

A Little Guide to Learning Distributed Algorithms for LLMS Training and Inference [D]

tutorialsr-machinelearning

Distributed Training and Inference both involves having a fundamental understanding of how distributed systems work in general Distributed Parallelism Tensor Parallelism Pipeline Parallelism Model Par

Open-source RL envs for the win. On Hugging Face of course!

tutorialsclem-delangue--x

Open-source RL envs for the win. On Hugging Face of course! was looking for a quiet weekend but xiaomi dropped their rl envs repo last night to put in perspective, if you have to buy some tasks like t

[P] A small MLP from scratch in NumPy with a GUI to look inside it while it trains (weight distributions, t-SNE per layer, neuron ablation...) [P]

tutorialsr-machinelearning

Hi everyone, I built an educational tool that shows what happens inside a small MLP while it trains, and I'd like some feedback from people who teach ML. Everything is plain NumPy, no autograd: manual

Yann LeCun's lab borrowed a trick from the human brain and more than doubled how often an AI found its way to a goal. The paper is called Te…

Yann LeCun's lab borrowed a trick from the human brain and more than doubled how often an AI found its way to a goal. The paper is called Temporal Straightening for Latent Planning, from NYU with Brow

tutorialsyann-lecun--x

A Study of the Limits of Collaborative DCT-Based Image Denoising via Interpretable Neural Networks

arXiv:2609.29334v1 Announce Type: new Abstract: Image denoising remains a fundamental problem in image restoration, with applications in photography, biomedical, and scientific imaging. Modern deep ne

Accelerate multimodal RL training with SkyRL on Amazon SageMaker HyperPod

Learn how to run SkyRL, an open-source reinforcement learning framework, on Amazon SageMaker HyperPod to post-train a Qwen3-VL-8B vision-language model with GRPO. This walkthrough covers building the

tutorialsaws-ml-blog

AIR: Analytic Imbalance Rectifier for Continual Learning

arXiv:2408.10349v2 Announce Type: replace-cross Abstract: Continual learning (CL) agents incrementally learn from sequentially arriving data and adapt to the dynamic, ever-changing nature of real-worl

Band-Attention Modulation Network for Robust Face Forgery Detection

arXiv:2404.06022v3 Announce Type: replace-cross Abstract: Face forgery detection faces critical challenges in generalizing to unseen manipulation techniques and remaining robust under image compressio

Can an LM, starting from random init (!!), learn to generate all of its pretraining data? Introducing Self-Play Pretraining with Zero Data. …

tutorialsemad-mostaque--x

Can an LM, starting from random init (!!), learn to generate all of its pretraining data? Introducing Self-Play Pretraining with Zero Data. Two models start from random initialization: a generator pro

Can Frozen Hyperspherical Features Guide the Selection of Pseudo Masks?

arXiv:2609.30080v1 Announce Type: new Abstract: Foundation segmenters such as SAM return several plausible masks for an unlabeled image, and a student trained on the wrong one inherits its errors. Cho

CFD Correction of Open Tip Clearance Flow in a Compressor Cascade Using VAE Latent Space Adaptation

arXiv:2609.28558v1 Announce Type: new Abstract: CFD predictions of open tip clearance flow in compressor cascades are subject to discrepancies relative to experiments, while experimental observations

Confident but Wrong: A Constrained Decoding Diagnostic for Low-Resource Automatic Post-Editing

arXiv:2609.29680v1 Announce Type: new Abstract: Automatic Post-Editing (APE) for low-resource languages (LRLs) often fails to improve Machine Translation (MT), and the score alone cannot say why: whet

CORDIAL: Calibrating Ordinal LLM Outputs from Few Labels

arXiv:2609.29807v1 Announce Type: new Abstract: A large language model (LLM) can turn a text into a distribution over an ordered scale, but that distribution is a noisy measurement: saturated, compres

Direct Message Approximation (DMA): A Consistency-Based Framework for Tractable Approximate Inference on Factor Graphs

arXiv:2609.29466v1 Announce Type: cross Abstract: Approximate message passing on factor graphs underlies two dominant families of probabilistic inference algorithms: expectation propagation (EP) and v

EgoSpeedUp: Transferring Human Manipulation Tempo to Robot Policies

arXiv:2609.29310v1 Announce Type: cross Abstract: Robot manipulation policies trained through imitation learning inherit not only the demonstrated behavior but also the conservative execution tempo of

EIB-Net: Entropy-Guided Information Bottleneck for Generalizable AI-Generated Image Detection

arXiv:2609.29064v1 Announce Type: cross Abstract: The proliferation of photorealistic AI-generated images demands robust detection methods that generalize across diverse generative models. While exist

ELiSe: Efficient Learning of Sequences in Structured Recurrent Networks

arXiv:2402.16763v3 Announce Type: replace-cross Abstract: Behavior can be described as a temporal sequence of actions driven by neural activity. To learn complex sequential patterns in neural networks

Evaluation of OpenAI o1: Opportunities and Challenges of AGI

arXiv:2409.18486v5 Announce Type: replace Abstract: This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, sp

Functional dynamic mode decomposition: Learning infinite-dimensional systems from data

arXiv:2609.29159v1 Announce Type: cross Abstract: Dynamic mode decomposition (DMD) is a data-driven method that computes the best linear approximation of the underlying dynamical system and decomposes

Generative Atmospheric Super-Resolution from Heterogeneous In Situ Observations through Composable Interfaces

arXiv:2609.29027v1 Announce Type: new Abstract: Atmospheric observations are sparse, heterogeneous, and unevenly distributed, whereas many generative atmospheric models learn distributions over regula

Guardrails or Roadblocks? Effects of Pedagogical Style and Context Awareness in AI Teaching Assistants for Programming

arXiv:2609.29995v1 Announce Type: cross Abstract: AI teaching assistants (AI TAs) backed by large language models (LLMs) and pedagogical guardrails are increasingly being integrated into programming c

How Datacor built self-service rental analytics with Amazon Quick Sight

Learn how Datacor built a self-service rental analytics experience for gas and welding distributors by embedding Amazon Quick Sight dashboards and natural language querying into its TrackAbout platfor

tutorialsaws-ml-blog

How To Do Things With Prompts

arXiv:2609.29657v1 Announce Type: new Abstract: When users address large language models, they produce directive speech acts whose pragmatic features differ from those of both everyday conversation an

Learning New Words from Unlabeled Test Data in Automatic Speech Recognition

arXiv:2609.28877v1 Announce Type: cross Abstract: New words are invented every day. A human listener can learn a new word by hearing it clearly once and inferring its usage from sentence context. This

Let Training Guide Selection: Online Synthetic Data Filtering via Real-Anchored Utility

arXiv:2609.29988v1 Announce Type: new Abstract: Synthetic data can scale training supervision when real-world data are limited, but noise and distribution mismatch can reduce its value. Existing synth

MorphIK: Morphology-Conditioned Neural Inverse Kinematics for Unknown Robots

arXiv:2609.29908v1 Announce Type: cross Abstract: Neural models can learn to generate various solutions to the inverse kinematics problem from data, but are usually limited to a single robot. We prese

Neuro-symbolic AI for Industrial Configuration

arXiv:2609.29947v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive performance on a wide range of generative tasks. Yet their probabilistic nature makes them, in isolat

Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Where is your robot car that can learn to drive…

Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Where is your robot car that can learn to drive in a few hours of practice like any 17 year old? Where is y

tutorialsyann-lecun--x

PePESeg3D: Perception Prior Enhances Multi-Scale Segmentation for 3D Gaussian Splatting

arXiv:2609.28645v1 Announce Type: new Abstract: Recent advancements in 3D Gaussian Splatting (3DGS) have extended its capabilities to multi-scale segmentation. Existing methods reconstruct a scene wit

Personalised federated learning for Riemannian and Euclidean EEG decoding

arXiv:2609.29037v1 Announce Type: cross Abstract: Federated learning (FL) lets EEG decoders learn from recordings of several subjects without pooling them. We consider two light EEG decoders, the Riem

RAPTOR: RAndom-projection Physics-informed Transient sOlveR

arXiv:2609.29714v1 Announce Type: cross Abstract: The complexity of time-domain simulation of modern power systems has increased significantly because converter-based resources introduce control dynam

Right Choice of Classification Algorithms Based on Reinforcement Learning for Prediction of Non-Alcoholic Fatty Liver

arXiv:2609.29181v1 Announce Type: new Abstract: There are many complex issues in the world of artificial intelligence. Some of these problems are solved using other artificial intelligence methods, wh

RLVR landscapes for iterated multiplications can be benign: Insights from spin-glass theory

arXiv:2609.28625v1 Announce Type: new Abstract: Despite the importance of reinforcement learning with verifiable rewards (RLVR), the extent to which it can learn new reasoning capabilities remains deb

Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput

Learn how to scale Mixture-of-Experts (MoE) reinforcement learning on Amazon EKS using Elastic Fabric Adapter (EFA) and DeepEP. This post presents an architecture that combines Amazon EKS, EFA, and Am

tutorialsaws-ml-blog

Self-Play Pretraining with Zero Data

arXiv:2609.30063v1 Announce Type: new Abstract: Advances in language modeling have been driven by scaling pretraining on ever more data. Yet, the training data is still largely curated on the model's

SplatLabel: Pseudo-Labelling through 4D Gaussian Splatting

arXiv:2609.29836v1 Announce Type: new Abstract: While 2D Vision Foundation Models offer a pathway to automate 3D semantic pseudo-labelling, translating these priors into robust 3D representations typi