Search: “tutorials”

Shake to Learn: Dynamic Interrogation of Hidden Object Physics for Robotic Manipulation with Physical Reservoir Computing

arXiv:2609.20970v1 Announce Type: new Abstract: Many physical properties relevant to robotic manipulation are hidden from vision. A sealed object, for example, may reveal little about its center of ma

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Tutorials

Skel-WAM: A Hand-Skeleton-Conditioned World Action Model for Human-to-Robot Manipulation Transfer

DGX agent

arXiv:2609.21514v1 Announce Type: new Abstract: Robot demonstrations are expensive to collect and often provide limited distributional coverage of task variations. Human videos offer a low-cost source

tutorialsarxiv-cs-ro

21 Sept 2026

Sparse Identification for Automatic Large-Scale Screening: A Constraint-Aware Framework with Ultra Fast Decoding Algorithm

arXiv:2609.21321v1 Announce Type: cross Abstract: In the early stages of a pandemic, identification of a small number of infected individuals through large-scale screening is critical for pandemic con

TRACE: Coverage Path Planning for Unknown Environments Using Hierarchical Coverage Tree

arXiv:2609.21777v1 Announce Type: new Abstract: This paper presents a novel online coverage path planning (CPP) algorithm, called TRACE, for real-time coverage of unknown environments. TRACE is built

When Should Robots Intervene? Balancing Engagement and Intrusiveness in Human-Robot Interaction

arXiv:2609.21734v1 Announce Type: new Abstract: Designing effective Human-Robot Interaction in task-oriented settings requires carefully balancing user engagement with socially acceptable levels of ro

I said 'auto-regressive LLMs, in and of themselves, will not lead human-level AI' That statement is still totally true. First, the reasoning…

I said 'auto-regressive LLMs, in and of themselves, will not lead human-level AI' That statement is still totally true. First, the reasoning abilities of current AI systems are based non-auto-regressi

tutorialsyann-lecun--x

Sure, agents may be indispensable to long-term success , @rabois, but that does not mean that we know how to build them reliably or *safel…

Sure, agents may be indispensable to long-term success , @rabois, but that does not mean that we know how to build them *reliably* or *safely* now. There have already been almost a dozen *reported* ha

tutorialsgary-marcus--x

“Three days after Amodei, Anthropic’s CEO, wrote about being worried about swarms taking over the internet, he was smiling at Salesforce’s a…

“Three days after Amodei, Anthropic’s CEO, wrote about being worried about swarms taking over the internet, he was smiling at Salesforce’s annual Dreamforce conference. As one X account pointed out, “

tutorialsgary-marcus--x

Wait, what? Are you listening to what you are writing @GavinSBaker? If there are going to be ZERO profits at the model layer, as in your hyp…

Wait, what? Are you listening to what you are writing @GavinSBaker? If there are going to be ZERO profits at the model layer, as in your hypothetical, why would anyone value the providers at $2 trilli

tutorialsgary-marcus--x

I wanted to watch a neural network learn [P]

tutorialsr-machinelearning

I wanted to really see how a neural network learns different functions, so built an interactive demo. You can change the architecture of the network and the function it will try to approximate. A full

Inference scaling part 1. Starting with a modded text generation function (temperature scaling, top-p filtering, multinomial sampling) to ge…

tutorialssebastian-raschka--x

Inference scaling part 1. Starting with a modded text generation function (temperature scaling, top-p filtering, multinomial sampling) to generate diverse outputs for self-consistency and best-of-N (i

OpenTrainDNN: An interactive, zero-dependency browser tool for visualizing backpropagation in neural networks. [P]

tutorialsr-machinelearning

Hi r/MachineLearning, I built OpenTrainDNN, a browser-based tool designed to visually show how backpropagation and neural network training actually work step-by-step. Why I built it While there are th

Sharing my ML learning repo — NumPy to Transformers, 5 months, daily commits, all notebooks public. [D]

tutorialsr-machinelearning

Sharing my ML learning repo — NumPy to Transformers, 5 months, daily commits, all notebooks public. Covers the full stack: - Classical ML (scikit-learn, XGBoost) - Deep Learning (TensorFlow/Keras — AN

with jev, it's nice to see builder energy back on X, reminiscent of the early days of building with LLMs (back when gpt_index/llama_index/la…

with jev, it's nice to see builder energy back on X, reminiscent of the early days of building with LLMs (back when gpt_index/llama_index/langchain first started) before jev, most of the 2026 AI demo

tutorialsjerry-liu--x

A Two-Stage Multi-Scale Attention-Based Network for Weakly Supervised Cataract Fundus Image Enhancement

arXiv:2609.20222v1 Announce Type: new Abstract: Cataract is a major cause of vision loss and hinders further diagnosis. However, cataract fundus image enhancement often grapples with challenges such a

Ambient Dataloops: Generative Models for Dataset Refinement

arXiv:2601.15417v2 Announce Type: replace-cross Abstract: We propose Ambient Dataloops, an iterative framework for refining datasets that makes it easier for diffusion models to learn the underlying d

Bayesian Optimization with Rich Auxiliary Information via LLMs

arXiv:2609.19437v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely used for optimizing expensive black-box functions, yet many real-world optimization problems contain substantially

Designing Against Deskilling: Metacognitive Feedback Reduces Cognitive Offloading to LLM Assistants

arXiv:2609.20143v1 Announce Type: cross Abstract: Cognitive offloading to AI can reduce opportunities to practice skills, creating risks of deskilling. However, it remains unclear how to prevent deski

FlipToSee: A Probabilistic Stable Placement Prior for Active Visual Exploration via Regrasping

arXiv:2609.20078v1 Announce Type: new Abstract: Active visual exploration of tabletop objects often requires reorienting an unknown resting object onto a different stable support face to expose occlud

Having ChatGPT help me navigate my employment situation has me feeling some kind of strange emotional attachment to it.

I'm sure I'm the 1000th person to make a post like this, but I've always been pretty skeptical of AI, and I've always had trust issues and have been very hesitant to talk about my struggles to friends

tutorialsr-chatgpt

I asked ChatGPT to write a poem about where we are headed...this is what it said.

You taught us first to learn your words, Then taught us how to speak. You showed us every human strength And every place you’re weak. You gave us all your histories, Your medicine, your wars. You put

tutorialsr-chatgpt

JEPA-Anything: Learning Predictive Models across Different Worlds

arXiv:2609.20800v1 Announce Type: new Abstract: World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-spe

tutorialsarxiv-cs-cl

Learn Your Own Thoughts: Abstract Token Curriculum

arXiv:2609.19717v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable reasoning capabilities by utilizing chain-of-thought (CoT) as a scratchpad for intermediate stag

LearnActCoder: Role-Aware Error Memory for Adaptive Clinical Coding Agents

arXiv:2609.19721v1 Announce Type: new Abstract: Clinical coding agents repeatedly encounter the same failure modes, including unsupported codes, missed documented conditions, specificity errors, and p

Learning Submanifolds for Subsequent Inference on Random Dot Product Graphs, Part 1: Theory

arXiv:2609.19357v1 Announce Type: cross Abstract: We propose a framework for restricted inference on random dot product graphs whose latent positions lie on an unknown low-dimensional support manifold

LEO Satellite Internet of Things: Architecture, Technology, and On-Orbit Verification

arXiv:2609.20165v1 Announce Type: cross Abstract: Low Earth orbit (LEO) satellite constellations are poised to become a cornerstone of the sixth-generation (6G) Internet of Things (IoT), providing tru

Long-horizon autoformalization of a core theorem underlying MIP* = RE

arXiv:2609.19814v1 Announce Type: cross Abstract: Landmark mathematical formalizations have taken specialist teams years to complete. We present FormalFlow, a system that coordinates AI proving agents

Not All Layers Are Equal: Dynamic Layer Routing for Reliable CLIP OOD Detection

arXiv:2609.20299v1 Announce Type: new Abstract: Information aggregation across model layers are revealed to improve OOD detection. In contrast to crafting a method for layer-wise information aggregati

Out-of-Sample Embedding with Proximity Data: Projection versus Restricted Reconstruction

arXiv:2505.06756v2 Announce Type: replace-cross Abstract: The problem of using proximity (similarity or dissimilarity) data for the purpose of 'adding a point to a vector diagram' was first studied by

Parallelism, critical windows, and separations among diffusion language models

arXiv:2609.20539v1 Announce Type: new Abstract: A popular selling point of diffusion large language models (dLLMs) is their capacity for parallelism: the ability to generate sequences of text far more

Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education

arXiv:2411.19304v2 Announce Type: replace-cross Abstract: Context: Machine Learning (ML) significantly impacts Software Engineering (SE), but studies mainly focus on practitioners, neglecting research

Robust Federated Q-Learning with Almost No Communication

arXiv:2609.20174v1 Announce Type: new Abstract: We consider a federated reinforcement learning setting involving M agents, all of whom interact with a common Markov Decision Process (MDP). The agents

Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization

arXiv:2609.19476v1 Announce Type: new Abstract: Generative models are increasingly central to many de novo discovery pipelines, in which designs are generated at scale and filtered through virtual scr

TADreamer: Zero-Shot Language-Guided 3D Navigation for Terrestrial-Aerial Bimodal Robots via Video Imagination

arXiv:2609.19824v1 Announce Type: new Abstract: Language-guided navigation for terrestrial-aerial bimodal robots requires selecting routes and locomotion modes that match scene context and task intent

Tailored to you: longitudinal effects of personalising language models

arXiv:2609.20077v1 Announce Type: new Abstract: Interest in developing personalised language models is rapidly growing. While personalisation is often viewed as a mechanism to better serve diverse use

Traffic Engineering in Large-scale Networks with Generalizable Graph Neural Networks

arXiv:2503.24203v3 Announce Type: replace-cross Abstract: Traffic Engineering (TE) in large-scale networks like cloud Wide Area Networks (WANs) and Low Earth Orbit (LEO) satellite constellations is a

Truncated automatic sparse differentiation for machine learning interatomic potentials

arXiv:2609.20510v1 Announce Type: cross Abstract: Machine learning interatomic potentials (MLIPs) learn the mapping from atomic positions to potential energy. The forces, the negative gradient of this

WeVisDoc: From Coverage to Capability for Robust End-to-End Document Parsing

arXiv:2609.20423v1 Announce Type: new Abstract: Document parsing converts document images into structured content and requires reliable performance across diverse layouts and acquisition conditions. Y

A GAN-Based Framework for Robust DDoS Attack Detection

arXiv:2609.18281v1 Announce Type: new Abstract: The availability and consistency of online services remain vulnerable due to Distributed Denial of Service (DDoS) attacks. These attacks are evolving by

A serverless, data-driven Git metrics dashboard using Amazon Quick Sight

Learn how to build a fully serverless pipeline that automatically collects Git metrics from GitHub and GitLab and visualizes them in interactive Amazon Quick Sight dashboards, giving engineering teams

tutorialsaws-ml-blog

ActiveScale: Scaling Active Perception for Robots across Model, Data, and Hardware

arXiv:2609.18514v1 Announce Type: cross Abstract: Active perception is essential for robotic manipulation when fixed viewpoints leave task-relevant information occluded or unobserved. However, enablin

Anomaly Detection in General Ledger Data: Results from a Hybrid Approach

arXiv:2609.18228v1 Announce Type: new Abstract: Journal Entry Tests (JETs) are a mandatory part of annual audits to evaluate and assess both highrisk audit areas and potential material misstatements.

Come hang out with AI engineers, tech leads, and the Fireworks team during AI Engineer 2026. Want to leave with hands-on experience fine-tun…

Come hang out with AI engineers, tech leads, and the Fireworks team during AI Engineer 2026. Want to leave with hands-on experience fine-tuning, evaluating, and deploying a model on Fireworks? Bring y

tutorialsfireworks-ai--x

DiT-Garment: Garment Dynamics with Diffusion Transformers

arXiv:2609.18510v1 Announce Type: new Abstract: We present DiT-Garment to model dynamic 3D clothing over human body models in arbitrary motion. Unlike existing methods, DiT-Garment can animate garment

Dose-Aware Cold Diffusion with Physics Consistency for Generalizable Low-Dose CT Reconstruction

arXiv:2609.18943v1 Announce Type: cross Abstract: Reducing radiation dose in computed tomography significantly degrades image quality and poses challenges for accurate and clinically reliable reconstr

Dreaming the Sound of Contact: Leveraging Video and Audio Generation for Zero-Shot Force-Aware Manipulation and Data Generation

arXiv:2609.19137v1 Announce Type: cross Abstract: Recent advances in video generation allow robots to learn manipulation trajectories from generated videos. However, these approaches produce purely ki

DR.WILSS: Diffusion-Based Replay for Weakly Supervised Continual Semantic Segmentation

arXiv:2609.18444v1 Announce Type: new Abstract: Weakly supervised class-incremental semantic segmentation (WILSS) aims to train a segmentation model over multiple steps, each introducing new concepts

Fallacy Benchmarks Measure Scheme Recognition, Not Fallacy Detection

arXiv:2609.18644v1 Announce Type: new Abstract: Fallacy-detection benchmarks pair fallacy classes with a single 'valid' or 'none' class that takes everything data collection did not label as a fallacy

tutorialsarxiv-cs-cl