tutorials

Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video

arXiv:2604.07786v1 Announce Type: new Abstract: Talking face generation has gained significant attention as a core application of generative models. To enhance the expressiveness and realism of synthe

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DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models

DGX agent

arXiv:2306.14685v5 Announce Type: replace-cross Abstract: We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide

tutorialsarxiv-cs-ai

10 Apr 2026

Diffusion Processes on Implicit Manifolds

arXiv:2604.07213v1 Announce Type: new Abstract: High-dimensional data are often modeled as lying near a low-dimensional manifold. We study how to construct diffusion processes on this data manifold in

'Don't Be Afraid, Just Learn': Insights from Industry Practitioners to Prepare Software Engineers in the Age of Generative AI

arXiv:2604.06342v1 Announce Type: cross Abstract: Although tension between university curricula and industry expectations has existed in some form for decades, the rapid integration of generative AI (

Don't Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget

arXiv:2402.02249v3 Announce Type: replace Abstract: We study how to best spend a budget of noisy labels to compare the accuracy of two binary classifiers. It's common practice to collect and aggregate

ELC: Evidential Lifelong Classifier for Uncertainty Aware Radar Pulse Classification

arXiv:2604.06958v1 Announce Type: cross Abstract: Reliable radar pulse classification is essential in Electromagnetic Warfare for situational awareness and decision support. Deep Neural Networks have

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis

arXiv:2604.07180v1 Announce Type: cross Abstract: We propose a geometric framework for longitudinal multi-parametric MRI analysis based on patient-specific energy modelling in sequence space. Rather t

EPIR: An Efficient Patch Tokenization, Integration and Representation Framework for Micro-expression Recognition

arXiv:2604.08106v1 Announce Type: new Abstract: Micro-expression recognition can obtain the real emotion of the individual at the current moment. Although deep learning-based methods, especially Trans

EventWeave: A Dynamic Framework for Capturing Core and Supporting Events in Dialogue Systems

arXiv:2503.23078v3 Announce Type: replace Abstract: Large language models have improved dialogue systems, but often process conversational turns in isolation, overlooking the event structures that gui

ExplainFuzz: Explainable and Constraint-Conditioned Test Generation with Probabilistic Circuits

arXiv:2604.06559v1 Announce Type: cross Abstract: Understanding and explaining the structure of generated test inputs is essential for effective software testing and debugging. Existing approaches--in

Exploring Temporal Representation in Neural Processes for Multimodal Action Prediction

arXiv:2604.08418v1 Announce Type: new Abstract: Inspired by the human ability to understand and predict others, we study the applicability of Conditional Neural Processes (CNP) to the task of self-sup

tutorialsarxiv-cs-ro

Face2Scene: Using Facial Degradation as an Oracle for Diffusion-Based Scene Restoration

arXiv:2603.16570v2 Announce Type: replace Abstract: Recent advances in image restoration have enabled high-fidelity recovery of faces from degraded inputs using reference-based face restoration models

Few-Shot Incremental 3D Object Detection in Dynamic Indoor Environments

arXiv:2604.07997v1 Announce Type: new Abstract: Incremental 3D object perception is a critical step toward embodied intelligence in dynamic indoor environments. However, existing incremental 3D detect

Generalization Under Scrutiny: Cross-Domain Detection Progresses, Pitfalls, and Persistent Challenges

arXiv:2604.08230v1 Announce Type: new Abstract: Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to vari

Getting started with ChatGPT

OpenAI Academy's 'Getting Started with ChatGPT' tutorial introduces users to ChatGPT as a conversational AI application built on large language models, teaching core concepts such as how to write e...

GitHub Copilot CLI for Beginners: Getting started with GitHub Copilot CLI

GitHub for Beginners: Getting started with the GitHub Copilot CLI, a step-by-step tutorial. The post GitHub Copilot CLI for Beginners: Getting started with GitHub Copilot CLI appeared first on The Git

tutorialsgithub-ai-blog

How to get ChatGPT to do substantially more work.

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tutorialsr-chatgpt

How to sketch a learning algorithm

arXiv:2604.07328v1 Announce Type: new Abstract: How does the choice of training data influence an AI model? This question is of central importance to interpretability, privacy, and basic science. At i

Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement

arXiv:2507.08390v4 Announce Type: replace Abstract: Discrete diffusion models have recently emerged as strong alternatives to autoregressive language models, matching their performance through large-s

is this still hot?

is this still hot? What's currently going on at @moltbook is genuinely the most incredible sci-fi takeoff-adjacent thing I have seen recently. People's Clawdbots (moltbots, now @openclaw) are self-org

tutorialsgary-marcus--x

Learning is Forgetting: LLM Training As Lossy Compression

arXiv:2604.07569v1 Announce Type: cross Abstract: Despite the increasing prevalence of large language models (LLMs), we still have a limited understanding of how their representational spaces are stru

Linear Representations of Hierarchical Concepts in Language Models

arXiv:2604.07886v1 Announce Type: new Abstract: We investigate how and to what extent hierarchical relations (e.g., Japan subset Eastern Asia subset Asia) are encoded in the internal representat

Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effects

arXiv:2505.02781v4 Announce Type: replace Abstract: Identifying controlled direct effects (CDEs) is crucial across numerous scientific domains. While existing methods can identify these effects from c

Migrating to Google Cloud’s Application Load Balancer: A practical guide

Migrating your existing application load balancer infrastructure from an on-premises hardware solution to Cloud Load Balancing offers substantial advantages in scalability, cost-efficiency, and tight

tutorialsgoogle-cloud-ai

MoRight: Motion Control Done Right

arXiv:2604.07348v1 Announce Type: cross Abstract: Generating motion-controlled videos--where user-specified actions drive physically plausible scene dynamics under freely chosen viewpoints--demands tw

Needle in a Haystack -- One-Class Representation Learning for Detecting Rare Malignant Cells in Computational Cytology

arXiv:2604.07722v1 Announce Type: new Abstract: In computational cytology, detecting malignancy on whole-slide images is difficult because malignant cells are morphologically diverse yet vanishingly r

OceanMAE: A Foundation Model for Ocean Remote Sensing

arXiv:2604.08171v1 Announce Type: new Abstract: Accurate ocean mapping is essential for applications such as bathymetry estimation, seabed characterization, marine litter detection, and ecosystem moni

ODE-free Neural Flow Matching for One-Step Generative Modeling

arXiv:2604.06413v1 Announce Type: new Abstract: Diffusion and flow matching models generate samples by learning time-dependent vector fields whose integration transports noise to data, requiring tens

Open swe uses deepagents under the hood Deepagents is general purpose, openswe is focused on coding

tutorialsharrison-chase--x

Open swe uses deepagents under the hood Deepagents is general purpose, openswe is focused on coding @hwchase17 @LangChain This is a very interesting comparison. Now my question is: how to compare Deep

Personalizing ChatGPT

The OpenAI Academy 'Personalizing ChatGPT' tutorial covers several methods users can employ to tailor ChatGPT's behavior to their needs, including custom instructions, memory, and prompt engineerin...

Physically Plausible Human-Object Rendering from Sparse Views via 3D Gaussian Splatting

arXiv:2503.09640v2 Announce Type: replace-cross Abstract: Rendering realistic human-object interactions (HOIs) from sparse-view inputs is a challenging yet crucial task for various real-world applicat

Prompting fundamentals

The OpenAI Academy 'Prompting Fundamentals' resource teaches users the basics of prompt engineering, explaining that a prompt is a question or instruction given to ChatGPT in text, image, audio, or...

Reading Recognition in the Wild

arXiv:2505.24848v4 Announce Type: replace Abstract: To enable egocentric contextual AI in always-on smart glasses, it is crucial to be able to keep a record of the user's interactions with the world,

Research with ChatGPT

The OpenAI Academy 'Research with ChatGPT' tutorial covers how to use ChatGPT's two primary research tools: the Search the Web feature for retrieving live data and sources quickly, and Deep Researc...

RPM-Net Reciprocal Point MLP Network for Unknown Network Security Threat Detection

arXiv:2604.06638v1 Announce Type: cross Abstract: Effective detection of unknown network security threats in multi-class imbalanced environments is critical for maintaining cyberspace security. Curren

Search-R3: Unifying Reasoning and Embedding in Large Language Models

arXiv:2510.07048v2 Announce Type: replace Abstract: Despite their remarkable natural language understanding capabilities, Large Language Models (LLMs) have been underutilized for retrieval tasks. We p

So simple yet so powerful. Also, remember to take a walk and sit at the park

tutorialscristobal-valenzuela--x

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Steering the Verifiability of Multimodal AI Hallucinations

arXiv:2604.06714v1 Announce Type: new Abstract: AI applications driven by multimodal large language models (MLLMs) are prone to hallucinations and pose considerable risks to human users. Crucially, su

TEC: A Collection of Human Trial-and-error Trajectories for Problem Solving

arXiv:2604.06734v2 Announce Type: replace Abstract: Trial-and-error is a fundamental strategy for humans to solve complex problems and a necessary capability for Artificial Intelligence (AI) systems o

The leadership lunch session at @aiDotEngineer was great! Loved meeting fellow Tech leaders and learn from each other. Thanks for organizing…

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tutorialsswyx--x

The pace at which useful things are shipping also seems to be accelerating. Model releases are coming faster, of course, but so are signific…

tutorialsethan-mollick--x

The pace at which useful things are shipping also seems to be accelerating. Model releases are coming faster, of course, but so are significant application and enterprise products (especially from Ant

The quality of talks at @aiDotEngineer is insane, being able to learn about diffusion models and flow mapping from @GoogleDeepMind’s @sediel…

The AI Engineer Summit (@aiDotEngineer) is a highly regarded technical conference featuring speakers from leading AI organizations including Google DeepMind, Anthropic, and OpenAI, known for its de...

tutorialsswyx--x

This is a great discussion. We've spent 2 years building a solution that's working well for us -- co-writing software side by side the AI in…

tutorialsjeremy-howard--x

This is a great discussion. We've spent 2 years building a solution that's working well for us -- co-writing software side by side the AI in an notebook-ish environment. We call it the 'solveit method

Tracking Adaptation Time: Metrics for Temporal Distribution Shift

arXiv:2604.07266v1 Announce Type: new Abstract: Evaluating robustness under temporal distribution shift remains an open challenge. Existing metrics quantify the average decline in performance, but fai

Transforming the Voice of the Customer: Large Language Models for Identifying Customer Needs

arXiv:2503.01870v2 Announce Type: replace Abstract: Identifying customer needs (CNs) is fundamental to product innovation and marketing strategy. Yet for over thirty years, Voice-of-the-Customer (VOC)

Understanding Task Transfer in Vision-Language Models

arXiv:2511.18787v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) perform well on multimodal benchmarks but lag behind humans and specialized models on visual perception tasks like dep

Using custom GPTs

Custom GPTs are tailored versions of ChatGPT that users can configure for specific tasks, roles, or workflows by setting instructions, uploading proprietary knowledge files, and enabling capabiliti...

Using projects in ChatGPT

ChatGPT Projects are dedicated workspaces that let users group related chats, upload reference files (such as PDFs, spreadsheets, and images), and set custom instructions so that ChatGPT maintains ...