Search: “tutorials”

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Sapiens2 is the highest quality ViT backbone that now exists in the public domain. It was pretrained on the equivalent of 1/2 of all human images on Flickr. First public release by a large lab that is

arXiv:2604.21931v1 Announce Type: cross Abstract: How can we tell whether a video has been sped up or slowed down? How can we generate videos at different speeds? Although videos have been central to

arXiv:2604.21693v1 Announce Type: new Abstract: Simultaneous localization and mapping (SLAM) is a foundational state estimation problem in robotics in which a robot accurately constructs a map of its

🚀 Sovereign AI for the world. Cohere & Aleph Alpha form transatlantic AI powerhouse anchored in Canada & Germany! Combining our global scale with European R&D excellence to build sovereign, enterprise

arXiv:2506.12721v2 Announce Type: replace Abstract: Scaling test-time compute has emerged as an effective strategy for improving the performance of large language models. However, existing methods typ

arXiv:2604.21764v1 Announce Type: new Abstract: Reasoning LLMs often spend substantial tokens on long intermediate reasoning traces (e.g., chain-of-thought) when solving new problems. We propose to su

Today I re-iterate: I hate MoEs and we are wasting time on them.... Let's unite and call a global ban on MoEs please. Please 1M+ salary researchers: do better... credits to @IlysMoutawwakil for the gr

arXiv:2604.21761v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have garnered significant interest for their potential in solving partial differential equations (PDEs) that go

At #RenderCon2026, @EMostaque makes the case during How to Build the Holodeck that stories still matter, IP still matters, but the barriers to building entirely new experiences are dropping faster tha

OpenAI's Automations documentation covers tools and techniques for automating repetitive tasks using AI models, likely including practical examples of how to use their APIs to create automated workflo

arXiv:2604.19954v1 Announce Type: new Abstract: Current text-to-image models struggle to provide precise camera control using natural language alone. In this work, we present a framework for precise c

Codex settings refers to configuration options and parameters available for OpenAI's Codex model, a machine learning system trained to understand and generate code. This documentation likely covers ho

arXiv:2510.10417v2 Announce Type: replace-cross Abstract: Gait recognition is an important biometric for human identification at a distance, particularly under low-resolution or unconstrained environm

Confidently wrong is worse than just wrong. When an AI searches one giant knowledge base for everything, it finds something—and serves it up like it's the answer. That's not a model problem. That's a

arXiv:2604.20817v1 Announce Type: cross Abstract: Language models trained on natural text learn to represent numbers using periodic features with dominant periods at T=2, 5, 10. In this paper, we iden

arXiv:2604.20516v1 Announce Type: cross Abstract: Determining identifiability of causal effects from observational data under latent confounding is a central challenge in causal inference. For linear

arXiv:2604.19797v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) for low-resource Dravidian languages like Telugu and Kannada faces significant challenges in specialized medical do

arXiv:2604.20760v1 Announce Type: new Abstract: Space-time self-similarity (STSS), which captures visual correspondences across frames, provides an effective way to represent temporal dynamics for vid

arXiv:2508.15411v3 Announce Type: replace-cross Abstract: Generative AI (GenAI) has emerged as a transformative technology, demonstrating remarkable capabilities across diverse application domains. Ho

arXiv:2603.09283v2 Announce Type: replace Abstract: Removing objects from videos remains difficult in the presence of real-world imperfections such as shadows, abrupt motion, and defective masks. Exis

OpenAI's Codex is a code-generating AI model that translates natural language instructions into functional code across multiple programming languages. This guide provides foundational steps for develo

arXiv:2604.01938v3 Announce Type: replace Abstract: The structure of all the permutations of a sequence can be represented as a permutohedron, a graph where vertices are permutations and two vertices

arXiv:2604.20329v1 Announce Type: cross Abstract: Recent works show that image and video generators exhibit zero-shot visual understanding behaviors, in a way reminiscent of how LLMs develop emergent

arXiv:2604.20078v1 Announce Type: new Abstract: Graph-based techniques and spectral graph theory have enriched the field of machine learning with a variety of critical advances. A central object in th

arXiv:2510.26285v2 Announce Type: replace-cross Abstract: Prior work has shown that large language models (LLMs) often converge to accurate input embedding for numbers, based on sinusoidal representat

arXiv:2508.06614v2 Announce Type: replace Abstract: As a class of generative artificial intelligence frameworks inspired by statistical physics, diffusion models have shown extraordinary performance i

arXiv:2604.20236v1 Announce Type: new Abstract: High-performance TSP solvers like LKH search within a sparsified candidate graph rather than over all possible edges. Graph sparsification is non-trivia

arXiv:2604.20317v1 Announce Type: new Abstract: GAN-based facial attribute editing is widely used in virtual avatars and social media but often suffers from attribute entanglement, where modifying one