Search: “tutorials”

La representacion de la variacion contextual mediante definiciones terminologicas flexibles

arXiv:1607.06330v2 Announce Type: replace Abstract: In this doctoral thesis, we apply premises of cognitive linguistics to terminological definitions and present a proposal called the flexible termino

Tutorials

MagicFuse: Single Image Fusion for Visual and Semantic Reinforcement

DGX agent

arXiv:2602.01760v2 Announce Type: replace Abstract: This paper focuses on a highly practical scenario: how to continue benefiting from the advantages of multi-modal image fusion under harsh conditions

tutorialsarxiv-cs-cv

22 May 2026

Personality Engineering with AI Agents: A New Methodology for Negotiation Research

arXiv:2605.20554v1 Announce Type: new Abstract: According to canonical negotiation theory, people's success in a negotiation depends on how well they balance competing demands--empathizing and asserti

tutorialsarxiv-cs-ai

Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking

arXiv:2605.22538v1 Announce Type: new Abstract: Traditional visual object tracking (VOT) methods typically rely on task-specific supervised training, limiting their generalization to unseen objects an

TextTeacher: What Can Language Teach About Images?

arXiv:2605.22098v1 Announce Type: new Abstract: The platonic representation hypothesis suggests that sufficiently large models converge to a shared representation geometry, even across modalities. Mot

Unified Data Selection for LLM Reasoning

arXiv:2605.22389v1 Announce Type: new Abstract: Effectively training Large Language Models (LLMs) for complex, long-CoT reasoning is often bottlenecked by the need for massive high-quality reasoning d

VChain: Chain-of-Visual-Thought for Reasoning in Video Generation

arXiv:2510.05094v2 Announce Type: replace Abstract: Recent video generation models can produce smooth and visually appealing clips, but they often struggle to synthesize complex dynamics with a cohere

Access to Windows VMs rolling out to customers over the next 24 hours. Learn more and try it here: http://devin.ai/windows

Cognition AI announced the rollout of access to Windows virtual machines (VMs) for customers, with availability expanding over a 24-hour period. This feature likely enables users of Cognition's AI dev

tutorialscognition-ai--x

Adaptive Probe-based Steering for Robust LLM Jailbreaking

arXiv:2605.20286v1 Announce Type: cross Abstract: Recent work has demonstrated the potential of contrastive steering for jailbreaking Large Language Models (LLMs). However, existing methods rely on li

Automatic Discovery of Disease Subgroups by Contrasting with Healthy Controls

arXiv:2605.21301v1 Announce Type: cross Abstract: In biomedical Subgroup Discovery, practitioners are interested in discovering interpretable and homogeneous subgroups within a group of patients. In t

Bayesian Optimization by Kernel Regression and Density-based Exploration

arXiv:2502.06178v5 Announce Type: replace-cross Abstract: Bayesian optimization is highly effective for optimizing expensive-to-evaluate black-box functions, but it faces significant computational cha

Build an AI-powered recruitment assistant using Amazon Bedrock

In this post, we demonstrate how to build an AI-powered recruitment assistant using Amazon Bedrock that brings efficiencies to candidate evaluation, generates personalized interview questions, and pro

tutorialsaws-ml-blog

Building a Custom Taxonomy of AI Skills and Tasks from the Ground Up with Job Postings

arXiv:2605.21029v1 Announce Type: new Abstract: Utilizing LLMs for automated taxonomy construction presents a clear opportunity for the comprehensive, yet efficient mapping of potentially complex doma

Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networks

arXiv:2605.20529v1 Announce Type: new Abstract: In what ways might statistical signals in linguistic input assist with the acquisition of syntax? Here we hypothesize a mechanism called collocational b

Efficient numeracy in language models through single-token number embeddings

arXiv:2510.06824v2 Announce Type: replace Abstract: To drive progress in science and engineering, large language models (LLMs) must be able to process large amounts of numerical data and solve long ca

Elon Musk just measured your existence by how many times your atoms have been inside a dying star. Musk: “How many times have your atoms bee…

Elon Musk just measured your existence by how many times your atoms have been inside a dying star. Musk: “How many times have your atoms been at the center of a star? I think it’s like on average thre

tutorialselon-musk--x

FlowLM: Few-Step Language Modeling via Diffusion-to-Flow Adaptation

arXiv:2605.20199v1 Announce Type: new Abstract: We present FlowLM, a flow matching language model transformed from pre-trained diffusion language models via efficient fine-tuning. By re-aligning the c

For anyone who isn't sure, this is how you release a model and talk about the performance. Not 3-5 cherry-picked benchmarks.

tutorialsjeremy-howard--x

For anyone who isn't sure, this is how you release a model and talk about the performance. Not 3-5 cherry-picked benchmarks. Performance：Qwen3.7-Max performs strongly across benchmarks in coding agent

Freshworks CEO: Mid-size enterprises can’t compete with giants until they fix their fragmented data

AI service management has arrived, and the enterprises keeping pace didn’t wait for perfect conditions — they consolidated their data first. Of course, that urgency is creating an opening for companie

tutorialssiliconangle

Gated DeltaNet-2 is here. 🚀 🔥 New paper: Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention Gated DeltaNet-2 outperforms KDA…

tutorialsjeremy-howard--x

Gated DeltaNet-2 is here. 🚀 🔥 New paper: Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention Gated DeltaNet-2 outperforms KDA and Mamba-3, the latest and best recurrent architectures, hea

Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation

arXiv:2605.20600v1 Announce Type: new Abstract: Autoregressive (AR) visual generation has achieved remarkable performance but suffers from high memory usage and low throughput, as it requires caching

How to build LLM-as-a-Judge evaluators that hold up in production

Learn how to design, calibrate, and run LLM-as-a-judge evaluators with fixed labels, human agreement checks, trace context, and Phoenix Evals. The post How to build LLM-as-a-Judge evaluators that hold

tutorialsarize-ai

HyDAR-Pano3D: A Hybrid Disentangled Anatomical Recovery Framework for Panoramic-to-3D Reconstruction

arXiv:2605.20827v1 Announce Type: new Abstract: Panoramic radiograph (PR) is fundamentally used in routine dental care, but it inherently provides only a two-dimensional (2D) projection of complex thr

I called my engineer friend at SpaceX the other day. 1am Pacific. 3am in Starbase. He was still in the office and not going home any time so…

I called my engineer friend at SpaceX the other day. 1am Pacific. 3am in Starbase. He was still in the office and not going home any time soon. And he was happy. Energized. Because he's directly influ

tutorialselon-musk--x

Introspective X Training: Feedback Conditioning Improves Scaling Across all LLM Training Stages

arXiv:2605.20285v1 Announce Type: new Abstract: We tackle the question of how to scale more efficiently across the many, ever-growing stages of current LLM training pipelines. Our guiding intuition st

iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance

arXiv:2605.21431v1 Announce Type: new Abstract: Video Virtual Try-On (VVT) aims to seamlessly replace a garment on a person in a video with a new one. While existing methods have made significant stri

Jointly Learning Predicates and Actions Enables Zero-Shot Skill Composition

arXiv:2605.20648v1 Announce Type: new Abstract: Learning from Demonstration (LfD) enables robots to learn complex behaviors from expert examples, yet existing approaches often fail to generalize to ne

tutorialsarxiv-cs-ro

Latent Process Generator Matching

arXiv:2605.20547v1 Announce Type: new Abstract: Many recent flow-matching and diffusion-style generative models rely on auxiliary stochastic dynamics during training: a richer process is simulated to

Learn how to build LLM Wikis and LLM Artifacts.

Learn how to build LLM Wikis and LLM Artifacts. New VIDEO: From LLM Wikis to LLM Artifacts Shared all my thoughts on why LLM wikis and HTML artifacts are a big deal. Plus, new tools to help you build

tutorialsdair-ai--x

Learn more about Replit Enterprise here: https://replit.com/enterprise

Replit Enterprise is a commercial offering from Replit designed for organizations and businesses seeking advanced collaborative coding and development capabilities on the Replit platform. This likely

tutorialsreplit--x

Learning to Defer in Non-Stationary Time Series via Switching State-Space Models

arXiv:2601.22538v2 Announce Type: replace Abstract: Learning-to-defer (L2D) routes each decision to a system's own predictor or to an external expert. Streaming time-series settings break the offline-

Let EEG Models Learn EEG

arXiv:2605.21280v1 Announce Type: new Abstract: High-fidelity EEG generation is critical for alleviating data scarcity and addressing privacy constraints in large-scale neural modeling. Despite recent

LLM training is built on fast MatMuls. But many surrounding ops still run as memory-bound kernels. CODA reparameterizes them to hide in the …

tutorialsjeremy-howard--x

LLM training is built on fast MatMuls. But many surrounding ops still run as memory-bound kernels. CODA reparameterizes them to hide in the matmul’s shadow, fused into its epilogue before results leav

LT2: Linear-Time Looped Transformers

arXiv:2605.20670v1 Announce Type: new Abstract: Looped Transformers (LT) have emerged as a powerful architecture by iterating their layers multiple times before decoding the final token. However, pair

Memorisation, convergence and generalisation in generative models

arXiv:2605.21402v1 Announce Type: cross Abstract: Generative neural networks learn how to produce highly realistic images from a large, but finite number of examples - or do they simply memorise their

Nathan's @cursor_ai team didn't prompt-engineer their way to Composer 2.5. They trained it. The massive RL program runs RL rollouts on Firew…

Nathan's @cursor_ai team didn't prompt-engineer their way to Composer 2.5. They trained it. The massive RL program runs RL rollouts on Fireworks, alongside production inference. 'Comment 🔥 to see my p

tutorialsfireworks-ai--x

On the Regularity and Generalization of One-Step Wasserstein-guided Generative Models for PDE-Induced Measures

arXiv:2605.21388v1 Announce Type: new Abstract: Despite the remarkable empirical success of generative models, the available theory on their statistical accuracy in scientific computing remains largel

PACD-Net: Pseudo-Augmented Contrastive Distillation for Glycemic Control Estimation from SMBG

arXiv:2605.20751v1 Announce Type: new Abstract: Effective diabetes management requires continuous monitoring of glycemic levels. Clinically, glycemic control is assessed using metrics such as Time in

Pseudo-Siamese Network for Planning in Target-Oriented Proactive Dialogues

arXiv:2605.20195v1 Announce Type: new Abstract: A target-oriented proactive dialogue system is designed to steer conversations toward predefined targets while actively providing suggestions. The core

Puzzled By ChatGPT? No more! A Jigsaw Puzzle to Promote AI Literacy and Awareness

arXiv:2605.20404v1 Announce Type: new Abstract: The rapid adoption of Generative AI, including LLM-based chatbots like ChatGPT, has highlighted the need for accessible ways to support public understan

Q-Net: Queue Length Estimation via Kalman-based Neural Networks

arXiv:2509.24725v3 Announce Type: replace Abstract: Estimating queue lengths at signalized intersections is a long-standing challenge in traffic management. Partial observability of vehicle flows comp

Reducing Object Hallucination in LVLMs via Emphasizing Image-negative Tokens

arXiv:2605.21300v1 Announce Type: new Abstract: Object hallucination is a significant challenge that hinders the application of large vision-language models (LVLMs) in practice. We hypothesize that on

Roundtables: Can AI Learn to Understand the World?

Listen to the session or watch below AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the fo

tutorialsmit-tech-review

Task-Routed Mixture-of-Experts with Cognitive Appraisal for Implicit Sentiment Analysis

arXiv:2605.20916v1 Announce Type: new Abstract: Implicit sentiment analysis is challenging because sentiment toward an aspect is often inferred from events rather than expressed through explicit opini

This isn't just corruption or grift, it's a full-on criminal enterprise. If Republicans in Congress hadn't sold themselves out completely, t…

This isn't just corruption or grift, it's a full-on criminal enterprise. If Republicans in Congress hadn't sold themselves out completely, they'd shut this down immediately. Since the Trump administra

tutorialsyann-lecun--x

This offering is best suited for: - Growing teams that have outgrown Replit Pro - Any org that needs Enterprise controls and wants to get st…

This offering is best suited for: - Growing teams that have outgrown Replit Pro - Any org that needs Enterprise controls and wants to get started quickly Learn more here: https://replit.com/blog/enter

tutorialsreplit--x

Towards Understanding Self-Pretraining for Sequence Classification

arXiv:2605.21070v1 Announce Type: new Abstract: Amos et al. (2024) showed that the accuracy of Transformer models in sequence classification can be significantly improved by first pretraining with a m

Verification of Unknown Dynamical Systems via Autoencoder Latent Space

arXiv:2512.13593v4 Announce Type: replace Abstract: Formal verification provides a powerful framework for proving that dynamical systems satisfy their specifications. However, these techniques face sc