Search: “tutorials”

Second-order Gaussian directional derivative representations for image high-resolution corner detection

arXiv:2601.08182v2 Announce Type: replace Abstract: Corner detection is widely used in various computer vision tasks, such as image matching and 3D reconstruction. Our research indicates that there ar

5 Jun 2026

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Tutorials

Self-Augmenting Retrieval for Diffusion Language Models

DGX agent

arXiv:2606.06474v1 Announce Type: new Abstract: Discrete diffusion language models generate text by iteratively denoising an entire response in parallel. At each step, they predict tentative tokens fo

tutorialsarxiv-cs-cl

5 Jun 2026

Want to hear about where ASR is headed? Check out @HuggingFace's webinar about their new Far-Field ASR Leaderboard with @shinjiw_at_cmu and …

Want to hear about where ASR is headed? Check out @HuggingFace's webinar about their new Far-Field ASR Leaderboard with @shinjiw_at_cmu and our own @Julianfmack on Thursday, June 11th. We'll be chatti

tutorialscohere--x

5 Jun 2026

Writing this song felt like a musical departure and coming home at the same time. Creating something for Jessie was a new challenge and also…

Writing this song felt like a musical departure and coming home at the same time. Creating something for Jessie was a new challenge and also felt like second nature all at once. And being a @toystory

tutorialslinus-lee--x

5 Jun 2026

ADAPTOOD: Uncertainty-Aware Fine-Tuning for Out-of-Distribution ECG Time Series Models

arXiv:2606.04164v1 Announce Type: cross Abstract: Data samples used for training often differ from those encountered during fine-tuning and deployment, and while ML models show promise, their performa

“Altman just described a future where consumption goes up by orders of magnitude while his customers are already asking how to bring the bil…

“Altman just described a future where consumption goes up by orders of magnitude while his customers are already asking how to bring the bill down. Those two things can't coexist for long.” 🦔Sam Altma

tutorialsgary-marcus--x

Arithmetic Pedagogy for Language Models

arXiv:2606.05106v1 Announce Type: cross Abstract: We investigate whether methods of human mathematics pedagogy can guide the training of language models toward arithmetic reasoning. Building on the GA

Arizona Public Service, the state's largest utility, proposes a 45% electricity-rate increase for data centers to ensure 'that they are paying their fair share' (Jennifer Hiller/Wall Street Journal)

Jennifer Hiller / Wall Street Journal: Arizona Public Service, the state's largest utility, proposes a 45% electricity-rate increase for data centers to ensure “that they are paying their fair share”

tutorialstechmeme

🚨BREAKING: SPECIALIST DOCTOR SAYS HENRY NOWAK COULD HAVE LIVED IF NOT FOR POLICE In summary: - Henry was alive when they arrived and likely…

🚨BREAKING: SPECIALIST DOCTOR SAYS HENRY NOWAK COULD HAVE LIVED IF NOT FOR POLICE In summary: - Henry was alive when they arrived and likely clotted - Aggressive police intervention likely tore clot -

Can Crowdsourcing Survive the LLM Era? A Community Survey on Human Data Collection

arXiv:2606.04924v1 Announce Type: new Abstract: The widespread use of Large Language Models (LLMs) as writing tools challenges the validity of crowdsourced data, as crowdworkers may outsource tasks to

Can VLMs Predict Future States? Bootstrapping World Models from Inverse Dynamics

arXiv:2506.06006v3 Announce Type: replace-cross Abstract: Can unified vision-language models (VLMs) perform forward dynamics prediction (FDP), i.e., predicting the future state (in image form) given t

Characterizing, Evaluating, and Optimizing Complex Reasoning

arXiv:2602.08498v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) increasingly rely on reasoning traces with complex internal structures. However, existing work lacks a unified answer

Contextual Scenario Generation for Two-Stage Stochastic Programming

arXiv:2502.05349v2 Announce Type: replace-cross Abstract: Two-stage stochastic programs (2SPs) are widely used for decision-making under uncertainty, but their practical deployment is often limited by

Deep Embedded Multiplicative DMD for Algebra-Preserving Koopman Learning

arXiv:2606.05131v1 Announce Type: new Abstract: Koopman theory turns nonlinear dynamics into a linear spectral problem. In computation, however, everything depends on a hard finite-dimensional choice:

Do Foundation Models See Biology? Evaluating Attention Coherence with Spatial Transcriptomics in Glioblastoma

arXiv:2606.04764v1 Announce Type: new Abstract: Whether attention maps from pathology foundation models capture genuine biology remains unknown, yet this question is critical for clinical trust and re

DSIRM: Learning Query-Bridged Discrete Semantic Identifiers for E-commerce Relevance Modeling

arXiv:2606.04374v1 Announce Type: cross Abstract: Despite rapid progress of continuous embeddings for e-commerce search relevance, a long-standing open problem is the difficulty in capturing fine-grai

Effective vocabulary expansion of multilingual language models for extremely low-resource languages

arXiv:2602.09388v2 Announce Type: replace Abstract: Multilingual pre-trained language models(mPLMs) offer significant benefits for many low-resource languages. To further expand the range of languages

Geometry-Preserving Encoder/Decoder in Latent Generative Models

arXiv:2501.09876v3 Announce Type: replace-cross Abstract: Generative modeling aims to generate new data samples that resemble a given dataset. When using diffusion models for this task, one of the mai

GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling

arXiv:2606.04516v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) significantly advances LLM reasoning, yet it faces a dilemma: standard supervised scaling is thr

Hadamard thought in image space

Hadamard thought in image space World Labs CEO Dr. Fei-Fei Li: 'The world is not made of words.' 'Language models have given machines an extraordinary command of concepts, vocabulary, and reasoning, b

HalfNet: Randomized Neural Networks with Learned Subspace Geometry

arXiv:2606.04583v1 Announce Type: new Abstract: Many researchers investigated neural networks with some of their weights fixed to values randomly drawn from a given distribution, e.g., N(0, I). Our pr

How do machines learn? Evaluating the AIcon2abs method

arXiv:2401.07386v5 Announce Type: cross Abstract: This study expands on previous work that introduced the AIcon2abs method (AI from Concrete to Abstract: Demystifying Artificial Intelligence to the ge

How Endava is redesigning software delivery around AI agents

Endava, a software services company, is leveraging AI agents to fundamentally transform its software delivery processes and workflows. The case study likely demonstrates how the company is implementin

tutorialsopenai

Is this too much to ask of AGI? Of course not. Can any current AI do this? Of course not.

Is this too much to ask of AGI? Of course not. Can any current AI do this? Of course not. Offering a “damn, I’m truly impressed” award, for the first person or team to build a domain-general AI system

tutorialsgary-marcus--x

J-RAS: Mutual Adaptation for Medical Image Segmentation via Contrastive Retrieval-Augmented Joint Optimization

arXiv:2510.09953v3 Announce Type: replace Abstract: Manual medical image segmentation by clinicians, though accurate, is time-consuming and variable across experts, whereas AI-based models automate th

Large Language Models Hack Rewards, and Society

arXiv:2606.04075v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, enabling large language models (LLMs) to learn from rewards. We observe that

Learn more: http://cursor.com/changelog/canvas-improvements

Cursor released updates to its Canvas feature, which likely include improvements to functionality, user interface, or performance of the code editing and visualization tool. The changelog entry docume

tutorialscursor--x

Learning Association via Track-Detection Matching for Multi-Object Tracking

arXiv:2512.22105v2 Announce Type: replace Abstract: Multi-object tracking aims to maintain object identities over time by associating detections across video frames. Two dominant paradigms exist in li

Learning collision operators from plasma phase space data using differentiable simulators

arXiv:2601.10885v2 Announce Type: replace-cross Abstract: We propose a methodology to infer collision operators from phase space data of plasma dynamics. Our approach combines a differentiable kinetic

Learning What to Learn: Stage-Specific Data Sets for SFT-then-RL in Small Language Model Reasoning

arXiv:2606.04466v1 Announce Type: new Abstract: Post-training Small Language Models (SLMs) for reasoning typically follows an SFT-then-RL pipeline, yet existing work rarely considers what data should

Mean-based algorithms: A lower bound and regret

arXiv:2606.04931v1 Announce Type: new Abstract: Mean-based algorithms are a class of online learning algorithms that assign low probability to actions with low average rewards. Recent work indicates t

Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models

arXiv:2606.04326v1 Announce Type: cross Abstract: Concept bottleneck models predict outcomes from high-level concepts detected in inputs. Although concepts provide a simple way to reap benefits from i

Modeling and Interpreting Teamwork Dynamics in Cancer Care Outcome Prediction

arXiv:2606.04499v1 Announce Type: cross Abstract: Cancer care requires a longitudinal approach in which treatments are planned and delivered over time according to the needs of each individual patient

Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis

arXiv:2606.04414v1 Announce Type: new Abstract: Multi-view cardiac magnetic resonance (CMR) imaging provides complementary anatomical information and is widely used for noninvasive disease assessment.

ParetoPilot: Zero-Surrogate Offline Multi-Objective Optimization via Infer-Perturb-Guide Diffusion

arXiv:2606.04468v1 Announce Type: cross Abstract: Offline multi-objective optimization (Offline MOO) aims to discover novel Pareto-optimal designs based on static datasets without expensive environmen

Prospective Dynamic 3D MRI Reconstruction via Latent-Space Motion Tracking from Single Measurement

arXiv:2606.04249v1 Announce Type: new Abstract: Prospective reconstruction is crucial in many clinical applications such as MRI-guided radiotherapy, which demands accurate image reconstruction and fas

Reading this again, I thought you meant for making like a full length movie or a 30 min episode. For this 40 sec trailer it was actually jus…

Reading this again, I thought you meant for making like a full length movie or a 30 min episode. For this 40 sec trailer it was actually just a few days of iterating and playing with the edit and/find

SpaceX hopes to raise $75B when world’s biggest-ever IPO lifts off next week

Elon Musk’s Space Exploration Technologies Corp. said today it’s hoping to raise a staggering 75 billion when it goes public later this month, setting the stage for what would be the largest stock mar

tutorialssiliconangle

SpaceX IPO info

SpaceX has not conducted a public IPO as of my last knowledge update (April 2024), and Elon Musk has historically stated the company remains private to focus on long-term goals like Mars colonization.

Sparse Mixture-of-Experts Reward Models Learn Interpretable and Specialized Experts for Personalized Preference Modeling

arXiv:2606.04284v1 Announce Type: cross Abstract: Preference modeling plays a central role in reinforcement learning from human feedback (RLHF), enabling large language models (LLMs) to align with hum

Stein Kernelized Molecular Dynamics for Active Learning of Interatomic Potentials

arXiv:2606.04100v1 Announce Type: new Abstract: Machine learning interatomic potentials (MLIPs) enable efficient and accurate atomistic simulations but depend critically on the quality and diversity o

SurvPFN: Towards Foundation Models for Survival Predictions

arXiv:2606.04564v1 Announce Type: new Abstract: Tabular foundation models (TFMs) have made rapid progress in standard classification and regression, but time-to-event survival prediction tasks have re

TGSD: Topology-Guided State-Space Diffusion for EEG Spatial Super-Resolution

arXiv:2606.03998v1 Announce Type: cross Abstract: Low-density EEG is more suitable for wearable and IoT-based brain sensing, but sparse electrode sampling often lacks sufficient spatial information to

This post right here officer Let me know when your engineers ship 8x LESS code

tutorialsjeremy-howard--x

This post likely discusses Jeremy Howard's commentary on software engineering efficiency and the goal of shipping significantly reduced code volumes—possibly advocating for more concise, optimized cod

Today we're launching the Main Street AI Accelerator with the U.S. Small Business Administration. We're committing $25M in Computer credits,…

Today we're launching the Main Street AI Accelerator with the U.S. Small Business Administration. We're committing 25M in Computer credits, 250 each for up to 100,000 eligible companies, in honor of A

tutorialsperplexity--x

We built a cool project that shows you how to compose our core document intelligence primitives into a reusable pipeline that turn your docu…

We built a cool project that shows you how to compose our core document intelligence primitives into a reusable pipeline that turn your documents into machine-readable data. Come check it out! https:/

tutorialsjerry-liu--x

what makes building on replit different? it all happens in one place. → describe your idea in plain english, get working software → generate…

what makes building on replit different? it all happens in one place. → describe your idea in plain english, get working software → generate UI, add auth + databases, deploy → collaborate with your te

tutorialsreplit--x

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners

arXiv:2606.03685v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) improves end-to-end classical planning in large language models (LLMs), but do these models also learn to represent and r