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  • All entries127,575
  • Agents10,689
  • Applications7,180
  • Companies3
  • Concepts7
  • Hardware2,792
  • Industry6,818
  • Local Ai7,045
  • Model Releases36,845
  • Research29,819
  • Safety19,750
  • Syntheses31
  • Tools1,780
  • Tutorials4,816

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10 Jul 2026

Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions

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arXiv:2603.02204v2 Announce Type: replace Abstract: Selective conformal prediction can yield substantially tighter uncertainty sets when we can identify calibration examples that are exchangeable with

Sam Altman should be in prison. But if we can’t have that, I’ll settle for him being a broke pariah.

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Sam Altman should be in prison. But if we can’t have that, I’ll settle for him being a broke pariah. OpenAI hardware chief Tang Tan allegedly helped coach recruits on how to evade Apple’s data securit

Steering Neural Network Training through Interpretable Constraints Based on Partial Dependence

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arXiv:2607.08641v1 Announce Type: new Abstract: Over the last few years, there has been an increased interest in making machine learning models more interpretable. Although a great deal of effort goes

Switch-Reasoner: Learn When to Think in Multitask Mixtures via Reinforcement Learning

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arXiv:2607.08572v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) often follow a fixed Think-then-Answer paradigm, which is inefficient in heterogeneous multitask settings becau

TrackStudio: An Integrated Toolkit for Markerless Tracking

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arXiv:2511.07624v3 Announce Type: replace Abstract: Markerless motion tracking has advanced rapidly in the past 10 years and currently offers powerful opportunities for behavioural, clinical, and biom

VectorizationLLM: Smart Vectorization Based AI Assistant

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arXiv:2607.07846v1 Announce Type: new Abstract: VectorizationLLM is a specialized Large Language Model based on Google open-weight LLMs. The model is designed to assist students to learn smart vectori

Volkswagen Group tells its board how to fix it, unions disagree

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Volkswagen CEO Oliver Blume presented a comprehensive restructuring plan to the supervisory board aimed at making the group more robust and competitive in a challenging environment. The plan reportedl

Write-Protected Discrete Bottlenecks for Language-Grounded World Models: A Structural Limitation and Sufficient Fix

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arXiv:2607.08312v1 Announce Type: new Abstract: How should language interface with a world model's discrete symbol system? The dominant paradigm -- end-to-end injection of LLM/VLM features into robot

9 Jul 2026

A Continual Learning Framework for Adaptive Control of Modular Soft Robots

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arXiv:2607.06740v1 Announce Type: cross Abstract: Soft robots have attracted significant attention in applications such as medical intervention, rehabilitation, and robotic manipulation due to their i

A Theory of Contrastive Learning with Natural Images

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arXiv:2607.07470v1 Announce Type: new Abstract: Why does contrastive learning with simple images and augmentations yield useful representations for downstream tasks? We address this question by analyt

A Visual Introduction to Information Theory (bookmark it) Information Theory is such an beautiful and powerful subject. In the era of AI, it…

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A Visual Introduction to Information Theory (bookmark it) Information Theory is such an beautiful and powerful subject. In the era of AI, it's worth spending time learning about it. Here is a highly-r

Adam Thierer had written the landmark book on 'Permissionless Innovation.' We get the best ideas when we don't have to ask the government in…

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Adam Thierer had written the landmark book on 'Permissionless Innovation.' We get the best ideas when we don't have to ask the government in advance for permission to invent. Protecting open source AI

Adversarial Rademacher Complexity of Deep Neural Networks

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arXiv:2211.14966v2 Announce Type: replace Abstract: Deep neural networks (DNNs) are highly vulnerable to adversarial attacks. Ideally, a robust model should perform well on both perturbed training dat

Also this graph that shows what an 'AI-pilled' startup looks like, and how uncommon it is even among startups: the answer when founders are …

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Also this graph that shows what an 'AI-pilled' startup looks like, and how uncommon it is even among startups: the answer when founders are asked 'Without GenAI, how many additional employees would yo

An Adaptive Differentially Private Federated Learning Framework

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arXiv:2602.06838v3 Announce Type: replace Abstract: Federated learning enables collaborative model training across distributed clients while preserving data privacy. However, in practical deployments,

An Edge-aware Prompt-enhanced SAM for Ultrasound Image Segmentation

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arXiv:2607.07240v1 Announce Type: new Abstract: Ultrasound image segmentation is essential for delineating anatomical structures and lesions, providing the foundation for accurate diagnosis. While the

Bayesian Optimization of Genetic Algorithm Hyperparameters in a Multi-Fidelity Framework for Efficient Lattice Material Design

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arXiv:2607.07289v1 Announce Type: cross Abstract: This study presents a multi-fidelity framework for the systematic optimization of genetic algorithm (GA) hyperparameters. The framework integrates thr

>be stardust >float around the universe for billions of years >somehow become human >gain consciousness >immediately start asking 'WHY?' >ne…

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>be stardust >float around the universe for billions of years >somehow become human >gain consciousness >immediately start asking 'WHY?' >never stop >discover fire >discover math >discover atoms >disc

Can We Really Learn One Representation to Optimize All Rewards?

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arXiv:2602.11399v2 Announce Type: replace-cross Abstract: As unsupervised pretraining becomes increasingly ubiquitous in reinforcement learning, a more thorough theoretical understanding of these meth

Come and learn about «Anatomy of Massive Activations and Attention Sinks», 📆 today (Thu) at 🕥 10:30, 📍 HALL A #3002. #ICML2026

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This is an announcement for a technical talk at ICML 2026 scheduled for Thursday at 10:30 AM in Hall A room 3002, focusing on the anatomy of massive activations and attention sinks—likely discussing h

Creating Power Distribution Network Layouts Using Generative Adversarial Networks and Image-Based Representations

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arXiv:2607.06622v1 Announce Type: cross Abstract: Utilities increasingly rely on planning and operational tools to cope with the increased penetrations of distributed energy resources, yet the lack of

Ensemble Deep Learning Approaches for AI-Altered Video Detection

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arXiv:2607.06872v1 Announce Type: new Abstract: The increasing accessibility of artificial intelligence has led to a rapid rise in AI-generated videos, making it more difficult to distinguish between

Fast, Slow, and Tool-augmented Thinking for LLMs: A Review

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arXiv:2508.12265v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable progress in reasoning across diverse domains. However, effective reasoning in real-world t

FL Studio 2026 turns its AI chatbot into your assistant engineer

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Last year, Image Line introduced Gopher for FL Studio, an AI chatbot that was basically a glorified instruction manual. You asked it how to do something, and it would serve up the relevant instruction

From system models to class models: An in-context learning paradigm

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arXiv:2308.13380v3 Announce Type: replace-cross Abstract: Is it possible to understand the intricacies of a dynamical system not solely from its input/output pattern, but also by observing the behavio

Generative Diffusion Models of Stochastic Graph Signals

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arXiv:2607.06833v1 Announce Type: new Abstract: Sampling stochastic signals supported on a graph underlies many graph machine learning tasks, including recommender systems, forecasting in financial ma

HiMoE-VLA: Hierarchical Mixture-of-Experts for Generalist Vision-Language-Action Policies

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arXiv:2512.05693v2 Announce Type: replace-cross Abstract: Generalist vision--language--action (VLA) policies are typically trained on heterogeneous mixtures of robot demonstrations spanning diverse em

I will present tomorrow our recent work on Crys-JEPA, where we use Joint Embedding Predictive Architectures to learn crystal distributions f…

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I will present tomorrow our recent work on Crys-JEPA, where we use Joint Embedding Predictive Architectures to learn crystal distributions for materials discovery. https://www.linkedin.com/posts/zhong

Learn more with the blog and workflows: https://links.comfy.org/4y3lNuS

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ComfyUI announced resources for users to deepen their knowledge through their official blog and workflow documentation, with a link provided for accessing these educational materials. The post encoura

Managers, and their belief in the value of AI & how to use it, determines the value they actually get from AI. Neat paper looking at startup…

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Managers, and their belief in the value of AI & how to use it, determines the value they actually get from AI. Neat paper looking at startups. 🤖Excited to share a new working paper🤖 Firms aren't built

MILES: Modular Instruction Memory with Learnable Selection for Self-Improving LLM Reasoning

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arXiv:2607.06974v1 Announce Type: new Abstract: Large language models (LLMs) increasingly improve their reasoning at test time via additional computation, yet most existing works treat each problem in

On the Principles of Deep Feedforward ReLU Networks

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arXiv:2607.07035v1 Announce Type: cross Abstract: The architecture of deep feedforward neural networks is ubiquitous in deep learning, either as a whole system or as a subnetwork of other architecture

Optimal Conformal Prediction under Epistemic Uncertainty

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arXiv:2505.19033v2 Announce Type: replace-cross Abstract: Conformal prediction (CP) is a widely used frequentist framework to quantify uncertainty by constructing prediction sets with user-specified m

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection

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arXiv:2607.07192v1 Announce Type: new Abstract: In this paper, we study Single-Domain Generalized Object Detection (Single-DGOD), which aims to transfer a detector trained on a single source domain to

Recovering Candidate Circadian Regulators of Arrhythmic Pituitary Hormone Genes Using Reliability-Weighted Magnetic Laplacian with rwMagLap

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arXiv:2607.06579v1 Announce Type: cross Abstract: We study how to recover candidate circadian-clock regulators of pituitary hormone genes that are important for women's health but do not show a clear

Research on Domain Information Mining and Theme Evolution of Scientific Papers

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arXiv:2204.08476v2 Announce Type: replace-cross Abstract: In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased

Smooth Operator: A Real-Time Sampling-Based Algorithm for Kinematic Hand Retargeting

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arXiv:2607.07491v1 Announce Type: new Abstract: Advances in learning-based robotic manipulation, such as Vision-Language-Action (VLA) models and Video Action Models (VAMs), heavily rely on high-qualit

SPECTRA: Context-Conditioned Spectral Movement Primitives for Robot Skill Generalization

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arXiv:2607.06978v1 Announce Type: new Abstract: Robot imitation learning for manipulation should preserve demonstrated task geometry while producing dynamically admissible robot motions. Existing pipe

Technical writing is the #1 top-of-funnel motion at a $12B company @philipkiely broke down exactly how he does it, his full writing process,…

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Technical writing is the #1 top-of-funnel motion at a $12B company @philipkiely broke down exactly how he does it, his full writing process, the hindsight 20/20 lessons, and how one article drove 500K

The Signs Were Always There: Training-Free Concept Detection and Steering in Raw Transformer Dimensions

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arXiv:2606.12629v3 Announce Type: replace-cross Abstract: The standard basis of transformer hidden states is a training-free, architecture-general feature basis for detecting concepts and, in language

Towards Understanding Steering Strength

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arXiv:2602.02712v2 Announce Type: replace-cross Abstract: A popular approach to post-training control of large language models (LLMs) is the steering of intermediate latent representations. Namely, id

We stand at a critical crossroads in the debate over AI governance in the United States, and it feels like we are inching closer to a very s…

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We stand at a critical crossroads in the debate over AI governance in the United States, and it feels like we are inching closer to a very serious battle over whether or not open source models will ev

While the writing style of LLMs is still as recognizable as ever, a new trend is that humans have started organically writing like them, too…

TutorialsDGX agent

While the writing style of LLMs is still as recognizable as ever, a new trend is that humans have started organically writing like them, too (which makes sense: of course you would end up imitating th

8 Jul 2026

A Convex Approximation Framework for Neural Likelihood-Based Bayesian Inverse Problems

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arXiv:2607.06252v1 Announce Type: cross Abstract: Many problems in science and engineering are difficult to model accurately, either due to unknown physical mechanisms, poorly quantified measurement u

A Definition and Roadmap for World Models

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arXiv:2607.06401v1 Announce Type: new Abstract: World models -- internal simulators that learn the structure and dynamics of an environment -- have become one of the most actively debated concepts in

America, the Beautiful

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America, the Beautiful Elon Musk just said the one thing about America they made sure you’d never learn. The one thing that should’ve made you proud, not ashamed. Musk: “After World War 2, the US coul

Base Models Know How to Reason, Thinking Models Learn When

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arXiv:2510.07364v4 Announce Type: replace Abstract: What do thinking language models learn during training that their base models lack? We first present an unsupervised method that discovers a model's

Blind Quality Enhancement of Compressed Video via Fine-Grained Degradation-Guided Sequential Inference

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arXiv:2511.16137v2 Announce Type: replace Abstract: Existing studies on quality enhancement for compressed video (QECV) predominantly rely on known quantization parameters (QPs), training separate enh

🚨BREAKING: Rupert Lowe talks to Joe Rogan about the 'Rape Gang Inquiry' report. 'The genesis of the rape gangs was this multicultural invas…

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🚨BREAKING: Rupert Lowe talks to Joe Rogan about the 'Rape Gang Inquiry' report. 'The genesis of the rape gangs was this multicultural invasion of Europe. They wanted open borders.' 'We've estimated a

Breaking Spurious Correlations via Generative Randomization and Cross-Variant Self-Supervised Learning

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arXiv:2607.05850v1 Announce Type: new Abstract: Deep neural networks trained with Empirical Risk Minimization (ERM) often fail under distribution shifts because they exploit spurious correlations betw

Canopy: A Heterograph Foundation Model for Metabolic Engineering

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arXiv:2607.06224v1 Announce Type: new Abstract: Designing microbial strains that produce high-value chemicals at commercially viable titers remains a central challenge in metabolic engineering. Existi

Contextual Procurement Auctions with Bandit Learning

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arXiv:2607.05813v1 Announce Type: cross Abstract: We study repeated contextual procurement auctions in which the platform must learn context-dependent product values from bandit feedback. We give an e

FGAA-FPN: Foreground-Guided Angle-Aware Feature Pyramid Network for Oriented Object Detection

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arXiv:2602.10710v2 Announce Type: replace Abstract: With the increasing availability of high-resolution remote sensing and aerial imagery, oriented object detection has become a key capability for geo

FlexAct: Why Learn when you can Pick?

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arXiv:2601.06441v2 Announce Type: replace Abstract: Learning activation functions has emerged as a promising direction in deep learning, allowing networks to adapt activation mechanisms to task-specif

For the past year, MAGA has been screaming “Europoor” like a cheap car alarm going off at three in the morning. Nobody asked for it, nobody …

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For the past year, MAGA has been screaming “Europoor” like a cheap car alarm going off at three in the morning. Nobody asked for it, nobody knows how to turn it off. But then along comes this chart. A

Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion

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arXiv:2607.06546v1 Announce Type: cross Abstract: Denoising graphs is a fundamental problem in graph learning and the core operation of graph diffusion models. Attention-based architectures like graph

Helping K–12 educators build practical AI skills

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OpenAI provides resources and guidance to help K-12 educators develop practical skills in teaching and implementing artificial intelligence concepts in their classrooms. The initiative aims to equip t

How Can Mamba Learn In Context with Outliers and Generalize Provably?

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arXiv:2510.00399v2 Announce Type: replace Abstract: The Mamba model has gained significant attention for its computational advantages over Transformer-based models, while achieving comparable performa

How Personas Can Influence Agents to Play Split or Steal

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arXiv:2607.05398v1 Announce Type: new Abstract: Personas are often employed to guide large language model agents, yet their effectiveness in shaping strategic behavior in social dilemma settings remai

How to Evaluate an Enterprise Analytics Platform

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This guide provides criteria and best practices for assessing enterprise analytics platforms, likely covering key evaluation factors such as scalability, performance, integration capabilities, ease of

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