tutorials

Learning to Think from Multiple Thinkers

arXiv:2604.24737v1 Announce Type: cross Abstract: We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different so

Local Mechanisms of Compositional Generalization in Conditional Diffusion

Conditional diffusion models appear capable of compositional generalization, i.e., generating convincing samples for out-of-distribution combinations of conditioners, but the mechanisms underlying thi

tutorialsapple-ml-research

28 Apr 2026

LunarDepthNet: Generation of Digital Elevation Models using Deep Learning and Monocular Satellite Images

arXiv:2604.22848v1 Announce Type: new Abstract: Recent times have seen an increase in demand of high quality Digital Elevation Models (DEMs) for the lunar surface, because they are highly important fo

MAE-Based Self-Supervised Pretraining for Data-Efficient Medical Image Segmentation Using nnFormer

arXiv:2604.22854v1 Announce Type: cross Abstract: Transformer architectures, including nnFormer,have demonstrated promising results in volumetric medical image segmentation by being able to capture lo

Mitigating Error Amplification in Fast Adversarial Training

arXiv:2604.24332v1 Announce Type: new Abstract: Fast Adversarial Training (FAT) has proven effective in enhancing model robustness by encouraging networks to learn perturbation-invariant representatio

Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation

arXiv:2412.07160v3 Announce Type: replace Abstract: To equip artificial intelligence with a comprehensive understanding towards a temporal world, video and 4D panoptic scene graph generation abstracts

Out of Spuriousity: Improving Robustness to Spurious Correlations without Group Annotations

arXiv:2407.14974v2 Announce Type: replace-cross Abstract: Machine learning models are known to learn spurious correlations, i.e., features having strong relations with class labels but no causal relat

PEPS: Positional Encoding Projected Sampling -- Extended

arXiv:2604.24167v1 Announce Type: new Abstract: Implicit neural representations (INRs) are increasingly being used as tools to map coordinates to signals, encompassing applications from neural fields

Point-MF: One-step Point Cloud Generation from a Single Image via Mean Flows

arXiv:2604.24586v1 Announce Type: new Abstract: Single-image point cloud reconstruction must infer complete 3D geometry, including occluded parts, from a single RGB image. While diffusion-based recons

Probing Visual Planning in Image Editing Models

arXiv:2604.22868v1 Announce Type: cross Abstract: Visual planning represents a crucial facet of human intelligence, especially in tasks that require complex spatial reasoning and navigation. Yet, in m

Propagation Structure-Semantic Transfer Learning for Robust Fake News Detection

arXiv:2604.23974v1 Announce Type: new Abstract: Fake news generally refers to false information that is spread deliberately to deceive people, which has detrimental social effects. Existing fake news

tutorialsarxiv-cs-cl

Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation

arXiv:2510.11541v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has demonstrated its ability to enhance Large Language Models (LLMs) by integrating external knowledge so

ReFinE: Streamlining UI Mockup Iteration with Research Findings

arXiv:2604.04353v2 Announce Type: replace-cross Abstract: Although HCI research papers offer valuable design insights, designers often struggle to apply them in design workflows due to difficulties in

Reheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms

arXiv:2604.23842v1 Announce Type: cross Abstract: Neologisms and emerging slang are central to daily conversation, yet challenging for non-native speakers (NNS) to interpret and use appropriately in c

Representational Curvature Modulates Behavioral Uncertainty in Large Language Models

arXiv:2604.23985v1 Announce Type: new Abstract: In autoregressive large language models (LLMs), temporal straightening offers an account of how the next-token prediction objective shapes representatio

Robust Grounding with MLLMs against Occlusion and Small Objects via Language-guided Semantic Cues

arXiv:2604.24036v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have enhanced grounding capabilities in general scenes, their robustness in crowded scenes remains undere

Shallow Neural Networks Learn Low-Degree Spherical Polynomials with Feature Learning by Learnable Channel Attention

arXiv:2512.20562v2 Announce Type: replace-cross Abstract: We study the problem of learning a low-degree spherical polynomial of degree ell_0 = Theta(1) ge 1 defined on the unit sphere in RR^d by train

Should we care about AI happiness? In our new research, we find evidence of functional AI wellbeing across several independent measures. We …

tutorialsdan-hendrycks--x

Should we care about AI happiness? In our new research, we find evidence of functional AI wellbeing across several independent measures. We find which AI models are happiest, how to make them happier,

SMoES: Soft Modality-Guided Expert Specialization in MoE-VLMs

arXiv:2604.23996v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent backbone for large vision-language models (VLMs), yet how modality-specific signals should guide expert

SRL-CLIP: Efficient CLIP Video Adaptation via Structured Semantic Role Labels

arXiv:2401.07669v2 Announce Type: replace Abstract: Adapting CLIP for videos has gained popularity due to its semantic and rich representation. While CLIP is a good starting point, it typically underg

StereoSpace: Depth-Free Synthesis of Stereo Geometry via End-to-End Diffusion in a Canonical Space

arXiv:2512.10959v2 Announce Type: replace Abstract: We introduce StereoSpace, a diffusion-based framework for monocular-to-stereo synthesis that models geometry purely through viewpoint conditioning,

Structure Guided Retrieval-Augmented Generation for Factual Queries

arXiv:2604.22843v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has been proposed to mitigate hallucinations in large language models (LLMs), where generated outputs may be fact

Survey in Characterizing Semantic Change

arXiv:2402.19088v5 Announce Type: replace-cross Abstract: Live languages continuously evolve to integrate the cultural change of human societies. This evolution manifests through neologisms (new words

Tandem: Riding Together with Large and Small Language Models for Efficient Reasoning

arXiv:2604.23623v1 Announce Type: new Abstract: Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit st

The Power of Power Law: Asymmetry Enables Compositional Reasoning

arXiv:2604.22951v1 Announce Type: new Abstract: Natural language data follows a power-law distribution, with most knowledge and skills appearing at very low frequency. While a common intuition suggest

This year's AI Accelerator winners shipped agents for finance teams, application security, and real estate. They built with $8M in credits a…

This year's AI Accelerator winners shipped agents for finance teams, application security, and real estate. They built with $8M in credits and hands-on mentorship from Vercel, @awscloud, @OpenAI, @Ant

tutorialsvercel--x

TokenTrace: Multi-Concept Attribution through Watermarked Token Recovery

arXiv:2602.19019v2 Announce Type: replace Abstract: Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without a

Universal approximation property of Banach space-valued random feature models including random neural networks

arXiv:2312.08410v5 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel

What's new in pip 26.1 - lockfiles and dependency cooldowns!

What's new in pip 26.1 - lockfiles and dependency cooldowns! Richard Si describes an excellent set of upgrades to Python's default pip tool for installing dependencies. This version drops support for

tutorialssimon-willison

When AI reviews science: Can we trust the referee?

arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s

ZID-Net: Zero-Inference Diffusion Prior Decoupling Network for Single Image Dehazing

arXiv:2604.23709v1 Announce Type: new Abstract: Single image dehazing is often constrained by a trade-off between restoration quality and computational efficiency. While efficient, CNN networks strugg

Are Natural-Domain Foundation Models Effective for Accelerated Cardiac MRI Reconstruction?

arXiv:2604.22557v1 Announce Type: cross Abstract: The emergence of large-scale pretrained foundation models has transformed computer vision, enabling strong performance across diverse downstream tasks

At #ICLR? Don’t miss @realDanFu 👇 Latent & Implicit Thinking Workshop (LIT) 🕐 Workshop at 1:30 PM BRT (local) Exploring what comes after c…

At #ICLR? Don’t miss @realDanFu 👇 Latent & Implicit Thinking Workshop (LIT) 🕐 Workshop at 1:30 PM BRT (local) Exploring what comes after chain-of-thought and how models may actually reason. 🔗 https://

tutorialstogether-ai--x

Automate repetitive tasks with Amazon Quick Flows

Amazon Quick Flows enables users to build automations for repetitive or routine tasks using simple, everyday language prompts , with no technical expertise required. The service uses an AI-powered UI

tutorialsaws-ml-blog

Beyond Patient Invariance: Learning Cardiac Dynamics via Action-Conditioned JEPAs

arXiv:2604.22618v1 Announce Type: new Abstract: Self-supervised learning in healthcare has largely relied on invariance-based objectives, which maximize similarity between different views of the same

CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting

arXiv:2604.22636v1 Announce Type: cross Abstract: Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual sett

Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions

arXiv:2512.20831v2 Announce Type: replace Abstract: Real-world sequential decision-making often involves parameterized action spaces that require both, decisions regarding discrete actions and decisio

Distilling Vision Transformers for Distortion-Robust Representation Learning

arXiv:2604.22529v1 Announce Type: new Abstract: Self-supervised learning has achieved remarkable success in learning visual representations from clean data, yet remains challenging when clean observat

Evidence of an Emergent 'Self' in Continual Robot Learning

arXiv:2603.24350v2 Announce Type: replace-cross Abstract: A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a 'sel

GCImOpt: Learning efficient goal-conditioned policies by imitating optimal trajectories

arXiv:2604.22724v1 Announce Type: new Abstract: Imitation learning is a well-established approach for machine-learning-based control. However, its applicability depends on having access to demonstrati

tutorialsarxiv-cs-ro

GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms

arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th

How to build scalable web apps with OpenAI's Privacy Filter

This article likely discusses techniques for building web applications that integrate OpenAI's APIs while maintaining user privacy through filtering mechanisms. It probably covers implementation strat

tutorialshugging-face

It just takes a little time and care to engage with the work of new folks in the field -- but it can make a big difference :D

tutorialsjeremy-howard--x

It just takes a little time and care to engage with the work of new folks in the field -- but it can make a big difference :D On a more personal note, I'm grateful to @jeremyphoward for helping me bre

jBOT: Semantic Jet Representation Clustering Emerges from Self-Distillation

arXiv:2601.11719v3 Announce Type: replace Abstract: Self-supervised learning, in the context of foundation model training, is a powerful pre-training method for learning feature representations withou

Join the new AI Agents Vibe Coding Course from Google and Kaggle

Google and Kaggle are offering a free five-day AI Agents Intensive course running June 15–19, 2026. The course teaches 'vibe coding' to create programs using natural language, with hands-on projects t

tutorialsgoogle-ai

last week we dropped a super comprehensive guide on runtime requirements for long running agents! this week i'll be diving into each require…

tutorialsharrison-chase--x

last week we dropped a super comprehensive guide on runtime requirements for long running agents! this week i'll be diving into each requirement and runtime capability that meets it, here's the lineup

Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data

arXiv:2604.22212v1 Announce Type: cross Abstract: In spite of the utility of 3-D electron back-scattered diffraction (EBSD) microscopy, the data collection process can be time-consuming with serial-se

One Shot Learning for Edge Detection on Point Clouds

arXiv:2604.22354v1 Announce Type: new Abstract: Each scanner possesses its unique characteristics and exhibits its distinct sampling error distribution. Training a network on a dataset that includes d