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If you are a mathematician, then you may want to make sure you are sitting down before reading further.

tutorialsjeremy-howard--x

This post likely discusses a surprising or shocking mathematical discovery, result, or announcement that would be of particular interest to mathematicians. Based on the dramatic framing, it probably p

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IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection

DGX agent

arXiv:2603.29183v2 Announce Type: replace-cross Abstract: Open-set anomaly detection (OSAD) is an emerging paradigm designed to utilize limited labeled data from anomaly classes seen in training to id

tutorialsarxiv-cs-ai

20 May 2026

INAR-VL: Input-Aware Routing for Edge-Cloud Vision-Language Inference

arXiv:2605.18853v1 Announce Type: cross Abstract: Edge deployment of Vision-Language Models (VLMs) faces a tradeoff between latency and accuracy: cloud execution provides high-quality predictions but

KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition

arXiv:2605.19031v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) have demonstrated an exceptional ability to learn complex functions on clean, low-dimensional data but struggle to mai

Language Model Memory and Memory Models for Language

arXiv:2602.13466v2 Announce Type: replace-cross Abstract: The ability of machine learning models to store input information in hidden layer vector embeddings, analogous to the concept of `memory', is

Language models struggle with compartmentalization

arXiv:2605.19284v1 Announce Type: new Abstract: In the training data used by large language models (LLMs), the same latent concept is often presented in multiple distinct ways: the same facts appear i

tutorialsarxiv-cs-cl

Latent Laplace Diffusion for Irregular Multivariate Time Series

arXiv:2605.19805v1 Announce Type: cross Abstract: Irregular multivariate time series impose a trade-off for long-horizon forecasting: discrete methods can distort temporal structure via re-gridding, w

Learning Interpretable Point-Based Clinical Risk Scores via Direct Optimization

arXiv:2605.19113v1 Announce Type: cross Abstract: Many clinical risk scores are deployed as additive rules with nonnegative integer points assigned to relevant binary predictive features. These intege

Neurosymbolic Learning for Inference-Time Argumentation

arXiv:2605.20098v1 Announce Type: new Abstract: Claim verification is an important problem in high-stakes settings, including health and finance. When information underpinning claims is incomplete or

OP2GS: Object-Aware 3D Gaussian Splatting with Dual-Opacity Primitives

arXiv:2605.20044v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) provides an explicit and efficient scene representation, but its primitives lack inherent object-level identity, hindering

relations can carry behaviors - depends_on can unblock work - contradicts can know how to trigger review - derived_from can know how to inva…

tutorialsyohei-nakajima--x

This post discusses how different types of relations or dependencies in systems can carry behavioral properties, where dependencies like 'depends_on' can unblock work progression, contradictions can t

See MiniMax Speech 2.8 Turbo in voice finder and try the voices directly: https://voicefinder.together.ai/minimax--speech-2.8-turbo Learn mo…

MiniMax Speech 2.8 Turbo is a text-to-speech model available through Together AI's voice finder tool at voicefinder.together.ai, allowing users to preview and test different voice options directly. Th

tutorialstogether-ai--x

Smartphone-based Circular Plot Sampling for Forest Inventory

arXiv:2605.19213v1 Announce Type: new Abstract: Circular sample plots are a cornerstone of forest inventory, yet accurate measurement of tree diameter at breast height (DBH) and spatial location withi

Structuring Open-Ended NAS: Semi-Automated Design Knowledge Structuring with LLMs for Efficient Neural Architecture Search

arXiv:2605.19247v1 Announce Type: new Abstract: Current neural architecture search (NAS) methods are often limited by their predefined, restrictive search spaces. While recent large language model (LL

The Wrong Side of History Has a Very Specific Smell By Gandalv / @Microinteracti1 Ben Hodges is not a man who wastes words. The former comma…

The Wrong Side of History Has a Very Specific Smell By Gandalv / @Microinteracti1 Ben Hodges is not a man who wastes words. The former commanding general of US Army Europe has spent the better part of

tutorialsyann-lecun--x

Towards Fine-Grained Robustness: Attention-Guided Test-Time Prompt Tuning for Vision-Language Models

arXiv:2605.19956v1 Announce Type: new Abstract: Vision-Language Models (VLMs), such as CLIP, have achieved significant zero-shot performance on downstream tasks with various fine-tuning adaptation met

Tweedie's Formulae and Diffusion Generative Models Beyond Gaussian

arXiv:2605.19391v1 Announce Type: cross Abstract: Diffusion models have achieved remarkable success in generating samples from unknown data distributions. Most popular stochastic differential equation

TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation

arXiv:2602.09023v4 Announce Type: replace Abstract: Despite strong generalization capabilities, Vision-Language-Action (VLA) models remain constrained by the high cost of expert demonstrations and lim

tutorialsarxiv-cs-ro

Urban Outfitters achieves major cost savings by moving Sterling OMS to AlloyDB for PostgreSQL

Editor’s note: Urban Outfitters, Inc. (URBN) recently completed a major infrastructure upgrade, migrating its IBM Sterling Order Management System (Sterling OMS) from an Oracle database to Google Clou

tutorialsgoogle-cloud-ai

wild to see a somewhat disgraced politician comment on the technical side of AI as if he has any idea about the underlying computational que…

wild to see a somewhat disgraced politician comment on the technical side of AI as if he has any idea about the underlying computational questions. and of course he dwells at the bottom of Paul Graham

tutorialsgary-marcus--x

WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling

arXiv:2602.03924v2 Announce Type: replace-cross Abstract: Deep learning has revolutionized weather forecasting, but many challenges remain, including climate modeling. Moreover, the current landscape

A CFO’s guide to managing value-based care financial performance

This guide provides Chief Financial Officers with strategies for financial management and performance optimization in value-based care models, which shift healthcare reimbursement from volume-based to

tutorialsdatabricks

AdaGraph: A Graph-Native Clustering Algorithm That Overcomes the Curse of Dimensionality and Enables Scientific Discovery

arXiv:2605.16320v1 Announce Type: cross Abstract: We present AdaGraph, a graph-native clustering algorithm born from the Structure-Centric Machine Learning (SC-ML) paradigm -- a new field of unsupervi

AI Slop or AI-enhancement? Student perceptions of AI-generated media for an English for Academic Purposes course

arXiv:2605.16275v1 Announce Type: cross Abstract: Artificial intelligence (AI) retrieval-augmented generation (RAG) tools now enable educators to transform course materials into diverse multimedia at

[AINews] How to land a job at a frontier lab (on Pretraining)

This article from Latent Space provides guidance on securing employment at cutting-edge AI research laboratories, with a focus on roles related to pretraining large language models. It likely covers p

tutorialslatent-space

An Interpretable Closed-Loop Intelligent Tutoring System for Multimodal Affective Feedback in Asynchronous Presentation Training

arXiv:2605.17468v1 Announce Type: cross Abstract: This paper presents an interpretable closed-loop Intelligent Tutoring System (ITS) that supports feedback-guided practice for developing on-camera ora

ANVIL: Analogies and Videos for Lecturers

arXiv:2605.16295v1 Announce Type: cross Abstract: We present ANVIL, a multimodal generative system that automates the production of analogy-based instructional animations for computer science topics.

Automated Knowledge Component Generation for Interpretable Knowledge Tracing in Coding Problems

arXiv:2502.18632v4 Announce Type: replace Abstract: Knowledge components (KCs) mapped to problems help model student learning, tracking their mastery levels on fine-grained skills thereby facilitating

Bridging the Gap between Sparse Matrix Reordering and Factorization: A Deep Learning Framework for Fill-in Reduction

arXiv:2605.17339v1 Announce Type: new Abstract: Sparse matrix reordering can significantly reduce the fill-in during matrix factorization, thereby decreasing the computational and storage requirements

CAVE: A Structured Credit Assignment Approach for Fragmented Visual Evidence Reasoning

arXiv:2605.16416v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved strong performance on general multimodal reasoning, yet remain challenged in integrating nonlocal visual i

CBT-Audio: Evaluating Audio Language Models for Patient-Side Distress Intensity Estimation in CBT Session Recordings

arXiv:2605.17370v1 Announce Type: new Abstract: Cognitive behavioural therapy is widely used to help patients understand and manage psychological distress. It is often delivered through spoken convers

Collision-Resistant Single-Pass Method for Unsupervised Fine-Grained Image Hashing

arXiv:2605.18288v1 Announce Type: new Abstract: Unsupervised fine-grained image hashing aims to learn compact binary codes that preserve subtle visual differences among highly similar instances withou

CoLLM-NAS: Collaborative Large Language Models for Efficient Knowledge-Guided Neural Architecture Search

arXiv:2509.26037v2 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Neural Architecture Search (NAS) has introduced new possibilities for automating the design of

Consistency of Learned Sparse Grid Quadrature Rules using NeuralODEs

arXiv:2507.01533v2 Announce Type: replace-cross Abstract: We prove consistency of a recently proposed scheme that evaluates expected values by composing a learned transport map with Clenshaw--Curtis s

Cross-Domain Molecular Relational Learning: Leveraging Chemical Structure-Activity Analysis

arXiv:2605.16799v1 Announce Type: cross Abstract: Recent advances in molecular representation integrates molecular topological and visual modalities, opening new avenues for precise Molecular Relation

CTFS : Collaborative Teacher Framework for Forward-Looking Sonar Image Semantic Segmentation with Extremely Limited Labels

arXiv:2603.21071v2 Announce Type: replace-cross Abstract: As one of the most important underwater sensing technologies, forward-looking sonar exhibits unique imaging characteristics. Sonar images are

deepagents v0.6 is about performance the first level at which we can control that is the model layer: how can you squeeze perf out of a mode…

tutorialsharrison-chase--x

deepagents v0.6 is about performance the first level at which we can control that is the model layer: how can you squeeze perf out of a model? tweaking prompts, tool names, and tool descriptions in ac

Degradation Frequency Curve: An Explicit Frequency-Quantified Representation for All-in-One Image Restoration

arXiv:2605.17506v1 Announce Type: new Abstract: A fundamental difficulty in all-in-one blind image restoration is that degradation is usually treated as an implicit factor hidden in degraded-to-clean

Diffusion Attention Expert Model for Predicting and Semi-automatic Localizing STAS in Lung Cancer Histopathological Images

arXiv:2605.16444v1 Announce Type: cross Abstract: Accurate intraoperative and postoperative diagnosis of spread through air spaces (STAS) is essential for guiding surgical decisions and postoperative

Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection

arXiv:2502.20981v2 Announce Type: replace Abstract: In Open-set Supervised Anomaly Detection (OSAD), the existing methods typically generate pseudo anomalies to compensate for the scarcity of observed

Encoding Robust Topological Signatures for Hyperdimensional Computing

arXiv:2605.16785v1 Announce Type: cross Abstract: Hyperdimensional (HD) computing offers an attractive alternative to deep networks for edge learning due to its simplicity, fast prototype-based infere

Evidence of a Cognitive Shift in AI Education: How Students Are Rethinking Human Intelligence?

arXiv:2605.16292v1 Announce Type: cross Abstract: Perceptions of intelligence shape how learners evaluate and rely on artificial intelligence (AI) systems. Despite rapid advances in AI capabilities, t

Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation

arXiv:2605.16350v1 Announce Type: cross Abstract: We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules,

Few-Shot Network Intrusion Detection Using Online Triplet Mining

arXiv:2605.17530v1 Announce Type: cross Abstract: Network intrusion detection systems play a vital role in protecting networks by detecting malicious network traffic which can then be investigated by

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster

arXiv:2605.18204v1 Announce Type: cross Abstract: Discrete diffusion models are a powerful class of generative models with strong performance across many domains. For efficiency, however, discrete dif

From Prediction to Intervention: The Evolution of AI in Biomedicine

arXiv:2605.16293v1 Announce Type: cross Abstract: Artificial intelligence has advanced rapidly in biomedicine through large-scale multimodal data integration, enabling increasingly accurate prediction

Generating Pretraining Tokens from Organic Data for Data-Bound Scaling

arXiv:2605.17849v1 Announce Type: cross Abstract: LLM pretraining is shifting from a compute-bound to a data-bound regime, where available human (organic) text falls far short of scaling demands. Howe

Generative Adversarial Learning from Deterministic Processes

arXiv:2605.18425v1 Announce Type: new Abstract: Physical AI is being successfully applied to data which does not follow the traditional paradigm of independent and identically distributed (i.i.d.) sam