applications

CYGNET: Cypher Gate for Neural Execution Triage and Cost Containment

arXiv:2606.04645v1 Announce Type: new Abstract: Language models acting as agents over knowledge graphs generate Cypher queries that fail structurally (crashing at the database) or semantically (execut

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Distributional Approximate Nearest Neighbour Search for Uncertainty-Aware Retrieval

DGX agent

arXiv:2606.04603v1 Announce Type: cross Abstract: Approximate Nearest Neighbour search indices form the backbone of real-world recommender systems, enabling real-time candidate retrieval over million-

applicationsarxiv-cs-lg

4 Jun 2026

Dynamic Content Moderation in Livestreams: Combining Supervised Classification with MLLM-Boosted Similarity Matching

arXiv:2512.03553v3 Announce Type: replace-cross Abstract: Content moderation remains a critical yet challenging task for large-scale user-generated video platforms, especially in livestreaming environ

Early Detection of Alzheimer's Disease Using Explainable Machine Learning on Clinical Biomarkers: A Multi-Class Classification Study Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) Dataset

arXiv:2606.03995v1 Announce Type: cross Abstract: Background: Alzheimer's disease (AD) affects over 55 million people worldwide. Accurate, interpretable detection of normal cognition (NC), mild cognit

Enterprise AI usage leaderboards are BAD and lead to the wrong behaviors. Employees feel pressure to hit higher token usage numbers without …

applicationsallie-k--miller--x

Enterprise AI usage leaderboards are BAD and lead to the wrong behaviors. Employees feel pressure to hit higher token usage numbers without any of the positive work transformation. I’ve heard directly

Expectations vs. Realities: The Cost of MSE-Optimal Forecasting Under Conditional Uncertainty

arXiv:2606.04342v1 Announce Type: cross Abstract: Multi-step time series forecasting (MSF) is commonly evaluated using point-wise error metrics such as mean squared error (MSE), implicitly treating th

Federated Learning for Multi-Center Sepsis Early Prediction with Privacy-Preserving

arXiv:2606.04338v1 Announce Type: new Abstract: Privacy-sensitive and distributed characteristics of multi-center medical data bring severe obstacles to centralized modeling for accurate early predict

Fine-grained Fragment Retrieval in Multi-modal Long-form Dialogues

arXiv:2606.04591v1 Announce Type: new Abstract: With the widespread adoption of multi-modal communication platforms, long-form dialogues interleaving text and images have become increasingly common. U

Fixed Aggregation Features Can Rival GNNs

arXiv:2601.19449v2 Announce Type: replace Abstract: Graph neural networks (GNNs) are widely believed to excel at node representation learning through trainable neighborhood aggregations. We challenge

From Motion Signals to Insights: A Unified Framework for Student Behavior Analysis and Feedback in Physical Education Classes

arXiv:2503.06525v2 Announce Type: replace-cross Abstract: Analyzing student behavior in educational scenarios is crucial for enhancing teaching quality and student engagement. Existing AI-based models

Generating Financial Time Series by Matching Random Convolutional Features

arXiv:2606.05138v1 Announce Type: new Abstract: Generating realistic financial time series is challenging as training data is often limited to a single historical path. With such scarce data, overfitt

GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors

arXiv:2606.05160v1 Announce Type: new Abstract: Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleop

applicationsarxiv-cs-ro

I actually read this & it is super weird, it appears to be an argument that prior machine learning systems (not generative AI) did not gener…

I actually read this & it is super weird, it appears to be an argument that prior machine learning systems (not generative AI) did not generate savings due to data issues so that will lead to a lack o

I think it is really worth reading this piece on RSI at Anthropic. There is a bit of navel-gazing, some marketing, and a lot of very sincere…

I think it is really worth reading this piece on RSI at Anthropic. There is a bit of navel-gazing, some marketing, and a lot of very sincere beliefs about what Anthropic thinks is likely in the near f

Implicit Fuzzification via Bounded Noise Injection for Robust Medical Image Segmentation

arXiv:2606.04427v1 Announce Type: new Abstract: Image segmentation remains fundamentally limited by boundary ambiguity arising from sampling-induced information loss and inherent uncertainty in pixel-

In general, OpenAI and Anthropic documentation lags their own products by months, and both companies have tons of obsolete and contradictory…

Ethan Mollick observes that both OpenAI and Anthropic's official documentation frequently falls behind their actual product releases by several months, resulting in outdated and conflicting informatio

Internal docs from lawsuits by 1,400 school districts show how social media companies targeted kids: Meta paid 'teen ambassadors', Snap sent school-hour alerts (Jennifer Valentino-DeVries/New York Times)

Jennifer Valentino-DeVries / New York Times: Internal docs from lawsuits by 1,400 school districts show how social media companies targeted kids: Meta paid “teen ambassadors”, Snap sent school-hour al

applicationstechmeme

KITE: Kernelized and Information Theoretic Exemplars for In-Context Learning

arXiv:2509.15676v2 Announce Type: replace-cross Abstract: In-context learning (ICL) has emerged as a powerful paradigm for adapting large language models (LLMs) to new and data-scarce tasks using only

Learning What Not to Impute: An Uncertainty-Aware Diffusion Framework for Meaningful Missingness

arXiv:2606.05073v1 Announce Type: new Abstract: Missing value imputation is a fundamental task in machine learning, with most existing methods assuming that all missing entries correspond to unobserve

Local Clustering on Complex Graphs and Complex Hypergraphs

arXiv:2412.03008v2 Announce Type: replace-cross Abstract: Local/seeded clustering aims to find a compact cluster near the given starting instances. While most existing studies on graph clustering assu

Long-Term and Short-Term Transistor Aging in Deep Neural Networks: Impact and Mitigation

arXiv:2606.04266v1 Announce Type: cross Abstract: Deep neural networks (DNNs) are used in a variety of real-world applications including, for example, image classification and speech recognition. The

Low-rank Distributional Matrix Completion

arXiv:2606.04176v1 Announce Type: new Abstract: We study a distributional generalization of the matrix completion problem in which each entry of the target matrix is a probability distribution rather

Multi-Camera AR Guidance System for Surgical Instrument Handling and Assembly: Investigating Workload and Efficiency

arXiv:2606.04992v1 Announce Type: new Abstract: The handling and assembly of instruments during surgery imposes high cognitive demands on scrub nurses, particularly when instruments are unfamiliar. We

Orthogonal Learner for Estimating Heterogeneous Long-Term Treatment Effects

arXiv:2604.00915v2 Announce Type: replace Abstract: Estimation of heterogeneous long-term treatment effects (HLTEs) is relevant for personalized decision-making in marketing, economics, and medicine,

Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models

arXiv:2606.04822v1 Announce Type: new Abstract: Causal modeling of physical temporal phenomena must handle interventions that act along trajectories, nonstationary induced laws, path-dependent effects

Reflection Separation from a Single Image via Joint Latent Diffusion

arXiv:2606.04107v1 Announce Type: new Abstract: Single-image reflection separation is highly challenging under extreme conditions like glare or weak reflections. Existing methods often struggle to rec

reiterating: 'We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficie…

applicationsclem-delangue--x

reiterating: 'We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficient models that are more efficient on a token basis or are op

Sem-NaVAE: Semantically-Guided Outdoor Mapless Navigation via Generative Trajectory Priors

arXiv:2602.01429v2 Announce Type: replace Abstract: This work presents a mapless navigation approach for outdoor applications. It combines the exploratory capacity of conditional variational autoencod

applicationsarxiv-cs-ro

SpaceX’s literally destroyed the cost to orbit so much even you can afford the ticket to ride on it in the future - For decades, launch cost…

SpaceX’s literally destroyed the cost to orbit so much even you can afford the ticket to ride on it in the future - For decades, launch cost to low Earth orbit was roughly 18,500 per kg - Falcon 9 bro

applicationselon-musk--x

Sparse Bayesian Deep Functional Learning with Structured Region Selection

arXiv:2602.20651v3 Announce Type: replace Abstract: In modern applications such as ECG monitoring, neuroimaging, wearable sensing, and industrial equipment diagnostics, complex and continuously struct

SSSD: Simply-Scalable Speculative Decoding

arXiv:2411.05894v3 Announce Type: replace-cross Abstract: Speculative Decoding has emerged as a popular technique for accelerating inference in Large Language Models. However, most existing approaches

Stationarity-Aware Retrieval-Augmented Time Series Forecasting

arXiv:2606.04135v1 Announce Type: new Abstract: Time series forecasting relies on historical patterns, but real-world series often exhibit non-stationarity and regime shifts that challenge fully param

StrokeTimer: Robust Representation Learning for Ischemic Stroke Onset-Time Estimation from Non-contrast CT

arXiv:2606.04722v1 Announce Type: new Abstract: Ischemic stroke is a major global disease. Treatment decisions are highly time-sensitive, as eligibility for reperfusion therapies relies on the interva

The Cost of Learning Under Multiple Change Points

arXiv:2602.11406v2 Announce Type: replace-cross Abstract: We consider an online learning problem in environments with multiple change points. In contrast to the single change point problem that is wid

The Differentiable Auditory Loop (DAL): An ML Framework for Hyper-Personalized Hearing Aids

arXiv:2606.04103v1 Announce Type: cross Abstract: Conventional hearing aids rely on fixed, frequency-dependent amplification and compression to manage reduced sensitivity, which often fails to provide

The Mechanistic Emergence of Symbol Grounding in Language Models

arXiv:2510.13796v3 Announce Type: replace Abstract: Symbol grounding (Harnad, 1990) describes how symbols such as words acquire their meanings by connecting to real-world sensorimotor experiences. Rec

There are lots of issues with GenAI implementations but surveys seem to suggest broad positive ROI. Data & stories about AI failures are rea…

There are lots of issues with GenAI implementations but surveys seem to suggest broad positive ROI. Data & stories about AI failures are real and useful but need to be clearer about what they are meas

Towards Evaluating the Robustness of Visual State Space Models

arXiv:2406.09407v3 Announce Type: replace Abstract: Vision State Space Models (VSSMs), a novel architecture that combines the strengths of recurrent neural networks and latent variable models, have de

Trusted healthcare AI hinges on data foundations, not models alone

Healthcare AI is moving out of the pilot phase and into production environments, where the gap between a compelling demo and a clinically trustworthy output has never been more consequential. As AI ag

applicationssiliconangle

TSMC struggles to keep up with AI demand: ‘We can only support so much’

Taiwan Semiconductor Manufacturing Co. - the world's biggest semiconductor-maker - is struggling to meet demands from American customers even with its factory buildout in the US, according to reports

applicationsthe-verge-ai

Ultra-Fast Neural Video Compression

arXiv:2606.04410v1 Announce Type: new Abstract: While neural video codecs (NVCs) have demonstrated superior compression ratio, their prohibitive computational complexity remains a critical barrier to

UltraEP: Unleash MoE Training and Inference on Rack-Scale Nodes with Near-Optimal Load Balancing

arXiv:2606.04101v1 Announce Type: cross Abstract: Large-scale expert parallelism (EP) is becoming pivotal for training and serving frontier MoE models, but it also amplifies device-level expert load i

Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication

arXiv:2606.04850v1 Announce Type: cross Abstract: Designing a neural network processor is an end-to-end co-design problem: network architecture and training budget determine the inference workload; ha

Updates to Legal Terms

Vercel announced updates to its legal terms and conditions in June 2026, likely covering changes to their service agreements, privacy policies, or terms of service. This update would apply to users of

applicationsvercel-blog

Using Text-Based Causal Inference to Disentangle Factors Influencing Online Review Ratings

arXiv:2606.04286v1 Announce Type: new Abstract: Online reviews provide valuable insights into the perceived quality of facets of a product or service. While aspect-based sentiment analysis has focused

Variance Reduction for Heavy-Tailed Monetization Metrics in Ranking Experiments via Post-Stratification

arXiv:2606.04110v1 Announce Type: new Abstract: Online evaluation of ranking and retrieval systems often relies on downstream monetization metrics such as app revenue or creator earnings. These metric

Vibe coding moves from weekend hobby to enterprise change management mandate

Artificial intelligence is rewriting how software gets built inside large enterprises — not just at the tooling level, but at the level of culture, governance and organizational change. The rise of vi

applicationssiliconangle

What to expect during Broadcom’s ‘Modern Private Cloud’ event: Join theCUBE June 9

Enterprise AI is forcing companies to rethink where their most sensitive workloads should live, and private cloud is moving deeper into the center of that decision. For many organizations, the cloud c

applicationssiliconangle