Search: “concepts”

Universality Reconsidered: Rethinking the Validation of Foundation Models for General-Purpose 3D Medical Segmentation

model-releasesarxiv-cs-cv

arXiv:2602.07643v2 Announce Type: replace Abstract: Foundation models have emerged as a transformative paradigm in 3D medical imaging, with the promise of unified quantitative analysis across diverse

23 Jul 2026

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MindControl - llama.cpp fork to guide the reasoning process via injection during sampling

DGX agent

The primary driver of this project is that I'd become frustrated with the reasoning behavior of smaller local models such as Qwen3.6-27B (i believe particularly at lower temperatures, and where system

model-releasesr-localllama

22 Jul 2026

Why AI apps fail in production (And how Google solved it)

We are living in the golden age of the weekend AI side project. Thanks to agentic engineering and LLMs, the time to go from a blank IDE to a functional local application has dropped from quarters to h

agentsgoogle-cloud-ai

21 Jul 2026

Disentangling Knowledge States with Ability and Proficiency Modeling for Knowledge Tracing

arXiv:2607.13103v1 Announce Type: cross Abstract: Knowledge tracing (KT) aims to predict students' future performance by modeling their evolving knowledge states from historical interactions. Existing

Fine-grained CLIP fine-tuning with self-annotated region alignment

model-releasesarxiv-cs-cv

arXiv:2607.13661v1 Announce Type: new Abstract: Contrastive Language-Image Pre-training (CLIP) has been shown to have limitations in its fine-grained dense feature representation, due to its pre-train

Probabilistic Extension of Neuro-Symbolic AGI Robots based on Belnap's Typed Intensional FOL

arXiv:2607.13073v1 Announce Type: new Abstract: Neuro-symbolic AI based on IFOL_B is a way to combine neural learning and symbolic reasoning to overcome limitations of purely neural systems (like lack

Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models

arXiv:2607.13395v1 Announce Type: new Abstract: The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from t

researcharxiv-cs-lg

Video to All-in-focus Image Reconstruction Algorithm for Automated Microscopic Urinalysis

arXiv:2607.13601v1 Announce Type: cross Abstract: Microscopic urinalysis is a routine diagnostic test at hospitals. Recent studies have demonstrated the effectiveness of deep learning methods to autom

Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model

arXiv:2409.10094v3 Announce Type: replace Abstract: Out-of-Distribution (OoD) detection aims to justify whether a given sample is from the training distribution of the classifier-under-protection, i.e

Bulkhead: Automated Semantic Detection and Remediation of Container Escape Vulnerabilities

arXiv:2607.12723v1 Announce Type: cross Abstract: Filesystem isolation in container ecosystems is often weakened by cross-boundary path misresolution, causing path traversal (PaTra) vulnerabilities. T

Calibrated Selective Prediction Using Deep Ensembles for ROI-Based Thyroid Nodule Ultrasound Classification Under Dataset Shift: A Retrospective Evaluation

arXiv:2607.12075v1 Announce Type: cross Abstract: Background: Deep learning models can classify thyroid nodules on ultrasound, but reliable clinical decision support also requires calibrated probabili

HPC-Enabled Video-based Coastal Wave Parameter Estimation Using V-JEPA and Deep Spatiotemporal Learning

arXiv:2607.11998v1 Announce Type: cross Abstract: High deployment cost, poor spatial coverage and susceptibility to storm conditions are all challenges faced by traditional in-situ methods. This paper

Mitigating The Effect of Class Imbalance in Data with Hierarchical and Dependable Structure

arXiv:2607.11994v1 Announce Type: cross Abstract: Classifying cybersecurity vulnerabilities using the Common Weakness Enumeration (CWE) taxonomy is challenging due to extreme class imbalance and stron

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories

arXiv:2512.04144v3 Announce Type: replace Abstract: Targeted interventions on language models, such as unlearning or model editing, aim to modify specific information, but their effects often propagat

Silent Alarm: A J-Space Protocol for Comparing Danger Recognition Across Models and Quantization Levels

arXiv:2607.12792v1 Announce Type: cross Abstract: Jailbreak-robustness research typically evaluates safety through generated responses using an LLM-as-judge approach. Such evaluations, however, are se

Solution of the Hempel's statistical ambiguity problem and Causal AI

arXiv:2607.12826v1 Announce Type: new Abstract: This paper addresses Carl Hempel's longstanding problem of statistical ambiguity in inductive-statistical inference, in which contradictory predictions

The Sound of Absence: Audio-Language Embedding Models Struggle with Negation

arXiv:2607.12290v1 Announce Type: cross Abstract: Audio-language embedding models such as CLAP are widely evaluated on matching present sound events, but rarely on negation. We show this affirmation-o

Applications

Sovereign AI infrastructure startup Valarian raises $50M to help nations secure their defense systems

The defense-focused artificial intelligence systems infrastructure startup Valarian Technologies Ltd. said today it has closed on a hefty 50 million early-stage funding round as it looks to position i

applicationssiliconangle

14 Jul 2026

Super impressed with what Harvinder and Suman have built at @airtap_ai. They've essentially turned SMS into a headless agentic execution lay…

agentsfrancois-chollet--x

Super impressed with what Harvinder and Suman have built at @airtap_ai. They've essentially turned SMS into a headless agentic execution layer for your mobile apps. You just text it to run errands, an

14 Jul 2026

ArtMine: Discovering and Formalizing Artistic Processes

arXiv:2607.08331v1 Announce Type: cross Abstract: Understanding how artworks are created requires reasoning about the iterative decisions, material operations, and contextual influences that shape art

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing

arXiv:2607.08177v1 Announce Type: new Abstract: In this paper, we study the automatic schema generation problem: given a collection of historical ship maintenance and operational reports across multip

Drift-Aware Temporal Graph Rewiring (DATGR) for Adaptive Semantic Modeling in Biomedical Text

arXiv:2607.08490v1 Announce Type: new Abstract: Biomedical language evolves rapidly as new discoveries emerge, causing traditional text models to lose semantic fidelity over time. Static embeddings an

Frontier and Center: Who evaluates the evaluations?

model-releasesgoogle-cloud-ai

Editor’s note: Some of the most interesting questions in AI are being asked by information theoreticians, around how to provide context to an emerging class of AI agents. A few weeks ago, we waded int

I fell for a lot of progressive nonsense, and hard. I was literally trans. But two things I can honestly say I never fell for were 1. altern…

I fell for a lot of progressive nonsense, and hard. I was literally trans. But two things I can honestly say I never fell for were 1. alternative ways of knowing. Science obviously works, and it’s har

tutorialselon-musk--x

I have spent years teaching people how AI agents work, but this one does not need an explanation. It just works. Meet the AI employee that 4…

This post highlights a practical AI agent that operates intuitively without requiring explanation of its underlying mechanics, suggesting it has achieved a user-friendly interface or autonomous functi

researchdair-ai--x

Leveraging Color Naming for Image Enhancement

arXiv:2607.08185v1 Announce Type: cross Abstract: Enhancing images to make them visually appealing is a persistent challenge in computer vision. Many deep-learning methods train models on paired datas

LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting

model-releasesarxiv-cs-cv

arXiv:2607.08016v1 Announce Type: new Abstract: Video relighting requires balancing long-form temporal consistency with a physically grounded understanding of light transport, which depends on accurat

Persistent Multiscale Density-based Clustering

model-releasesarxiv-cs-lg

arXiv:2512.16558v3 Announce Type: replace Abstract: Clustering is a cornerstone of modern data analysis. Detecting clusters in exploratory data analyses (EDA) requires algorithms that make few assumpt

Industry

Real-time dental image verification with Amazon SageMaker AI at Henry Schein One

This post describes how Henry Schein One closed that gap by building Image Verify, an AI-powered quality verification system on Amazon SageMaker AI that evaluates dental X-ray quality at the point of

industryaws-ml-blog

Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles

arXiv:2607.08373v1 Announce Type: cross Abstract: Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from norm

SPHINX: First Explain, Then Explore

arXiv:2606.17482v2 Announce Type: replace Abstract: Generating adversarial driving scenarios is critical for evaluating and improving autonomous vehicle decision-making systems in simulation. Recent a

safetyarxiv-cs-cv

Statistical inverse learning problems with random observations

arXiv:2312.15341v1 Announce Type: cross Abstract: We provide an overview of recent progress in statistical inverse problems with random experimental design, covering both linear and nonlinear inverse

researcharxiv-cs-lg

The Download: Claude’s inner workings and OpenAI’s “super app”

model-releasesmit-tech-review

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Anthropic found a hidden space where Claude puzzles over conce

Validating LLMs in social science: Epistemic threats and emerging norms

arXiv:2607.07915v1 Announce Type: cross Abstract: Large language models (LLMs) are reshaping social science methodology. Researchers increasingly prompt language models to generate quantitative measur

safetyarxiv-cs-cl

VectorizationLLM: Smart Vectorization Based AI Assistant

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

tutorialsarxiv-cs-ai

VocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval

arXiv:2607.08541v1 Announce Type: cross Abstract: Open-vocabulary object detection and segmentation aim to recognize arbitrary objects beyond predefined categories. Although recent vision-language and

a self-improving agent is a software factory pointed at itself

A self-improving agent is conceptualized as a software factory—a system capable of generating and modifying code—that is directed toward improving its own codebase and capabilities. This framing sugge

agentsyohei-nakajima--x

Adversarial Rademacher Complexity of Deep Neural Networks

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

tutorialsarxiv-cs-lg

Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels

arXiv:2601.06135v3 Announce Type: replace-cross Abstract: Spatial computation in geographic systems increasingly requires query-conditioned, local, interpretable aggregation under metric constraints.

Distributed Dynamic Associative Memory via Online Convex Optimization

arXiv:2511.23347v2 Announce Type: replace Abstract: An associative memory (AM) enables cue-response recall, and it has recently been recognized as a key mechanism underlying modern neural architecture

agentsarxiv-cs-lg

Explain Before You Answer: A Survey on Compositional Visual Reasoning

arXiv:2508.17298v3 Announce Type: replace-cross Abstract: Compositional visual reasoning has emerged as a key research frontier in multimodal AI, aiming to endow machines with the human-like ability t

FedCVESA: Taking Away Training Data in Federated Learning via Correlation Value Encoding and Segmented Aggregation

arXiv:2607.07314v1 Announce Type: cross Abstract: Federated learning (FL) avoids explicit data exposure by keeping raw data on local clients, yet privacy risks remain in the training process and the l

LLM-powered reasoning in agent-based modeling

arXiv:2607.06757v1 Announce Type: new Abstract: Agent-based modeling (ABM) has the capability to model millions of individuals and their interactions, which is useful for policy making. However, ABMs

MMDiff: Extending Diffusion Transformers for Multi-Modal Generation

arXiv:2606.16673v2 Announce Type: replace Abstract: Diffusion transformers have demonstrated remarkable generative capabilities, yet the rich perceptual representations computed across their denoising

Network Dynamics-Based Framework for Understanding Deep Neural Networks

arXiv:2501.02436v5 Announce Type: replace Abstract: Advancements in artificial intelligence call for a deeper understanding of the fundamental mechanisms underlying deep learning. In this work, we pro

researcharxiv-cs-lg

On the Principles of Deep Feedforward ReLU Networks

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

tutorialsarxiv-cs-ai

PB-OEL: A Performance-Bounded Online Ensemble Learning Framework With Mixed Feedback for Real-Time Safety Assessment

arXiv:2503.15581v2 Announce Type: replace Abstract: Real-time safety assessment is critical for ensuring the reliable operation of complex dynamic systems. However, obtaining full safety labels in rea

safetyarxiv-cs-lg

Towards Understanding Steering Strength

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

tutorialsarxiv-cs-cl