Search: “concepts”

Mythos, a security researcher or team, successfully exploited macOS security vulnerabilities in a five-day timeframe, demonstrating the relative speed at which determined actors can compromise Apple's

toolsboris-cherny--x

Neural Surrogate Forward Modelling For Electrocardiology Without Explicit Intracellular Conductivity Tensor

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DGX agent

arXiv:2605.13366v1 Announce Type: new Abstract: Accurate forward modelling is essential for non-invasive cardiac electrophysiology, particularly in atrial fibrillation, where electrical activation is

researcharxiv-cs-cv

14 May 2026

Tutorials

New course: Transformers in Practice. You'll get a practical view of how transformer-based LLMs work, so you can reason about their behavior…

New course: Transformers in Practice. You'll get a practical view of how transformer-based LLMs work, so you can reason about their behavior, diagnose problems like slow inference, and make smarter de

tutorialsandrew-ng--x

Phasor Memory Networks: Stable Backpropagation Through Time for Scalable Explicit Memory

arXiv:2605.13370v1 Announce Type: new Abstract: For over a decade, explicit memory architectures like the Neural Turing Machine have remained theoretically appealing yet practically intractable for la

Revealing Interpretable Failure Modes of VLMs

arXiv:2605.12674v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly used in safety-critical applications because of their broad reasoning capabilities and ability to general

Runtime Monitoring of Perception-Based Autonomous Systems via Embedding Temporal Logic

arXiv:2605.12651v1 Announce Type: new Abstract: Runtime monitoring of autonomous systems traditionally relies on mapping continuous sensor observations to discrete logical propositions defined over lo

safetyarxiv-cs-lg

Agents

Semantic knowledge guides innovation and drives cultural evolution

arXiv:2510.12837v3 Announce Type: replace-cross Abstract: Cultural evolution allows ideas and technologies to accumulate across generations, reaching their most complex and open-ended form in humans.

agentsarxiv-cs-ai

SynCABEL: Synthetic Contextualized Augmentation for Biomedical Entity Linking

arXiv:2601.19667v2 Announce Type: replace-cross Abstract: We present SynCABEL (Synthetic Contextualized Augmentation for Biomedical Entity Linking), a framework that addresses a central bottleneck in

Unweighted ranking for value-based decision making with uncertainty

arXiv:2605.13601v1 Announce Type: new Abstract: As intelligent systems are increasingly implemented in our society to make autonomous decisions, their commitment to human values raises serious concern

A Composite Activation Function for Learning Stable Binary Representations

arXiv:2605.11558v1 Announce Type: new Abstract: Activation functions play a central role in neural networks by shaping internal representations. Recently, learning binary activation representations ha

researcharxiv-cs-lg

ASD-Bench: A Four-Axis Comprehensive Benchmark of AI Models for Autism Spectrum Disorder

arXiv:2605.11091v1 Announce Type: new Abstract: Automated ASD screening tools remain limited by single-architecture evaluations, axis-restricted assessment, and near-exclusive focus on adult cohorts,

Beyond Prediction: Interval Neural Networks for Uncertainty-Aware System Identification

arXiv:2605.11460v1 Announce Type: new Abstract: System identification (SysID) is critical for modeling dynamical systems from experimental data, yet traditional approaches often fail to capture nonlin

Cooperative Robotics Reinforced by Collective Perception for Traffic Moderation

arXiv:2605.11972v1 Announce Type: new Abstract: Collisions at non-line-of-sight (NLOS) intersections remain a major safety concern because drivers have limited visibility of approaching traffic. V2X b

safetyarxiv-cs-ro

Agents

Encore: Conditioning Trajectory Forecasting via Biased Ego Rehearsals

arXiv:2605.11463v1 Announce Type: new Abstract: Learning and representing the subjectivities of agents has become a challenging but crucial problem in the trajectory prediction task. Such subjectiviti

agentsarxiv-cs-cv

Local Ai

FAME: Feature Activation Map Explanation on Image Classification and Face Recognition

arXiv:2605.12017v1 Announce Type: new Abstract: Deep Learning has revolutionized machine learning, reaching unprecedented levels of accuracy, but at the cost of reduced interpretability. Especially in

local-aiarxiv-cs-cv

Tools

increasing levels of autonomy: /skill: preset prompts /plan: human-refined inputs /goal: AI-evaluated outputs

This post outlines a framework for progressively automating AI workflows through three levels of increasing autonomy: using preset prompts for consistency, refining inputs with human judgment to impro

toolsswyx--x

MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering

arXiv:2605.12361v1 Announce Type: new Abstract: Evaluating large language models (LLMs) in the biomedical domain requires benchmarks that can distinguish reasoning from pattern matching and remain dis

Applications

Model-Level GNN Explanations via Rule-to-Graph Readout for Logit Reconstruction

arXiv:2503.09051v2 Announce Type: replace Abstract: We propose a novel model-level GNN explanation framework that shifts the explanation target from class-wise rule extraction to rule-based logit reco

applicationsarxiv-cs-lg

Tutorials

Online Continual Learning with Dynamic Label Hierarchies

arXiv:2605.11742v1 Announce Type: new Abstract: Online Continual Learning (OCL) aims to learn from endless nonext{-}stationary data streams, yet most existing methods assume a flat label space and ove

tutorialsarxiv-cs-lg

Overview of the MedHopQA track at BioCreative IX: track description, participation and evaluation of systems for multi-hop medical question answering

arXiv:2605.12313v1 Announce Type: new Abstract: Multi-hop question answering (QA) remains a significant challenge in the biomedical domain, requiring systems to integrate information across multiple s

PresentAgent-2: Towards Generalist Multimodal Presentation Agents

arXiv:2605.11363v1 Announce Type: cross Abstract: Presentation generation is moving beyond static slide creation toward end-to-end presentation video generation with research grounding, multimodal med

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

arXiv:2605.11887v1 Announce Type: new Abstract: Large language models have achieved remarkable capabilities across diverse tasks, yet their internal decision-making processes remain largely opaque, li

Agents

RoboBlockly Studio: Conversational Block Programming with Embodied Robot Feedback for Computational Thinking

arXiv:2605.12059v1 Announce Type: cross Abstract: Computational thinking (CT) is increasingly promoted as a core literacy, yet learners and teachers face challenges in connecting abstract program logi

agentsarxiv-cs-ro

Robustness Certificates for Neural Networks against Adversarial Attacks

arXiv:2512.20865v2 Announce Type: replace Abstract: The increasing use of machine learning in safety-critical domains amplifies the risk of adversarial threats, especially data poisoning attacks that

safetyarxiv-cs-lg

STAGE: Tackling Semantic Drift in Multimodal Federated Graph Learning

arXiv:2605.11919v1 Announce Type: new Abstract: Federated graph learning (FGL) enables collaborative training on graph data across multiple clients. As graph data increasingly contain multimodal node

Stationary MMD Points

arXiv:2505.20754v3 Announce Type: replace-cross Abstract: Approximation of a target probability distribution using a finite set of points is a problem of fundamental importance in numerical integratio

researcharxiv-cs-lg

The power of LLMs on your data, more than two orders of magnitude faster and cheaper

model-releasesgoogle-cloud-ai

Databases have introduced new AI-powered SQL functions which take natural language instructions as input and are evaluated using LLMs. They leverage the power of LLMs to answer new kinds of queries: W

What Does It Mean for a Medical AI System to Be Right?

model-releasesarxiv-cs-cv

arXiv:2605.11963v1 Announce Type: new Abstract: This paper examines what it means for a medical AI system to be right by grounding the question in a specific clinical context: the automatic classifica

World Action Models: The Next Frontier in Embodied AI

arXiv:2605.12090v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have achieved strong semantic generalization for embodied policy learning, yet they learn reactive observation-to-

safetyarxiv-cs-cl

WorldComp2D: Spatio-semantic Representations of Object Identity and Location from Local Views

arXiv:2605.11743v1 Announce Type: new Abstract: Learning latent representations that capture both semantic and spatial information is central to efficient spatio-semantic reasoning. However, many exis

A Single Neuron Is Sufficient to Bypass Safety Alignment in Large Language Models

arXiv:2605.08513v1 Announce Type: cross Abstract: Safety alignment in language models operates through two mechanistically distinct systems: refusal neurons that gate whether harmful knowledge is expr

Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge

arXiv:2605.10370v1 Announce Type: new Abstract: Scientific knowledge on the Web is published as passive assertions and cannot decide when to validate evidence, reconcile contradictions, or update conf

BEA-GS: BEyond RAdiance Supervision in 3DGS for Precise Object Extraction

arXiv:2605.09662v1 Announce Type: new Abstract: Most Gaussian Splatting techniques that provide a 3D semantic representation of the scene do not optimize the underlying 3D geometry, making object-leve

Applications

Behavior-Centric Extraction of Scenarios from Highway Traffic Data and their Domain-Knowledge-Guided Clustering using CVQ-VAE

arXiv:2603.16964v2 Announce Type: replace Abstract: Approval of ADS depends on evaluating its behavior within representative real-world traffic scenarios. A common way to obtain such scenarios is to e

applicationsarxiv-cs-cv

Can You Keep a Secret? Involuntary Information Leakage in Language Model Writing

arXiv:2605.10794v1 Announce Type: cross Abstract: Language models are deployed in settings that require compartmentalization: system prompts should not be disclosed, chain-of-thought reasoning is hidd

CLEF: EEG Foundation Model for Learning Clinical Semantics

arXiv:2605.10817v1 Announce Type: new Abstract: Clinical EEG interpretation requires reasoning over full EEG sessions and integrating signal patterns with clinical context. Existing EEG foundation mod

CodeClinic: Evaluating Automation of Coding Skills for Clinical Reasoning Agents

arXiv:2605.09675v1 Announce Type: new Abstract: Clinical reasoning agents based on large language models (LLMs) aim to automate tasks such as intensive care unit (ICU) monitoring and patient state tra

Applications

Count Anything at Any Granularity

arXiv:2605.10887v1 Announce Type: new Abstract: Open-world object counting remains brittle: despite rapid advances in vision-language models (VLMs), reliably counting the objects a user intends is far

applicationsarxiv-cs-cv

Deep Dreams Are Made of This: Visualizing Monosemantic Features in Diffusion Models

arXiv:2605.08218v1 Announce Type: cross Abstract: This paper proposes latent visualization by optimization (LVO), a mechanistic interpretability technique that extends feature visualization by optimiz

Diffusion Models are Evolutionary Algorithms

arXiv:2410.02543v3 Announce Type: replace-cross Abstract: In a convergence of machine learning and biology, we reveal that diffusion models are evolutionary algorithms. By considering evolution as a d

Explaining Graph Neural Networks for Node Similarity on Graphs

arXiv:2407.07639v2 Announce Type: replace-cross Abstract: Similarity search is a fundamental task for exploiting information in various applications dealing with graph data, such as citation networks

Exploring the AI Obedience: Why is Generating a Pure Color Image Harder than CyberPunk?

arXiv:2603.00166v2 Announce Type: replace-cross Abstract: Recent advances in generative AI have shown human-level performance in complex content creation. However, we identify a 'Paradox of Simplicity

Local Ai

fmxcoders: Factorized Masked Crosscoders for Cross-Layer Feature Discovery

arXiv:2605.09438v1 Announce Type: new Abstract: Many features in pretrained Transformers span multiple layers: they emerge through stages of inference, persist in the residual stream, or are built joi

local-aiarxiv-cs-lg

Functional Subspace, where language models can use vector algebra to solve problems

arXiv:2602.01687v2 Announce Type: replace-cross Abstract: Large language models (LLMs) were invented for natural language tasks such as translation, but they have proved that they can perform highly c

Generative Giants, Retrieval Weaklings: Why do Multimodal Large Language Models Fail at Multimodal Retrieval?

arXiv:2512.19115v2 Announce Type: replace Abstract: Despite the remarkable success of multimodal large language models (MLLMs) in generative tasks, we observe that they exhibit a counterintuitive defi

GUARD: Guideline Upholding Test through Adaptive Role-play and Jailbreak Diagnostics for LLMs

arXiv:2508.20325v3 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) become increasingly integral to various domains, their potential to generate harmful responses has prompted si

In-Context Fixation: When Demonstrated Labels Override Semantics in Few-Shot Classification

arXiv:2605.08295v1 Announce Type: cross Abstract: While random demonstration labels barely hurt in-context learning (Min et al., 2022), we show that homogeneous labels--even semantically valid ones--c

Interpretable Coreference Resolution Evaluation Using Explicit Semantics

arXiv:2605.10627v1 Announce Type: cross Abstract: Coreference resolution is typically evaluated using aggregate statistical metrics such as CoNLL-F1, which measure structural overlap between predicted