Search: “automated”

MedSAE: Dissecting MedCLIP Representations with Sparse Autoencoders

arXiv:2510.26411v2 Announce Type: replace Abstract: Artificial intelligence in healthcare requires models that are accurate and interpretable. We advance mechanistic interpretability in medical vision

applicationsarxiv-cs-ai

25 May 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

NeuroWeaver: An Autonomous Evolutionary Agent for Exploring the Programmatic Space of EEG Analysis Pipelines

DGX agent

arXiv:2602.13473v2 Announce Type: replace Abstract: Although foundation models have demonstrated remarkable success in general domains, the application of these models to electroencephalography (EEG)

agentsarxiv-cs-ai

25 May 2026

Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems

arXiv:2605.23297v1 Announce Type: new Abstract: AI-enabled services deployed in critical digital infrastructure are subject to governance obligations spanning transparency, accountability, fairness, a

25 May 2026

USIM and U0: A Vision-Language-Action Dataset and Model for General Underwater Robots

arXiv:2510.07869v4 Announce Type: replace Abstract: Underwater environments pose unique challenges for robotic navigation and manipulation. While existing research has primarily focused on task-specif

researcharxiv-cs-ro

25 May 2026

A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction

arXiv:2605.21528v1 Announce Type: new Abstract: Accurate and reproducible disease risk prediction remains challenging due to heterogeneous features, limited samples, and severe class imbalance. This s

applicationsarxiv-cs-lg

AutoBaxBuilder: Bootstrapping Code Security Benchmarking

model-releasesarxiv-cs-lg

arXiv:2512.21132v2 Announce Type: replace-cross Abstract: As large language models (LLMs) see wide adoption in software engineering, the reliable assessment of the correctness and security of LLM-gene

Hardware

AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems

arXiv:2605.21560v1 Announce Type: new Abstract: Deploying neural networks on microcontroller units (MCUs) is critical for edge intelligence but remains challenging due to tight memory, storage, and co

hardwarearxiv-cs-lg

MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data

arXiv:2605.22775v1 Announce Type: new Abstract: Real-time cognitive load assessment from eye-tracking signals could potentially enable adaptive human-centered-AI such as safety-critical applications s

safetyarxiv-cs-lg

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices

arXiv:2605.22097v1 Announce Type: cross Abstract: Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challen

AgentCo-op: Retrieval-Based Synthesis of Interoperable Multi-Agent Workflows

arXiv:2605.20425v1 Announce Type: new Abstract: Designing multi-agent workflows is especially difficult in open-ended scientific settings where tasks lack curated training sets, reliable scalar evalua

An Open Multi-Center Whole-Body FDG PET/CT Foundation Model for Tumor Segmentation

arXiv:2605.21835v1 Announce Type: cross Abstract: The synergistic interpretation of anatomical information from computed tomography (CT) and metabolic information from positron emission tomography (PE

researcharxiv-cs-cv

Audience Engagement with Arabic Women's Social Empowerment and Wellbeing: A Decadal Corpus

arXiv:2605.22204v1 Announce Type: new Abstract: This paper presents the Arabic Women and Society Corpus, a ten year collection of 252,487 public Arabic Facebook posts related to women's empowerment an

COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decomposition

arXiv:2605.22068v1 Announce Type: new Abstract: We formalize and enable the task of open tree decomposition, which segments an image into hierarchical trees of visual components with unconstrained gra

Agents

Enabling Regulatory Multi-Agent Collaboration: Architecture, Challenges, and Solutions

arXiv:2509.09215v2 Announce Type: replace Abstract: Large language models (LLMs)-empowered autonomous agents are transforming both digital and physical environments by enabling adaptive, multi-agent c

agentsarxiv-cs-ai

Agents

Evaluating multimodal emotion recognition in proactive conversational agents: A user study

arXiv:2605.20200v1 Announce Type: cross Abstract: This article presents a multimodal emotion recognition module integrated into a proactive Socially Interactive Agent (SIA) powered by generative artif

agentsarxiv-cs-ai

HyperBench: Standardizing and Scaling Synthetic Evaluation for Hyperspectral Super-Resolution

arXiv:2605.21671v1 Announce Type: cross Abstract: Hyperspectral super-resolution (HSR) reconstructs a high-spatial-resolution hyperspectral image by fusing a low-resolution hyperspectral image (LR-HSI

applicationsarxiv-cs-cv

LLM Readiness Harness: Evaluation, Observability, and CI Gates for LLM/RAG Applications

arXiv:2603.27355v2 Announce Type: replace-cross Abstract: We present a readiness harness for LLM and RAG applications that turns evaluation into a deployment decision workflow. The system combines aut

Moral Semantics Survive Machine Translation: Cross-Lingual Evidence from Moral Foundations Corpora

arXiv:2605.22660v1 Announce Type: new Abstract: Moral language is subtle and culturally variable, making it difficult to translate faithfully across languages. Idiomatic expressions, slang, and cultur

safetyarxiv-cs-cl

MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation

arXiv:2505.17123v3 Announce Type: replace Abstract: Recent advances in Large Language Models (LLMs) have shown promising results in complex reasoning tasks. However, current evaluations predominantly

Open-World Evaluations for Measuring Frontier AI Capabilities

arXiv:2605.20520v1 Announce Type: new Abstract: Benchmark-based evaluation remains important for tracking frontier AI progress. But it can both overstate and understate deployed capability because it

Reflective Prompt Tuning through Language Model Function-Calling

arXiv:2605.21781v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly capable of following instructions and complex reasoning, making prompting a flexible interface for

SFN-YOLO: Towards Free-Range Poultry Detection via Scale-aware Fusion Networks

arXiv:2509.17086v2 Announce Type: replace Abstract: Detecting and localizing poultry is essential for advancing smart poultry farming. Despite the progress of detection-centric methods, challenges per

SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure

arXiv:2605.21198v1 Announce Type: cross Abstract: Public events on social media generate large volumes of discussion whose collective dynamics carry direct value for opinion forecasting and crisis res

Synthetic Data Alone is Enough? Rethinking Data Scarcity in Pediatric Rare Disease Recognition

arXiv:2605.22767v1 Announce Type: new Abstract: Children with rare genetic diseases often exhibit distinctive facial phenotypes, yet developing computer vision systems for early diagnosis remains chal

applicationsarxiv-cs-cv

VDE Bench: Evaluating The Capability of Image Editing Models to Modify Visual Documents

arXiv:2602.00122v2 Announce Type: replace Abstract: In recent years, image editing models have made significant progress, enabling users to manipulate visual content in a flexible and interactive mann

A Comprehensive Comparison of Deep Learning Architectures for COVID-19 Classification on CT & X-ray Imagery

arXiv:2605.20445v1 Announce Type: new Abstract: COVID-19 was a significant challenge that led to the loss of numerous lives daily. Not only a certain country was involved in this outbreak, but even th

researcharxiv-cs-cv

AI-Assisted Competency Assessment from Egocentric Video in Simulation-Based Nursing Education

arXiv:2605.20233v1 Announce Type: new Abstract: Assessing learner competency in clinical simulation requires expert observation that is time-intensive, difficult to scale, and subject to inter-rater v

safetyarxiv-cs-cv

ArPoMeme: An Annotated Arabic Multimodal Dataset for Political Ideology and Polarization

arXiv:2605.20967v1 Announce Type: new Abstract: Memes have become a prominent medium of political communication in the Arab world, reflecting how humor, imagery, and text interact to express ideologic

researcharxiv-cs-cl

Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users

arXiv:2605.20198v1 Announce Type: cross Abstract: Augmented analytics has transformed how business intelligence (BI) systems support managerial decision-making. This is especially true for users witho

Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

arXiv:2602.06500v2 Announce Type: replace Abstract: Scaling inference methods such as Markov chain Monte Carlo to high-dimensional models remains a central challenge in Bayesian deep learning. A promi

safetyarxiv-cs-lg

Agents

Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training

arXiv:2605.21372v1 Announce Type: new Abstract: Data scaling is fundamental to modern deep learning, and grows increasingly critical as autonomous driving shifts to end-to-end learning. Real-world dri

agentsarxiv-cs-cv

CoarseSoundNet: Building a reliable model for ecological soundscape analysis

arXiv:2605.21143v1 Announce Type: cross Abstract: A soundscape is composed of three types of sound: biophony (sounds made by animals), geophony (natural abiotic sounds) and anthropophony (sounds made

applicationsarxiv-cs-lg

DASH: Fast Differentiable Architecture Search for Hybrid Attention in Minutes on a Single GPU

arXiv:2605.20936v1 Announce Type: cross Abstract: Hybrid attention architectures are becoming an increasingly important paradigm for improving LLM inference efficiency while preserving model quality,

Epistemic Uncertainty Quantification for Pre-trained VLMs via Riemannian Flow Matching

arXiv:2601.21662v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) are typically deterministic in nature and lack intrinsic mechanisms to quantify epistemic uncertainty, which reflects

EvalMORAAL: Interpretable Chain-of-Thought and LLM-as-Judge Evaluation for Moral Alignment in Large Language Models

arXiv:2510.05942v3 Announce Type: replace Abstract: We present EvalMORAAL, a transparent chain-of-thought (CoT) framework that uses two scoring methods (log-probabilities and direct ratings) plus a mo

safetyarxiv-cs-cl

Genetic Programming with Transformer-Based Mutation for Approximate Circuit Design

arXiv:2605.21055v1 Announce Type: cross Abstract: A recent trend is to leverage machine learning models to improve the evolutionary design and optimization process. We propose a novel transformer-base

Hack-Verifiable Environments: Towards Evaluating Reward Hacking at Scale

model-releasesarxiv-cs-lg

arXiv:2605.20744v1 Announce Type: new Abstract: Aligning autonomous agents with human intent remains a central challenge in modern AI. A key manifestation of this challenge is reward hacking, whereby

LASH: Adaptive Semantic Hybridization for Black-Box Jailbreaking of Large Language Models

arXiv:2605.21362v1 Announce Type: new Abstract: Jailbreak attacks expose a persistent gap between the intended safety behavior of aligned large language models and their behavior under adversarial pro

safetyarxiv-cs-cl

Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning

arXiv:2605.21160v1 Announce Type: new Abstract: The discovery of first integrals is of fundamental scientific importance for understanding conservation laws in dynamical systems. However, existing sym

Leveraging LLMs for Grammar Adaptation: A Study on Metamodel-Grammar Co-Evolution

arXiv:2605.21465v1 Announce Type: new Abstract: In model-driven engineering, metamodel evolution leads to the need to adapt corresponding grammars to maintain consistency, which typically requires ted

MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks

arXiv:2605.20729v1 Announce Type: new Abstract: Accurate evaluation of conversational retrieval is pivotal for advancing Retrieval-Augmented Generation (RAG) systems. However, existing conversational

OpenSeisML: Open Large-Scale Real Seismic and well-log Dataset for Generative AI

arXiv:2605.20539v1 Announce Type: new Abstract: The advent of machine learning (ML) and computer vision has significantly accelerated seismic inversion workflows by reducing the computational cost of

QwenSafe: Multimodal Content Rating Description Identification via Preference-Aligned VLMs

arXiv:2605.20584v1 Announce Type: new Abstract: Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or res

SOPE: Stabilizing Off-Policy Evaluation for Online RL with Prior Data

model-releasesarxiv-cs-lg

arXiv:2605.05863v2 Announce Type: replace Abstract: Incorporating prior data into online reinforcement learning accelerates training but typically forces a difficult trade-off between high computation

SUGAR: A Scalable Human-Video-Driven Generalizable Humanoid Loco-Manipulation Learning Framework

arXiv:2605.20373v1 Announce Type: cross Abstract: Building humanoid robots capable of generalizable whole-body loco-manipulation in the real world remains a fundamental challenge. Existing methods eit

safetyarxiv-cs-cv

TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos

arXiv:2605.21443v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being explored for video game quality assurance, especially gameplay glitch detection. Most existing eval

Terminal-World: Scaling Terminal-Agent Environments via Agent Skills

arXiv:2605.20876v1 Announce Type: new Abstract: Terminal agents extend Large Language Models with the ability to execute tasks directly in command-line environments, but their progress is bottlenecked

TextSculptor: Training and Benchmarking Scene Text Editing

arXiv:2605.21090v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and diffusion-based generative models have substantially improved prompt-driven image editin