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What is sample-based quantum diagonalization?

Sample-based quantum diagonalization is a quantum algorithm technique that estimates the eigenvalues and eigenvectors of matrices using measurements from quantum hardware, rather than requiring full q

researchibm-research

6 May 2026

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Where Paths Split: Localized, Calibrated Control of Moral Reasoning in Large Language Models

DGX agent

arXiv:2605.03609v1 Announce Type: cross Abstract: Large language models often display heterogeneous moral preferences across settings. We study inference-time steering toward a desired ethical framewo

researcharxiv-cs-lg

6 May 2026

Wiki-Builder on Hacker News front page! Exciting! New updates coming soon with a cool way for everyone to build their LLM Wikis. Go check it…

Wiki-Builder, a tool for creating LLM-powered wikis, was featured on Hacker News' front page, announced by DAIR.AI. The post indicates upcoming updates and improvements to make wiki creation more acce

researchdair-ai--x

6 May 2026

1BT: One-Block Transformer for EEG-Based Cognitive Workload Assessment

arXiv:2605.00856v1 Announce Type: cross Abstract: Accurate and continuous estimation of cognitive workload is fundamental to creating adaptive human-machine systems. However, designing architectures t

2D-ThermAl: Physics-Informed Framework for Thermal Analysis of Circuits using Generative AI

arXiv:2512.01163v2 Announce Type: replace Abstract: Thermal analysis is increasingly critical in modern integrated circuits, where non-uniform power dissipation and high transistor densities can cause

A blueprint for using AI to strengthen democracy

Every few centuries, changes in how information moves reshape how societies govern themselves. The printing press spread vernacular literacy, helping give rise to the Reformation and, eventually, repr

researchmit-tech-review

A Category-Theoretic Analysis of Conformal Prediction

arXiv:2507.04441v4 Announce Type: replace-cross Abstract: Conformal prediction (CP) produces prediction regions with finite-sample, distribution free coverage guarantees, but its interpretation as a q

A Coupled Fourth Order Telegraph Diffusion Framework Using Grayscale Indicators for Image Despeckling

arXiv:2605.00881v1 Announce Type: cross Abstract: Speckle noise severely limits the quality of images acquired from coherent imaging systems such as Synthetic Aperture Radar (SAR) and medical ultrasou

A dimensional R2 regression metric

arXiv:2605.01066v1 Announce Type: new Abstract: R2 score is the standard metric for evaluating regression tasks, offering a normalized magnitude-agnostic measure of accuracy that captures variance. Ho

A framework for analyzing concept representations in neural models

arXiv:2605.01381v1 Announce Type: new Abstract: Understanding how neural models represent human-interpretable concepts is challenging. Prior work has explored linear concept subspaces from diverse per

A Hybrid Windkessel-Neural Approach for Improved Noninvasive Blood Pressure Monitoring

arXiv:2605.00858v1 Announce Type: cross Abstract: Owing to the recent advancements in wearable devices for health care, the importance of BP estimation without cuffs increases. Cuff technologies are i

A Meta Reinforcement Learning Approach to Goals-Based Wealth Management

arXiv:2605.02300v1 Announce Type: new Abstract: Applying concepts related to zero-shot meta-learning and pre-training of foundation models, we develop a meta reinforcement learning approach (denoted M

A Multimodal Dataset for Visually Grounded Ambiguity in Machine Translation

arXiv:2605.02035v1 Announce Type: new Abstract: Ambiguity resolution is a key challenge in multimodal machine translation (MMT), where models must genuinely leverage visual input to map an ambiguous e

A Near-optimal SQ Lower Bound for Smoothed Agnostic Learning of Boolean Halfspaces

arXiv:2605.02350v1 Announce Type: new Abstract: We study the complexity of smoothed agnostic learning of halfspaces on {pm 1}^n under the uniform distribution in the model of itet{KM25} where each inp

A Novel Preprocessing-Driven Approach to Remaining Useful Life (RUL) Prediction Using Temporal Convolutional Networks (TCN)

arXiv:2605.02507v1 Announce Type: new Abstract: Accurate prediction of Remaining Useful Life (RUL) in aero-engines is vital for predictive maintenance, improved operational reliability, and reduced li

A PAC-Bayesian Analysis of Channel-Induced Degradation in Edge Inference

arXiv:2601.10915v2 Announce Type: replace-cross Abstract: In the emerging paradigm of edge learning, neural networks (NNs) are partitioned across distributed edge devices that collaboratively perform

A Proof-of-Concept Study of Multitask Learning for Cranial Synthetic CT Generation Across Heterogeneous MRI Field Strengths

arXiv:2605.00923v1 Announce Type: cross Abstract: Accurate synthesis of computed tomography (CT) images from magnetic resonance imaging (MRI) is clinically valuable for cranial applications such as at

A Rational Account of Categorization Based on Information Theory

arXiv:2603.29895v2 Announce Type: replace-cross Abstract: We present a new theory of categorization based on an information-theoretic rational analysis. To evaluate this theory, we investigate how wel

A Review of the Receiver Operating Characteristic Curve and a Proof About the Area Beneath It

arXiv:2605.00926v1 Announce Type: new Abstract: The Receiver Operating Characteristic (ROC) curve of a binary classifier has often been utilized to measure the performance of the classifier. The area

A second-order method on the Stiefel manifold via Newtonnicode{x2013}Schulz

arXiv:2605.02838v1 Announce Type: cross Abstract: Retraction-free approaches offer attractive low-cost alternatives to Riemannian methods on the Stiefel manifold, but they are often first-order, which

A Semi-Supervised Kernel Two-Sample Test

arXiv:2605.01775v1 Announce Type: cross Abstract: We consider the problem of two-sample testing in a semi-supervised setting with abundant unlabeled covariate data. Standard two-sample tests neglect c

A skin-like conformal sensor for real-time shape mapping

arXiv:2605.01170v1 Announce Type: cross Abstract: Reliable real-time 3D shape sensing is essential for robust control and interpretation of deformable systems during motion. Existing vision-based appr

researcharxiv-cs-ro

A Systematic Exploration of Text Decomposition and Budget Distribution in Differentially Private Text Obfuscation

arXiv:2605.01065v1 Announce Type: new Abstract: The goal of differentially private text obfuscation is to obfuscate, or 'perturb', input texts with Differential Privacy (DP) guarantees, such that the

A Theory of Saddle Escape in Deep Nonlinear Networks

arXiv:2605.01288v1 Announce Type: new Abstract: In deep networks with small initialization, training exhibits long plateaus separated by sharp feature-acquisition transitions. Whereas shallow nonlinea

Ablation Study of Multimodal Perception, Language Grounding, and Control for Human-Robot Interaction in an Object Detection and Grasping Task

arXiv:2605.00963v1 Announce Type: new Abstract: This manuscript extends our previous multimodal human-robot interaction system by introducing a controlled ablation study of the three modules that most

researcharxiv-cs-ro

Act in Collusion: Distributed Multi-Target Backdoor Attacks in Federated Learning

arXiv:2411.03926v3 Announce Type: replace Abstract: Federated learning (FL) is widely used in Internet-of-Things (IoT) systems, but its distributed training process also exposes it to backdoor attacks

Act2See: Emergent Active Visual Perception for Video Reasoning

arXiv:2605.01657v1 Announce Type: new Abstract: Vision-Language Models (VLMs) typically rely on static initial frames for video reasoning, restricting their ability to incorporate essential dynamic in

ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control

arXiv:2510.18232v2 Announce Type: replace Abstract: Generating high-quality synthetic text under differential privacy (DP) is critical for training and evaluating language models without compromising

Active multiple matrix completion with adaptive confidence sets

arXiv:2605.02458v1 Announce Type: cross Abstract: In this work, we formulate a new multi-task active learning setting in which the learner's goal is to solve multiple matrix completion problems simult

Active Reasoning Vision-Language Models via Sequential Experimental Design

arXiv:2605.01345v1 Announce Type: new Abstract: Visual perception in modern Vision-Language Models (VLMs) is constrained by a fundamental perceptual bandwidth bottleneck: a broad field of view inevita

Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusion

arXiv:2605.02849v1 Announce Type: new Abstract: Diffusion models provide a powerful generative prior for perceptual reconstruction at ultra-low bitrates, but effective video compression requires contr

Adversarial Update-Based Federated Unlearning for Poisoned Model Recovery

arXiv:2605.02110v1 Announce Type: new Abstract: Federated learning (FL) is vulnerable to poisoning attacks, where malicious clients upload manipulated updates to degrade the performance of the global

AI Washing Inflates Expected Performance but Not Interaction Outcomes: An AI Placebo Study Using Fitts' Law

arXiv:2605.00582v1 Announce Type: cross Abstract: Expectations about the support of artificial intelligence (AI) may influence interaction outcomes similar to placebos. Such expectations may result fr

researcharxiv-cs-ai

Almost for Free: Crafting Adversarial Examples with Convolutional Image Filters

arXiv:2605.01098v1 Announce Type: cross Abstract: Adversarial examples in machine learning are typically generated using gradients, obtained either directly through access to the model or approximated

An Adaptive Spatiotemporal Clustering Framework for 3D Ocean Subsurface Temperature Reconstruction

arXiv:2605.00860v1 Announce Type: cross Abstract: The reconstruction of ocean subsurface temperature (OST) using satellite remote sensing data holds significant scientific value for advancing the unde

An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications

arXiv:2605.00870v1 Announce Type: cross Abstract: Wearable devices running Human Activity Recognition(HAR) on Inertial Measurement Units~(IMUs) waste energy by performing continuous classification for

Anomaly Detection from a Tensor Train Perspective

arXiv:2409.15030v2 Announce Type: replace Abstract: We present a series of algorithms in tensor networks for anomaly detection in datasets, by using data compression in a Tensor Train representation.

Anon: Extrapolating Optimizer Adaptivity Across the Real Spectrum

arXiv:2605.02317v1 Announce Type: cross Abstract: Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However,

AoI-Aware Multi-Robot Sensing and Transport on Connected Graphs

arXiv:2605.02107v1 Announce Type: new Abstract: A team of mobile robots monitors spatially distributed processes and delivers measurements to a base, where AoI is measured from sensing start, capturin

researcharxiv-cs-ro

Application Research of a Deep Learning Model Integrating CycleGAN and YOLO in PCB Infrared Defect Detection

arXiv:2601.00237v2 Announce Type: replace Abstract: This paper addresses the critical bottleneck of infrared (IR) data scarcity in Printed Circuit Board (PCB) defect detection by proposing a cross-mod

Argumentation for Explainable and Globally Contestable Decision Support with LLMs

arXiv:2603.14643v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit strong general capabilities, but their deployment in high-stakes domains is hindered by their opacity and

ATLAS: Article Tracking, Linking, and Analysis of Swedish Encyclopedias

arXiv:2605.02466v1 Announce Type: new Abstract: The digitization of old encyclopedias represents an important step to improve access to historically structured knowledge. Often, however, this process

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse

arXiv:2602.01203v2 Announce Type: replace Abstract: Large Language Models (LLMs) often assign disproportionate attention to the first token, a phenomenon known as the attention sink. Several recent ap

Automated In-the-Wild Data Collection for Continual AI Generated Image Detection

arXiv:2605.02567v1 Announce Type: new Abstract: The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existi

Automatic Correction of Writing Anomalies in Hausa Texts

arXiv:2506.03820v2 Announce Type: replace Abstract: Hausa texts are often characterized by writing anomalies, such as incorrect character substitutions and spacing errors, which sometimes hinder natur

BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron

arXiv:2602.07200v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) are energy-efficient counterparts of Deep Neural Networks (DNNs) with high biological plausibility, as informat

researcharxiv-cs-ai

Balalaika: Data-Centric, Prosody-Aware Annotation Pipeline for Russian Speech

arXiv:2507.13563v2 Announce Type: replace Abstract: We introduce Balalaika, an open-source, data-centric pipeline for processing audio and producing prosody-aware annotations. It combines semantic VAD

BaldWhisper: Faster Whisper with Head Shearing and Layer Merging

arXiv:2510.08599v2 Announce Type: replace-cross Abstract: Pruning large pre-trained transformers in a data-scarce scenario is challenging, as it often requires massive retraining data to recover perfo