research

Automated Compliance Mapping in Cloud Security with Domain-Adapted Sentence Transformers

arXiv:2607.06364v1 Announce Type: new Abstract: Mapping cloud security controls to technical metrics is currently a manual process. This paper proposes domain adaptation of Sentence Transformer models

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Benign Overfitting with Quantum Kernels

DGX agent

arXiv:2503.17020v2 Announce Type: replace-cross Abstract: Kernel methods compare inputs through feature maps. Quantum kernels follow the same principle: input data are encoded into quantum states, whi

researcharxiv-cs-lg

8 Jul 2026

Binocular Gaze Estimation with Single Camera and Single Light Source

arXiv:2607.05473v1 Announce Type: cross Abstract: According to commonly consented theories, the minimum hardware requirement for gaze tracker is one camera and two light sources to realize gaze estima

BitFair: A 12nm Bit-Serial CNN Accelerator with Learnable Early Termination and Adaptive Bit Ordering for Ultra-Low-Power XR Vision

arXiv:2607.05445v1 Announce Type: cross Abstract: Extended Reality (XR) wearables require always-on perception within tight power envelopes of a few watts and motion-to-photon latency budgets below 20

Black Hole Black Boxes: Numerical Black Hole Metrics via AInstein Neural Networks

arXiv:2607.05489v1 Announce Type: cross Abstract: The AInstein architecture introduced an unsupervised neural method for solving the Riemannian Einstein equations on arbitrary manifolds. This Physics

Boosting with List-Decodable Codes

arXiv:2607.05791v1 Announce Type: cross Abstract: Boosting is a fundamental technique for generically improving the accuracy of learning algorithms (Schapire 1989). Existing boosting algorithms constr

Breaking the Likelihood Trap: Variance-Calibrated Modulation for Large Language Model Decoding

arXiv:2606.22511v2 Announce Type: replace Abstract: In open-ended generation, LLMs frequently fall into the 'likelihood trap', marked by repetitive degeneration and vocabulary dullness, creating a dis

Broken Ergodicity and the Violation of the Fluctuation-Dissipation Theorem Lead to Generalization Beyond Overfitting in Machine Learning

arXiv:2607.04135v1 Announce Type: cross Abstract: The remarkable ability of modern neural networks to generalize improves with increasing network capacity, even when the number of model parameters or

Catalyst Papers in Artificial Intelligence Research: A Landscape on ICLR from 2017 to 2025

arXiv:2607.05401v1 Announce Type: cross Abstract: A small number of methodological contributions, including word2vec, the Transformer, large-scale pre-training, and reinforcement learning from human f

Channel-wise Retrieval for Multivariate Time Series Forecasting

arXiv:2604.05543v2 Announce Type: replace Abstract: Multivariate time series forecasting often struggles to capture long-range dependencies due to fixed lookback windows. Retrieval-augmented forecasti

Complementary Roles of Image Classification and Vessel Segmentation in AI-Based Screening for Retinopathy of Prematurity Plus Disease in a Kenyan Preterm Cohort

arXiv:2607.05825v1 Announce Type: cross Abstract: Background. Retinopathy of prematurity (ROP) is a preventable cause of childhood blindness, with rising burden in low- and middle-income countries whe

Contrastive Predictive Coding with Compression for Enhanced Channel State Feedback in Wireless Networks

arXiv:2607.05419v1 Announce Type: cross Abstract: Accurate and timely channel state information (CSI) is essential for next-generation wireless systems, yet existing works treat CSI compression and CS

Decision-Focused Scenario Generation and Selection for Efficient and Robust Grid Dispatch

arXiv:2607.05830v1 Announce Type: cross Abstract: The increasing uncertainty from flexible demand and renewable generation has made distributionally robust optimization (DRO) an important tool for rob

Decoupled Single-Mask Annotation Noise Detection via Cross-Sectional Patch Self-Consistency

arXiv:2607.05965v1 Announce Type: cross Abstract: Vascular computed tomography datasets are commonly annotated only once per scan, yielding the pervasive yet under addressed problem of single mask ann

Depression Symptoms and Relational Patterns in 187k ChatGPT Histories

arXiv:2607.05685v1 Announce Type: cross Abstract: Large language models are increasingly used as private, always-available conversational systems, but little is known about how people with depressive

Designing Maintainable Hybrid Generative Systems: A Quantum-Inspired Approach to Automated Music Harmony Generation

arXiv:2607.06296v1 Announce Type: cross Abstract: This paper presents the design and evaluation of a maintainable hybrid generative architecture for automated music harmony generation from melody. The

Determinantal point process sampling for bioacoustic active learning

arXiv:2607.06063v1 Announce Type: cross Abstract: Eco-acoustic monitoring generates vast volumes of audio data, making active learning a promising approach for reducing annotation effort while efficie

DexTele: A Dual-Arm Dexterous Teleoperation System Based on Motion Retargeting and Adaptive Force Control

arXiv:2607.05883v1 Announce Type: new Abstract: In dual-arm dexterous teleoperation, cross-platform generalization of motion retargeting and interactivity of grasping are crucial. However, the heterog

researcharxiv-cs-ro

Diffusion Language Model Parallel Decoding via Product-of-Experts Bridge

arXiv:2606.08048v1 Announce Type: cross Abstract: Diffusion language models (DLMs) offer substantial speed advantages through parallel decoding, but the lack of token dependencies limits generation qu

Dithered Gaussian Mechanism for Randomness-Efficient Differential Privacy

arXiv:2607.06320v1 Announce Type: cross Abstract: We present the dithered Gaussian mechanism, a novel alternative to the discrete Gaussian mechanism for differential privacy that discretizes the priva

Do It Right! A Methodology for Successful NLP System Development

arXiv:2607.05644v1 Announce Type: cross Abstract: Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electr

Dynamic Evaluation of Classical and Control-Aware Optimal Trajectory Planning in Robot Manipulators

arXiv:2607.05544v1 Announce Type: new Abstract: Trajectory planning strongly influences tracking accuracy, actuator demand, and overall execution behavior in robotic manipulators. Classical planners s

researcharxiv-cs-ro

Early Language Learning via Spreading Activation and Category Exploration in Complex Networks

arXiv:2607.06258v1 Announce Type: new Abstract: Is word acquisition in children uneven with respect to semantic and lexical categories? To answer this question, we model early language learning as a s

EcoVision: AI-Powered Drone Imaging for Salt Marsh Vegetation Monitoring and Dominance Mapping

arXiv:2607.06105v1 Announce Type: cross Abstract: High-resolution RGB imagery acquired from low-altitude UAV surveys was processed through a modular pipeline incorporating transformer-based semantic s

Efficient Transfer Learning of Robot Dynamic Models Using Morphological Similarity

arXiv:2607.05665v1 Announce Type: new Abstract: This study proposes a neural network-based transfer learning framework for modeling the dynamics of soft, fin-actuated underwater robots. We focus on mo

researcharxiv-cs-ro

EmTech AI 2026: The Rise of the AI Platform

The next generation of AI is evolving from a tool into a platform where models, applications, and human workflows converge to create integrated operating environments capable of automating tasks and e

researchmit-tech-review

EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning

arXiv:2607.06497v1 Announce Type: new Abstract: We introduce EntroPath, a manifold learning method that recovers geodesic geometry from data graphs through ensembles of diffusion paths. Many existing

EquiFiLM: Charge-Conditioned Equivariant Force Fields via Feature-wise Linear Modulation

arXiv:2607.05559v1 Announce Type: new Abstract: Foundation machine learning force fields (MLFFs) such as MACE-MP-0 and UMA cover broad chemical space at near density functional theory (DFT) accuracy.

Estimating Uncertainty from Reasoning: A Large-Scale Study of Multi- and Crosslingual MCQA Performance in LLMs

arXiv:2607.06327v1 Announce Type: cross Abstract: Uncertainty estimation (UE) enables LLM-powered systems to recognize when to abstain, yet existing research has predominantly focused on English. We p

Estimation of instrument and noise parameters for inverse problem based on prior diffusion model

arXiv:2602.11711v2 Announce Type: replace-cross Abstract: This article addresses the issue of estimating observation parameters (response and error parameters) in inverse problems. The focus is on cas

ExplAIner: A Declarative Query Language for Explaining Classification Models

arXiv:2607.06407v1 Announce Type: new Abstract: The XAI community has studied a wide range of queries and scores for explaining predictions of ML models. From a data management perspective, this proli

Few-Medoids: An Embarrassingly Simple Coreset Selection Method for Few-Shot Knowledge Distillation

arXiv:2607.05891v1 Announce Type: cross Abstract: Coreset selection aims to identify a small and highly representative subset of a massive dataset for efficient model training. The problem remains cha

FIELDS: Face reconstruction with accurate Inference of Expression using Learning with Direct Supervision

arXiv:2511.21245v3 Announce Type: replace Abstract: Monocular 3D face reconstruction estimates a 3D morphable model (3DMM) representation from a single image, providing geometry-aware expression codes

Flint: A visualization language for the AI era

researchmicrosoft-research

Short chart specifications are easy to write, but often produce uninspiring results. Flint is an open-source visualization language that offers a middle path, letting AI agents create expressive chart

From Global to Granular: Revealing IQA Model Performance via Correlation Surface

arXiv:2601.21738v2 Announce Type: replace-cross Abstract: Evaluation of Image Quality Assessment (IQA) models has long been dominated by global correlation metrics, such as Pearson Linear Correlation

From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Physical IoT Systems and Beyond

arXiv:2607.05563v1 Announce Type: new Abstract: Interpretable explanation methods in Artificial Intelligence aim to uncover the underlying causes and their effects, enabling a deeper understanding of

From RGB Generation to Dense Field Readout: Pixel-Space Dense Prediction with Text-to-Image Models

arXiv:2607.06553v1 Announce Type: new Abstract: Large-scale text-to-image models are attractive backbones for dense prediction because RGB generation pretraining learns rich semantic, structural, and

From Sinhala to Dhivehi: Cross-Lingual Transfer Learning for Low-Resource Speech Recognition

arXiv:2607.06289v1 Announce Type: new Abstract: Dhivehi, the national language of the Maldives, is currently under-resourced for automatic speech recognition (ASR) and other NLP tasks. This study inve

From Textural Counterpoint to Feature Encoding: A Multi-Dimensional Machine Representation Study of Haydn's 'The Lark' Integrating Electroacoustic Analysis

arXiv:2607.05902v1 Announce Type: cross Abstract: Chamber music, as a highly precise multi-part interactive system, contains a logic of 'role assignment and dynamic interaction' that provides an extre

FUSE: A Flow-based Mapping Between Shapes

arXiv:2511.13431v2 Announce Type: replace Abstract: We introduce a novel neural representation for maps between 3D shapes based on flow-matching models, which is computationally efficient and supports

GraphBU: MILP Instance Generation with Graph-Native Block Units

arXiv:2607.06532v1 Announce Type: new Abstract: Mixed-integer linear programming (MILP) instances used for solver development are hard to obtain when models come from private or application-specific p

Harrison.Rad 1.5 Technical Report: A radiology foundation model that can draft reports from images, priors and clinical context

arXiv:2607.05880v1 Announce Type: cross Abstract: Imaging demand is growing faster than the radiology workforce can expand, and reporting backlogs cannot be resolved through training and recruitment a

Hierarchical Classification via Cascading Feature Elimination: Application to Human Phenotype Ontology-Aligned Facial Phenotyping (FaceMesh2HPO)

arXiv:2607.05585v1 Announce Type: cross Abstract: FaceMesh2HPO is a framework for classifying facial phenotypic descriptors aligned with the Human Phenotype Ontology (HPO) to support clinical diagnosi

i-EXAM: Instructable and Explainable Attack Connectivity Graph Modeler

arXiv:2607.05888v1 Announce Type: cross Abstract: i-EXAM is a planning-powered tool that helps system administrators to create security profiles of complex networks and perform what-if analyses to ide

Implementing Metric Temporal Answer Set Programming

arXiv:2601.20735v2 Announce Type: replace Abstract: We develop a computational approach to Metric Answer Set Programming (ASP) to allow for expressing quantitative temporal constraints, like durations

Integrating GNSS-Derived Zenith Wet Delay into a Weather Foundation Model Improves Precipitation Forecasting

arXiv:2607.05658v1 Announce Type: cross Abstract: Global Navigation Satellite Systems (GNSS), best known for positioning, also serve weather science, as atmospheric water vapour delays their signals.

KaLM-Reranker-V1: Fast but Not Late Interaction for Compressed Document Reranking

arXiv:2606.22807v2 Announce Type: replace Abstract: As retrieval systems scale, high-quality reranking becomes increasingly important. However, most existing rerankers, whether encoder-based or decode

Kernel-based Operator Learning: Error Analysis, Budget Allocation, and a Physics-Informed Extension

arXiv:2607.06287v1 Announce Type: cross Abstract: We study kernel-based operator learning in a two-stage sampling framework, where an offline kernel regression operator learns a discretized representa