62 technical terms and definitions
XPS surface characterization thin films, chemical state oxidation XPS analysis, depth profiling sputtering XPS, semiconductor interface XPS metrology
X-ray Photoelectron Spectroscopy (XPS): Surface Characterization and Thin Film Analysis in Semiconductor Processing Introduction X-ray photoelectron spectroscopy (XPS), also known…
x-ray reflectivity, xrr measurement, thin film xrr, x-ray reflectometry semiconductor
X-ray reflectometry turns a grazing beam and a rapidly fading interference pattern into a depth model of a thin-film stack. The measurement is nondestructive and chemically…
ray, metrology, XRD, SAXS, semiconductor, analysis
Spectroscopic ellipsometry and inline optical wafer metrology constitute the non-destructive physical measurement and defect detection disciplines that govern yield control across…
time series models
X-13-ARIMA-SEATS is statistical seasonal-adjustment framework combining ARIMA modeling with decomposition procedures. - It is widely used for official economic time-series…
spc
X-bar and R chart is the paired variables control-chart method that tracks subgroup mean and within-subgroup range for small rational subgroups - it is a standard SPC approach…
spc
X-bar and S chart is the variables chart pair that monitors subgroup means and subgroup standard deviation for larger subgroup sizes - it provides more robust spread estimation…
computer vision
X-Decoder is a generalized decoding framework for pixel-level vision-language tasks — capable of reducing image segmentation, image captioning, and retrieval into a unified…
X-Learner for Highly Imbalanced Treatment Regimes Introduction & Motivation X-Learner for Highly Imbalanced Treatment Regimes addresses a central problem in causal inference…
design & verification
X-Masking is techniques that block or neutralize unknown logic values before they corrupt scan signatures or analysis outputs - It is a core method in advanced semiconductor…
design & verification
X-Propagation is the spread of unknown logic states through combinational and sequential paths during simulation and test analysis - It is a core method in advanced semiconductor…
xas, x-ray absorption fine structure, xafs, xas semiconductor, x-ray absorption metrology
X-ray absorption spectroscopy follows one selected element as incident X-ray energy is swept through a core-electron binding energy. The abrupt absorption edge and fine structure…
x-ray bga ball inspection drift prediction, x-ray bga ball, bga ball inspection, ball inspection drift, inspection drift prediction, x-ray bga, bga ball, ball inspection
X-Ray BGA Ball Inspection Drift Prediction with Machine Learning Introduction & Motivation X-Ray BGA Ball Inspection Drift Prediction with Machine Learning addresses a central…
x-ray ct void analysis drift prediction, x-ray ct void, ct void analysis, void analysis drift, analysis drift prediction, x-ray ct, ct void, void analysis, analysis drift
X-Ray CT Void Analysis Drift Prediction with Machine Learning Introduction & Motivation X-Ray CT Void Analysis Drift Prediction with Machine Learning addresses a central problem…
x-ray detector panel defect prediction, x-ray detector panel, detector panel defect, panel defect prediction, x-ray detector, detector panel, panel defect, defect prediction
X-Ray Detector Panel Defect Prediction with Machine Learning Introduction & Motivation X-Ray Detector Panel Defect Prediction with Machine Learning addresses a central problem…
x-ray diffraction crystal quality assessment, x-ray diffraction crystal, diffraction crystal quality, crystal quality assessment, x-ray diffraction, diffraction crystal
X-Ray Diffraction Crystal Quality Assessment with Machine Learning Introduction & Motivation X-Ray Diffraction Crystal Quality Assessment with Machine Learning addresses a central…
x-ray diffraction crystal quality assessment, x-ray diffraction crystal, diffraction crystal quality, crystal quality assessment, x-ray diffraction, diffraction crystal
X-Ray Diffraction Crystal Quality Assessment with Machine Learning Introduction & Motivation X-Ray Diffraction Crystal Quality Assessment with Machine Learning addresses a central…
x-ray diffraction strain mapping prediction, x-ray diffraction strain, diffraction strain mapping, strain mapping prediction, x-ray diffraction, diffraction strain
X-Ray Diffraction Strain Mapping Prediction with Machine Learning Introduction & Motivation X-Ray Diffraction Strain Mapping Prediction with Machine Learning addresses a central…
XRF mapping, micro-XRF mapping, x-ray fluorescence imaging, elemental mapping XRF, wafer XRF mapping, quantitative XRF microscopy
X-ray fluorescence mapping builds a spatially resolved elemental picture by rastering a focused or collimated excitation beam across a specimen and recording an energy spectrum…
x-ray inspection internal defect prediction, x-ray inspection internal, inspection internal defect, internal defect prediction, x-ray inspection, inspection internal
X-Ray Inspection Internal Defect Prediction with Machine Learning Introduction & Motivation X-Ray Inspection Internal Defect Prediction with Machine Learning addresses a central…
quality
X-ray inspection of solder is the non-destructive imaging method used to evaluate hidden solder joints and internal defects in assembled packages - it is indispensable for BGA…
x ray inspection solder joint classification prediction with machine learning, x ray inspection solder joint classification prediction machine learning, x ray
X-Ray Inspection Solder Joint Classification Prediction with Machine Learning Introduction & Motivation X-Ray Inspection Solder Joint Classification Prediction with Machine…
failure analysis advanced
X-Ray Laminography is an angled X-ray imaging technique that improves visibility of layered structures in packaged assemblies - It helps inspect hidden interconnects and solder…
x-ray photoelectron emission microscopy chemical mapping prediction, x-ray photoelectron emission, photoelectron emission microscopy
X-Ray Photoelectron Emission Microscopy Chemical Mapping Prediction with Machine Learning Introduction & Motivation X-Ray Photoelectron Emission Microscopy Chemical Mapping…
x-ray photoelectron spectroscopy, xps, xps analysis
Read XPS through a binding-energy and chemical-state lens rather than a survey or element-presence lens. This fundamental shift in perspective transforms how we interpret X-ray…
xpeem, photoemission electron microscopy, x-ray peem, xpeem semiconductor, chemical imaging peem, magnetic domain xpeem
X-ray photoemission electron microscopy turns a surface-sensitive electron-yield measurement into a full-field image. Tunable X-rays illuminate a field of view, a cathode lens…
x-ray reflectivity thin film density prediction, x-ray reflectivity thin, reflectivity thin film, thin film density, film density prediction, x-ray reflectivity
X-Ray Reflectivity Thin Film Density Prediction with Machine Learning Introduction & Motivation X-Ray Reflectivity Thin Film Density Prediction with Machine Learning addresses…
xrr, xrr thin film measurement, xrr thickness density roughness, specular x-ray reflectivity
X-ray reflectometry turns a grazing beam and a rapidly fading interference pattern into a depth model of a thin-film stack. The measurement is nondestructive and chemically…
CDSAXS, XRR reflectometry, GISAXS grazing incidence, synchrotron lab source, buried structure measurement, sub nanometer sensitivity, model robust metrology
X-ray scatterometry uses X-ray diffraction and scattering, rather than visible or near-visible light, to measure nanoscale semiconductor structure dimensions — and the entire…
failure analysis advanced
X-ray tomography is a three-dimensional imaging method that reconstructs internal package and board structures from multiple x-ray projections - Computed reconstruction combines…
design & verification
X-State Handling is test methodologies that control, mask, or bound unknown logic states during scan and compaction - It is a core technique in advanced digital implementation…
x3d, video understanding
X3D is the efficient video architecture family that expands a compact seed network along multiple dimensions such as depth, width, resolution, and frame rate to find strong…
Trust Calibration Metrics in Human-AI Interaction Introduction & Motivation Trust Calibration Metrics in Human-AI Interaction addresses a central problem in explainability…
x-ray absorption near-edge structure, xanes spectroscopy, xanes oxidation state, xanes semiconductor, xanes metrology
X-ray absorption near-edge structure is the strongly featured portion of an absorption spectrum around an element-specific core edge. A few tens of electronvolts can carry…
optimization
Weight initialization is the choice of what values a network's parameters hold *before* the first gradient step — and it is far less innocent than it sounds. Set the initial…
recommendation systems
xDeepFM is a recommendation architecture combining explicit and implicit high-order feature interactions. - It integrates compressed interaction networks with deep components…
xfib, failure analysis advanced
Semiconductor failure analysis (FA), non-destructive inspection, and advanced electrical fault isolation (EFI) constitute the essential metrological and diagnostic disciplines…
popular, regularized
XGBoost (eXtreme Gradient Boosting) is the most influential gradient boosting library in machine learning history — dominating Kaggle competitions from 2014 to 2020, winning…
xgboost extreme gradient boosting prediction, xgboost extreme gradient, extreme gradient boosting, gradient boosting prediction, xgboost extreme, extreme gradient
XGBoost Extreme Gradient Boosting Prediction with Machine Learning Introduction & Motivation XGBoost Extreme Gradient Boosting Prediction with Machine Learning addresses a central…
xgboost gradient boosting, xgboost gradient, gradient boosting
XGBoost Gradient Boosting Introduction & Motivation XGBoost Gradient Boosting addresses a central problem in ml process control and model-performance-accuracy prediction: how…
accelerated linear algebra, compiler, fusion, tensorflow, jax
XLA (Accelerated Linear Algebra) is a domain-specific compiler that optimizes TensorFlow and JAX computations — performing whole-program optimization including operation fusion…
xla, infrastructure
XLA is the domain-specific linear algebra compiler stack that optimizes ML graphs for CPU, GPU, and TPU backends - it performs aggressive graph transformations and kernel fusion…
xla, model optimization
XLA is an optimizing compiler for linear algebra that accelerates TensorFlow and JAX workloads - It improves performance through graph-level fusion and backend-specific code…
foundation model
XLNet uses permutation language modeling to capture bidirectional context while maintaining autoregressive pre-training benefits. Problem addressed: BERT uses artificial MASK…
xlnet autoregressive pretraining, xlnet autoregressive, autoregressive pretraining, bert glue plm qa
XLNet - Autoregressive Pretraining Introduction & Motivation XLNet: permutation language modeling for autoregressive pre-training. Overcomes BERT limitations. Applications…
xlnet autoregressive pre-training and permutation language modeling, xlnet autoregressive pre-training, autoregressive pre-training permutation, pre-training permutation language
XLNet Autoregressive Pre-Training and Permutation Language Modeling Introduction & Motivation XLNet Autoregressive Pre-Training and Permutation Language Modeling addresses…
foundation model
XLNet is a generalized autoregressive language model that uses permutation language modeling — instead of predicting tokens left-to-right, XLNet learns to predict each token…
cross-lingual nli, multilingual benchmark
XNLI (Cross-lingual Natural Language Inference) is a multilingual NLI benchmark spanning 15 languages — testing whether models can perform natural language inference across…
model optimization
XNOR-Net is an optimized binary neural network architecture — that approximates full-precision convolutions using XNOR (exclusive-NOR) operations and popcount, achieving ~58x…
xpos, extrapolatable position embedding
xPos (Extrapolatable Position Embedding) is an advanced position encoding method that enables transformers to generalize to sequence lengths far beyond those seen during training…
xps charge compensation drift prediction machine learning, xps charge, compensation drift prediction, xps, xps charge compensation drift prediction, xps charge compensation
XPS Charge Compensation Drift Prediction with Machine Learning Introduction & Motivation XPS Charge Compensation Drift Prediction with Machine Learning addresses a central problem…