Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:52:30.612043Z
Paper Citation Record · LEDGER
Cross-Process Defect Attribution using Potential Loss Analysis
As of 21 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2508.00895.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
9 of 9 outbound references displayed
- verified exact1
- verified fuzzy7
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 1e5be640-b757-41e1-8156-82259e3ba9f6 · outbound
This paper cites Improved Yield Prediction and Failure Analysis in Semiconductor Man- ufacturing with XGBoost and Shapley Additive exPlanations Models.
Cross-Process Defect Attribution using Potential Loss Analysis Improved Yield Prediction and Failure Analysis in Semiconductor Man- ufacturing with XGBoost and Shapley Additive exPlanations Models
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T17:52:30.727040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 564ec91f-c441-47b1-8be4-4e2a761ff5cd · outbound
This paper cites Soft-sensing conformer: A curriculum learning-based convolutional transformer.
Cross-Process Defect Attribution using Potential Loss Analysis Soft-sensing conformer: A curriculum learning-based convolutional transformer
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T17:52:30.706304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f84daf31-3385-400e-98dd-6dbb202960b8 · outbound
This paper cites Travel-time prediction using Gaussian process regression: A trajectory-based approach.
Cross-Process Defect Attribution using Potential Loss Analysis Travel-time prediction using Gaussian process regression: A trajectory-based approach
Reference 2009
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T17:52:30.780859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e93a1276-f5b3-4718-aab3-728dc891a25b · outbound
This paper cites Machine Learning Assisted New Product Setup.
Cross-Process Defect Attribution using Potential Loss Analysis Machine Learning Assisted New Product Setup
Reference 2020
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T17:52:30.744955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation aea48f78-aced-4b4e-b753-5365dce539f9 · outbound
This paper cites Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey.
Cross-Process Defect Attribution using Potential Loss Analysis Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:52:30.586506Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86529e4c-bde2-4591-9e4a-4ccb3e1df6b9 · outbound
This paper cites Graph representation and embedding for semiconductor manufacturing fab states.
Cross-Process Defect Attribution using Potential Loss Analysis Graph representation and embedding for semiconductor manufacturing fab states
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T17:52:30.763092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 64e91630-4322-4bb3-903b-03abdc60a801 · outbound
This paper cites Deep learning-based virtual metrology in multivariate time series.
Cross-Process Defect Attribution using Potential Loss Analysis Deep learning-based virtual metrology in multivariate time series
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T17:52:30.800213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 5df7cc77-ae5e-42d5-b4d1-beba683039f3 · outbound
This paper cites Enhanced Yield Prediction in Semiconductor Manufacturing: Innovative Strategies for Imbalanced Sample Management and Root Cause Analysis.
Cross-Process Defect Attribution using Potential Loss Analysis Enhanced Yield Prediction in Semiconductor Manufacturing: Innovative Strategies for Imbalanced Sample Management and Root Cause Analysis
Reference 2024
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T17:52:30.818261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1ff0286d-deb8-4928-82f8-7b68c8bea277 · outbound
This paper cites Path Learning with Trajectory Advantage Regression.
Cross-Process Defect Attribution using Potential Loss Analysis Path Learning with Trajectory Advantage Regression
Reference 2025
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T17:52:30.662070Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
No inbound Pith citation observations are available.