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Paper Citation Record · LEDGER

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs

As of 13 August 2026, this Paper Citation Record lists 100 of 291 outbound references and 2 inbound Pith citation observations for arXiv:2412.00800.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.00800 v2

Coverage vector

measured 100 of 291 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:01:31.879510Z

measured 102 of 102 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T09:54:05.683478Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T09:54:34.440547Z

Reference resolution

100 of 291 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved99
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e5f4d176-5c84-4e65-af3c-4c5721e26fa1 · outbound

This paper cites Jordan and Tom M.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Jordan and Tom M

Reference 1

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Observation 9cf224a3-ecd7-4d0f-8e69-14cc7b796bcb · outbound

This paper cites Gilpin, David Bau, Ben Z.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Gilpin, David Bau, Ben Z

Reference 5

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Observation 8ef13d32-ce83-4f6b-b81b-d0b264892bba · outbound

This paper cites General data protection regulation (gdpr).

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs General data protection regulation (gdpr)

Reference 6

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Observation 156568f2-aa8b-43b7-b5fc-727c61b2710e · outbound

This paper cites European union regulations on algorithmic decision- making and a â ˘AIJright to explanationâ ˘A˙I.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs European union regulations on algorithmic decision- making and a â ˘AIJright to explanationâ ˘A˙I

Reference 7

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Observation a67d992d-4832-4ffd-8b1a-f8ddb6b12ed9 · outbound

This paper cites an unresolved cited work.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Unresolved cited work

Reference 10

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Observation b5b1e08b-a8ec-46fa-94a1-f7e2970d66a9 · outbound

This paper cites Explainable artificial intelligence (xai): Concepts, taxonomies, opportunities and challenges toward responsible ai.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Explainable artificial intelligence (xai): Concepts, taxonomies, opportunities and challenges toward responsible ai

Reference 11

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Observation 78e210f1-9b2d-40d9-94f2-240c9d6b77c4 · outbound

This paper cites Explanation in artificial intelligence: Insights from the social sciences.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Explanation in artificial intelligence: Insights from the social sciences

Reference 12

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Observation b3d04a02-7408-4188-a062-06230970fd52 · outbound

This paper cites The Elements of Statistical Learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs The Elements of Statistical Learning

Reference 13

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Observation 42f37589-4d37-448f-889a-56c58378633e · outbound

This paper cites Ross Quinlan.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Ross Quinlan

Reference 14

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Observation b9f4cd0a-3d68-452b-b1de-2b96133dca0c · outbound

This paper cites To predict and serve? Significance, 13(5):14–19, 2016.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs To predict and serve? Significance, 13(5):14–19, 2016

Reference 15

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Observation 12f32538-1b1a-4bf9-9923-9b3c191a720f · outbound

This paper cites Support-vector networks.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Support-vector networks

Reference 16

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Observation 2dd6d75a-dca9-490a-9164-00bc7f64b978 · outbound

This paper cites Visualizing and understanding convolutional networks.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Visualizing and understanding convolutional networks

Reference 17

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Observation 3c3e2dce-6354-458f-82ef-65910f8f5bd1 · outbound

This paper cites Neural machine translation by jointly learning to align and translate.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Neural machine translation by jointly learning to align and translate

Reference 18

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Observation d5575999-b8cc-4c2d-a602-d6e669b689e2 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 19

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Observation da9bab9f-7b21-477b-a104-c608d3317884 · outbound

This paper cites Improving language understanding by generative pre-training.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Improving language understanding by generative pre-training

Reference 20

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Observation 5fdd91a4-b384-415f-94d1-a4eda8ebf6a7 · outbound

This paper cites an unresolved cited work.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Unresolved cited work

Reference 21

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Observation 782f70f7-ca24-47b5-a420-ca696340faff · outbound

This paper cites Unified framework for interpretable methods.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Unified framework for interpretable methods

Reference 22

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Observation d2b0fb65-5aae-4887-9a7a-44b5e4c18874 · outbound

This paper cites â ˘AIJwhy should i trust you?â ˘A˙I: Ex- plaining the predictions of any classifier.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs â ˘AIJwhy should i trust you?â ˘A˙I: Ex- plaining the predictions of any classifier

Reference 23

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Observation 6305f8b9-e5ab-4c39-89e9-603ec61e21de · outbound

This paper cites Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, and Dhruv Batra.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, and Dhruv Batra

Reference 24

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Observation 7be8edc2-c9d1-476d-82f3-ab741b21d15b · outbound

This paper cites A survey on explainable artificial intelligence (xai): Toward medical xai.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs A survey on explainable artificial intelligence (xai): Toward medical xai

Reference 25

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Observation 616ad4f3-e103-4b1b-9f83-5e93225567f5 · outbound

This paper cites Captum: A unified and generic model interpretability library for PyTorch.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Captum: A unified and generic model interpretability library for PyTorch

Reference 26

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Observation 3abbd7f5-b726-417e-b156-7ad3851db0ef · outbound

This paper cites MIT press, 2016.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs MIT press, 2016

Reference 28

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Observation 9702238f-bc81-461b-8349-f7afc6cb826e · outbound

This paper cites A survey of methods for explaining black box models.ACM computing surveys (CSUR), 51(5):1–42, 2018.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs A survey of methods for explaining black box models.ACM computing surveys (CSUR), 51(5):1–42, 2018

Reference 29

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Observation 1392c28e-c329-4a9f-bb94-9f4889af4e96 · outbound

This paper cites Novoa, Justin Ko, Susan M.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Novoa, Justin Ko, Susan M

Reference 30

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Observation c9d2e6ae-1946-4db1-b19c-c037ca1fabc4 · outbound

This paper cites Khandani, Adlar J.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Khandani, Adlar J

Reference 31

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Observation 6157e8ab-0cee-46d1-afb9-7996ed84ccd0 · outbound

This paper cites Frey, Joshua P.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Frey, Joshua P

Reference 32

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Observation b41387a4-7a3c-46f4-a87d-0a7530a159b5 · outbound

This paper cites Why a right to explanation of automated decision-making does not exist in the general data protection regulation.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Why a right to explanation of automated decision-making does not exist in the general data protection regulation

Reference 33

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Observation b15c135e-dbac-46f9-85e0-e1aa535d40d3 · outbound

This paper cites Interpretable Machine Learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Interpretable Machine Learning

Reference 34

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Observation 6d30af2b-515c-4620-9cf7-432baea18a63 · outbound

This paper cites Imagenet classification with deep con- volutional neural networks.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Imagenet classification with deep con- volutional neural networks

Reference 35

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Observation 64ec3f5b-8d48-472d-9fa2-6fab0dfebf85 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 36

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Observation 56ea7cc4-8639-4174-80e0-cbe3e808fdbd · outbound

This paper cites Methods for interpreting and understanding deep neural networks.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Methods for interpreting and understanding deep neural networks

Reference 37

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Observation 3146c383-a01e-426f-842f-038d4eed7eeb · outbound

This paper cites Visual analytics for explainable deep learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Visual analytics for explainable deep learning

Reference 38

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A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Unresolved cited work

Reference 39

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Observation 95dfbf76-3b16-4e1e-9518-51044e3125d0 · outbound

This paper cites A survey of methods for explaining black box models.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs A survey of methods for explaining black box models

Reference 40

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Observation 2be1b0e6-46a3-4108-be78-20e62eed2bc9 · outbound

This paper cites The Mythos of Model Interpretability.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs The Mythos of Model Interpretability

Reference 41

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Observation 83ea6ec3-f8af-4052-a630-dc772322566d · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

Reference 42

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Observation b1bcbe33-1d73-4994-adbf-f3f387672ac9 · outbound

This paper cites Ross Quinlan.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Ross Quinlan

Reference 43

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Observation 16d168de-466e-4086-b477-3c325b8d0685 · outbound

This paper cites Regression shrinkage and selection via the lasso.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Regression shrinkage and selection via the lasso

Reference 44

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Observation 15a4411f-5ec0-4e25-8268-254a642c8d54 · outbound

This paper cites Random forests.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Random forests

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Observation cfe9c4cf-44a6-4f7f-87ce-9b1f2f14960c · outbound

This paper cites Xgboost: A scalable tree boosting system.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Xgboost: A scalable tree boosting system

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Observation 85a883d9-3d3a-44db-ae31-986651a8178b · outbound

This paper cites Deep learning.Nature, 521(7553):436–444, 2015.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Deep learning.Nature, 521(7553):436–444, 2015

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Observation dc495199-6564-4601-815f-8d8538b0c87b · outbound

This paper cites Decision trees and multivariate analysis, volume 1.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Decision trees and multivariate analysis, volume 1

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source=pdf_text observed=2026-08-12T05:01:31.626816Z digest=sha256:62fd3eb40deef50215617ef596bfeba558f59d9aa1b166b853737627c5f8806c

Observation 5866d302-2b79-4bbe-81b2-33a172d1a1af · outbound

This paper cites Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission

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source=pdf_text observed=2026-08-12T05:01:31.631467Z digest=sha256:cf5ad486c5ff7b11b75619672d4258ef86b8be18b92bd68964d4bcec70a637cd

Observation b7ff2d77-d35d-4e15-b388-26c4a8d5e3d0 · outbound

This paper cites Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models

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source=pdf_text observed=2026-08-12T05:01:31.635572Z digest=sha256:8de7fbac0ba16a50fce51a9b8ecce4b8ffcbf5bd9a72360e9951ac79b31e48fc

Observation 6802c0b1-27bc-43d4-a9f9-9291dc279a6e · outbound

This paper cites Logistic Regression Explained.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Logistic Regression Explained

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source=pdf_text observed=2026-08-12T05:01:31.639757Z digest=sha256:5b1cf1cfd4d0aa88ba4e4df62f755c5914d37654eb010366340988d24c28c68c

Observation 22eb7052-d575-4758-9b50-d25a41d84125 · outbound

This paper cites Applied Logistic Regression.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Applied Logistic Regression

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source=pdf_text observed=2026-08-12T05:01:31.644057Z digest=sha256:b7954b3cb838d5676df50d138f66419cd285ac365844889bae932fa989898d8d

Observation a5ae5c9d-4edf-4d57-b574-0ebda347b65b · outbound

This paper cites Pattern recognition and machine learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Pattern recognition and machine learning

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source=pdf_text observed=2026-08-12T05:01:31.648331Z digest=sha256:f852cd8e9bfa221e0fd1fa6c83f2090e0a994ea15009f6d0c1c395bfb589c520

Observation 02ba10f0-c5af-4b35-9c55-88672648cd66 · outbound

This paper cites An Introduction to Statis- tical Learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs An Introduction to Statis- tical Learning

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source=pdf_text observed=2026-08-12T05:01:31.652525Z digest=sha256:1d0bf03178ebc441e75a6f48f53e1004a690a8d4ac70c0ed50bd190fed9c2fdb

Observation 53289a1b-4f54-482f-91b8-72a01546cad0 · outbound

This paper cites Understanding Machine Learning: From Theory to Algorithms.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Understanding Machine Learning: From Theory to Algorithms

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source=pdf_text observed=2026-08-12T05:01:31.656804Z digest=sha256:610d3015855d7ee098c591b2aeea046f07341da6f6ce5db32bd49ead21338cdc

Observation f2ebe673-8cd0-48a0-831a-c6325dc34126 · outbound

This paper cites Scikit- learn: Machine learning in python.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Scikit- learn: Machine learning in python

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source=pdf_text observed=2026-08-12T05:01:31.660983Z digest=sha256:bba8d97bfc4236f5f51b69c67f0b9af49b14328a7f88160990616ed4b30bbdaf

Observation 577c824e-55f4-40cc-aba2-352ea7f2bd45 · outbound

This paper cites James Murdoch, Chandan Singh, Karl Kumbier, Reza Abbasi-Asl, and Bin Yu.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs James Murdoch, Chandan Singh, Karl Kumbier, Reza Abbasi-Asl, and Bin Yu

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source=pdf_text observed=2026-08-12T05:01:31.665331Z digest=sha256:eee6661a78f0cccc984c0d876a7fc31df6c2987747f8d8feaa565927a11697df

Observation 6c5dd67b-cb2c-4e28-b0f4-3cf4de79d3b1 · outbound

This paper cites Artificial Intelligence: A Modern Approach.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Artificial Intelligence: A Modern Approach

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source=pdf_text observed=2026-08-12T05:01:31.669579Z digest=sha256:df13552d510f27c5b61e625444fa7ddab7be0eece955a1452c408729bcd7e8d0

Observation 4d93093d-6235-49f9-af4d-1750e5b92620 · outbound

This paper cites McCormick, and David Madigan.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs McCormick, and David Madigan

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source=pdf_text observed=2026-08-12T05:01:31.673929Z digest=sha256:67fe72e1581271e8f069f0dcab3653006c3a5440f40f009051123bd0dc7f0394

Observation a74a4994-c7b0-487c-866c-d270325f20fe · outbound

This paper cites Rule-based machine learning and knowledge extraction for model interpretability.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Rule-based machine learning and knowledge extraction for model interpretability

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source=pdf_text observed=2026-08-12T05:01:31.678109Z digest=sha256:88ff2c9721d37bb329bba1d95f8228e3d5a51351ea4014b53fd42ae5f023f36e

Observation 4d72ceed-edd8-4586-81b8-dddeb0b3bba7 · outbound

This paper cites Rule-based systems.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Rule-based systems

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source=pdf_text observed=2026-08-12T05:01:31.682403Z digest=sha256:ec61157d098d35bb89ae9753eba4104433dac000f214b15f8599adc127ee2feb

Observation 06e7c030-e0cb-43ba-9626-bd344aeed4fe · outbound

This paper cites Emerging trends and challenges in rule-based machine learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Emerging trends and challenges in rule-based machine learning

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source=pdf_text observed=2026-08-12T05:01:31.686461Z digest=sha256:861405d2dc7e10df6e8551f4700028913474de95ff94160c026c3e8df8bf4075

Observation 7a1cde92-7bf8-4997-9f24-c6bbbf8620b3 · outbound

This paper cites Biomedical Informatics: Computer Applications in Health Care and Biomedicine.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Biomedical Informatics: Computer Applications in Health Care and Biomedicine

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source=pdf_text observed=2026-08-12T05:01:31.690988Z digest=sha256:27e6af12c9f94fb864005bac74553cb426aef1f38f008bdf0c03cd41c8e0cdce

Observation 645a3418-af3f-47ee-9708-2e3496df099c · outbound

This paper cites Expert systems in medical applications: a review.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Expert systems in medical applications: a review

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source=pdf_text observed=2026-08-12T05:01:31.695454Z digest=sha256:c0012601c7e99ca1d45911a11442c854f8b0d04c28b83aea54b478ccaf777cbc

Observation b7930cff-3adc-4688-b4b8-5fba163dc0bb · outbound

This paper cites Legal reasoning and legal argumentation.The Knowl- edge Engineering Review, 27(1):1–5, 2012.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Legal reasoning and legal argumentation.The Knowl- edge Engineering Review, 27(1):1–5, 2012

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source=pdf_text observed=2026-08-12T05:01:31.699667Z digest=sha256:c8c4a5e6366443857c130cceb9e644a34be96b2b69cabdbe0a41faa428644d89

Observation 1202ea29-a658-467b-848b-45685fa4b045 · outbound

This paper cites The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature

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source=pdf_text observed=2026-08-12T05:01:31.703920Z digest=sha256:9f1465fe5718f3453825d758466ac239079bfc06a153c5ac0e33867bce3c528c

Observation a62edd5e-d580-4f0a-809b-7dfcf6c58011 · outbound

This paper cites Guidelines for a knowledge-based systems paper.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Guidelines for a knowledge-based systems paper

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source=pdf_text observed=2026-08-12T05:01:31.708091Z digest=sha256:74ac7200b72fb5c4073202108eaa0ff8fc532c8b666d086378ec70f5924885b6

Observation 3d680a59-2a4d-47b0-a828-c27377236bb0 · outbound

This paper cites Generalized Additive Models.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Generalized Additive Models

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source=pdf_text observed=2026-08-12T05:01:31.712101Z digest=sha256:661eaf35aaef5997c3bf4413a3da2eb6ab61bfa11ef80fce15c99d3f8a8eefdb

Observation 4d122890-dde0-4387-a519-1f217ac7f0ad · outbound

This paper cites Generalized Additive Models: An Introduction with R.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Generalized Additive Models: An Introduction with R

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source=pdf_text observed=2026-08-12T05:01:31.716144Z digest=sha256:c6fb5621f1bb67957bf9c3f11127a0bfbc419a74380516658d5104b69b4f4a7e

Observation 4458b2da-8f87-4857-97ab-4d0d3f8efa0b · outbound

This paper cites Intelligible models for classification and re- gression.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Intelligible models for classification and re- gression

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source=pdf_text observed=2026-08-12T05:01:31.720119Z digest=sha256:94712884422ae031da39754180143cc87a26a6df46277ee04e3e8e2309b33bf8

Observation 85f4ea4d-59ce-405a-8dcc-f410b871108c · outbound

This paper cites pygam: Generalized additive models in python.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs pygam: Generalized additive models in python

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source=pdf_text observed=2026-08-12T05:01:31.724474Z digest=sha256:658095c039128194426e93e3256b1bcc6c88c6c9b3ab22a038bf4408d386e667

Observation ed50d77b-b833-470c-ab16-2717d2d6ab97 · outbound

This paper cites Intel- ligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Intel- ligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission

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source=pdf_text observed=2026-08-12T05:01:31.728672Z digest=sha256:14c10b41520e722eaa0135d7e871f284931697e0be57eb30269cc0c5bb0f16d9

Observation 5a72ac05-8760-4f54-9b98-6bbf9d972f88 · outbound

This paper cites Applications of third order differential subordination and superordination involving generalized Struve function.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Applications of third order differential subordination and superordination involving generalized Struve function

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source=pdf_text observed=2026-08-12T05:01:31.732770Z digest=sha256:7dfbbfa9abd3b8618c40e96a56a515a25d03fbc8d8bd9d13f9d86d7292f0147b

Observation 672e68f1-3df1-4bbf-a716-d6642ecb81bc · outbound

This paper cites Gam: The predictive modeling silver bullet.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Gam: The predictive modeling silver bullet

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Observation 3c883af5-f178-404c-b3cd-124fb11504a9 · outbound

This paper cites Strong and weak divergence of exponential and linear-implicit Euler approximations for stochastic partial differential equations with superlinearly growing nonlinearities.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Strong and weak divergence of exponential and linear-implicit Euler approximations for stochastic partial differential equations with superlinearly growing nonlinearities

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source=pdf_text observed=2026-08-12T05:01:31.741335Z digest=sha256:86f49ff1be8763777f651aa6fd24d0de43e7fd71141c9495530206dd7e8ea328

Observation 919ef878-1fb7-4a16-abaa-e9a8a5fd87b1 · outbound

This paper cites Machine learning: a probabilistic perspective.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Machine learning: a probabilistic perspective

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source=pdf_text observed=2026-08-12T05:01:31.746148Z digest=sha256:3010140cb6752f7cef3d84556486c5e4dc81543b2bbbcb410f17651b74bc12dd

Observation 29c4df3c-2b6a-4169-914f-c4583f1aefdc · outbound

This paper cites Bayesian data analysis.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Bayesian data analysis

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source=pdf_text observed=2026-08-12T05:01:31.750414Z digest=sha256:281b3d7573ca25260eaa509c33d0847fcbf506f8ae0f8e5fa66333df43369698

Observation 681753b6-e62b-4556-99cf-af0816e91d7b · outbound

This paper cites Pattern Recognition and Machine Learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Pattern Recognition and Machine Learning

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source=pdf_text observed=2026-08-12T05:01:31.754611Z digest=sha256:66cfecf20c34ae2392f22f88da64ab6a36e9b0e8c6a59a4bbdfbe7b2af30173a

Observation e9f4887c-0b23-4808-b375-021e01d4c3da · outbound

This paper cites TensorFlow Distributions.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs TensorFlow Distributions

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source=pdf_text observed=2026-08-12T05:01:31.759026Z digest=sha256:85a22692edbc0a6e96e85284897302baf413a442b04cbc297f54708e7af9bec0

Observation 7f017009-f504-4864-90a4-0c4eea0a2e64 · outbound

This paper cites Handbook of Markov Chain Monte Carlo.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Handbook of Markov Chain Monte Carlo

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source=pdf_text observed=2026-08-12T05:01:31.763550Z digest=sha256:ff0bf3245652c75af5cc8ea1ef64d154d64a1f4667d18f4f4d5af4175b202952

Observation f486a306-a00f-4943-9148-b5723e856c9a · outbound

This paper cites Bayesian portfolio analysis.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Bayesian portfolio analysis

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source=pdf_text observed=2026-08-12T05:01:31.767906Z digest=sha256:07bf2a32c39cb8051089bd2133ad89e000294f287e25bb7f8cfc81e6341525ad

Observation 4d10e6be-687a-4f96-a007-ed1c0bbc4156 · outbound

This paper cites Online controlled experiments and a/b testing.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Online controlled experiments and a/b testing

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source=pdf_text observed=2026-08-12T05:01:31.772188Z digest=sha256:446cd159bf6731285bc5aae92d0ecaac64b1ec126db139e23843123b99b8595b

Observation 167ffc21-7316-475e-8f50-b6d2f3e75cc5 · outbound

This paper cites Variational inference: A review for statisti- cians.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Variational inference: A review for statisti- cians

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source=pdf_text observed=2026-08-12T05:01:31.776299Z digest=sha256:dc0316ebe0b6c0fb71c6b0838126c87215a7fcc405fee98806a7ee5015107fb5

Observation 6ae499ba-7156-49f6-89e9-deb9d695dfd7 · outbound

This paper cites Streaming variational bayes.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Streaming variational bayes

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source=pdf_text observed=2026-08-12T05:01:31.780431Z digest=sha256:c36c6e9b3e5357ddcb7a713c7fe849719aab8f2ddf20a6b4b09a07105eaf8341

Observation 2fb1ba8c-d1f5-463b-b95f-a2152f22c88a · outbound

This paper cites Representation learning: A review and new perspectives.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Representation learning: A review and new perspectives

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Observation 7ad49e39-a830-4cc3-972b-3b357bd2e96c · outbound

This paper cites Understanding neu- ral networks through deep visualization.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Understanding neu- ral networks through deep visualization

Reference 86

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Observation 71844d70-2b78-4b65-b64b-90cea558c60a · outbound

This paper cites Very deep convolutional networks for large-scale image recognition.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Very deep convolutional networks for large-scale image recognition

Reference 87

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Observation bdb73837-a6a1-4060-990c-9a7021e42e8f · outbound

This paper cites Deep inside convolutional networks: Visualising image classification models and saliency maps.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Deep inside convolutional networks: Visualising image classification models and saliency maps

Reference 88

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Observation ee4bfffa-1289-4ccb-935c-0a9701a6b9aa · outbound

This paper cites Axiomatic attribution for deep networks.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Axiomatic attribution for deep networks

Reference 89

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Observation f5e90e96-6f1b-4f8d-b9b8-40303d603270 · outbound

This paper cites A Critical Review of Recurrent Neural Networks for Sequence Learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs A Critical Review of Recurrent Neural Networks for Sequence Learning

Reference 90

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Observation ead0d47f-b369-455a-b2f7-c3983799f965 · outbound

This paper cites Visualizing and Understanding Recurrent Networks.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Visualizing and Understanding Recurrent Networks

Reference 91

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Observation 077f6673-e512-4a0f-8a2a-8d56ef806ccf · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 92

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Observation 7fa0ab5a-82c0-4119-8f0f-8563de27b4dc · outbound

This paper cites Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 93

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Observation e9d7876b-7d0e-4d5f-8ee1-a9f1be3fa89a · outbound

This paper cites A Multiscale Visualization of Attention in the Transformer Model.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs A Multiscale Visualization of Attention in the Transformer Model

Reference 94

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Observation 88b8db3a-5585-4521-aea7-85036e72fc00 · outbound

This paper cites Language models are few-shot learners.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Language models are few-shot learners

Reference 95

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Observation 2bd6014c-b69f-4bf8-a53c-7b89a133916e · outbound

This paper cites Large Lan- guage Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challenges.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Large Lan- guage Models and Cognitive Science: A Comprehensive Review of Similarities, Differences, and Challenges

Reference 96

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Observation 5f2483d0-8493-46f4-bd5c-4f091a5fbf7c · outbound

This paper cites Design of intelligent customer service system based on deep learning.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Design of intelligent customer service system based on deep learning

Reference 97

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Observation cf5b9608-cefd-41d6-a858-2c076fc58ca9 · outbound

This paper cites CTRL: A Conditional Transformer Language Model for Controllable Generation.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs CTRL: A Conditional Transformer Language Model for Controllable Generation

Reference 98

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Observation b567346c-4053-47d2-93ac-090a8537f70f · outbound

This paper cites Github copilot: Y our ai pair programmer.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Github copilot: Y our ai pair programmer

Reference 99

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Observation 32208586-f769-499f-be7a-5835849bab09 · outbound

This paper cites Biobert: a pre-trained biomedical language representation model for biomedical text mining.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Biobert: a pre-trained biomedical language representation model for biomedical text mining

Reference 100

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Observation ad459a42-6e80-4203-b558-3d74ac493065 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 101

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Observation 3fe92703-0e56-4f64-b32c-8b210621e8f0 · outbound

This paper cites GPT-4 Technical Report.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs GPT-4 Technical Report

Reference 102

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Observation 959347ec-d355-4298-bdf8-43f9be70f0f5 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs LLaMA: Open and Efficient Foundation Language Models

Reference 103

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source=pdf_text observed=2026-08-12T05:01:31.865661Z digest=sha256:f9cf730e8670f5af967014fb0b3cbfb9ce529e2c3c42686bc223b0fe7a8a4ef6

Observation adb05308-342e-47ba-a3ed-a5c4e6ee6fbb · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 104

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source=pdf_text observed=2026-08-12T05:01:31.870230Z digest=sha256:fff75bbd05e9e81079252684e0304fdf9cc8544027664433914db1527b199d56

Observation bd088d7f-a695-4882-844c-37401f2fc0cc · outbound

This paper cites Scaling Laws for Neural Language Models.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Scaling Laws for Neural Language Models

Reference 105

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Observation 0e81de2c-7d20-4fc1-9f36-5d9c7645a3b7 · outbound

This paper cites Energy and policy considerations for deep learning in nlp.

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs Energy and policy considerations for deep learning in nlp

Reference 106

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Pith citing papers

Observation 25460c5d-9d3c-4e49-b126-334954d11087 · inbound

AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compression cites this paper.

AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compression A Comprehensive Guide to Explainable AI: From Classical Models to LLMs

Reference 5

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arxiv_id, observed 2026-05-16T21:28:34.035794Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 605b29a7-85f7-44fe-bf69-7695a1c04804 · inbound

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions cites this paper.

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions A Comprehensive Guide to Explainable AI: From Classical Models to LLMs

Reference 8

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arxiv_id, observed 2026-06-30T09:54:34.442358Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-30T09:54:05.683478Z digest=sha256:f1a758a5c4d317e56bf52e7bf6df1b8a1c56995e77bce28fc23fb3b92d5f990e