Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:07:54.739544Z
Paper Citation Record · LEDGER
As of 20 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2505.10991.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:07:54.739544Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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
58 of 58 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 2a128c86-69b5-4f24-bfa1-c7a49ca6a204 · outbound
Most General Explanations of Tree Ensembles (Extended Version) On pixel-wise explanations for non-linear classifier decisions by layer-wise relevanc e propagation
Reference 1
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Most General Explanations of Tree Ensembles (Extended Version) Solving MAXSA T by solving a sequence of simpler SA T instances
Reference 11
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Most General Explanations of Tree Ensembles (Extended Version) Friedman
Reference 12
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Reference 13
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Most General Explanations of Tree Ensembles (Extended Version) On the failings of shapley values for explainability
Reference 15
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Reference 16
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Most General Explanations of Tree Ensembles (Extended Version) Liffiton, and Joao Marques-Silva
Reference 17
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Reference 21
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Most General Explanations of Tree Ensembles (Extended Version) Towards trustable explain- able AI
Reference 22
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Most General Explanations of Tree Ensembles (Extended Version) On explaining random forests with SA T
Reference 23
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Most General Explanations of Tree Ensembles (Extended Version) Efficient Contrastive Explanations on Demand
Reference 24
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Most General Explanations of Tree Ensembles (Extended Version) On tackling explanation redundancy in de- cision trees
Reference 25
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Most General Explanations of Tree Ensembles (Extended Version) A new class of explanations for classifiers with non-binary features
Reference 26
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Most General Explanations of Tree Ensembles (Extended Version) Towards trustable SHAP scores
Reference 27
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Observation 737a96a1-805c-493e-ae3b-a2c30a6dd041 · outbound
Most General Explanations of Tree Ensembles (Extended Version) Lundberg and Su-In Lee
Reference 30
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Most General Explanations of Tree Ensembles (Extended Version) Delivering trustworthy AI through formal XAI
Reference 32
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Observation 85f9c4e9-902f-4cdf-ba12-3c39256c80d5 · outbound
Most General Explanations of Tree Ensembles (Extended Version) Logic-based ex- plainability in machine learning
Reference 33
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Most General Explanations of Tree Ensembles (Extended Version) Logic-based ex- plainability: Past, present and future
Reference 34
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Most General Explanations of Tree Ensembles (Extended Version) Explanation in artificial intelli- gence: Insights from the social sciences
Reference 35
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Most General Explanations of Tree Ensembles (Extended Version) Interpretable machine learning
Reference 36
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Most General Explanations of Tree Ensembles (Extended Version) Olson, William La Cava, Pa- tryk Orzechowski, Ryan J
Reference 37
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Most General Explanations of Tree Ensembles (Extended Version) Scikit-learn: Machine learning in Python
Reference 38
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Most General Explanations of Tree Ensembles (Extended Version) Partial MUS enumeration
Reference 39
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Most General Explanations of Tree Ensembles (Extended Version) ”why should I trust you?”: Explain- ing the predictions of any classifier
Reference 40
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Observation 72b9304b-5dba-417d-b67e-caf5cd293b8d · outbound
Most General Explanations of Tree Ensembles (Extended Version) Anchors: High-precision model- agnostic explanations
Reference 41
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Observation 3e78992a-69c3-43fa-8a7d-50cdd829ecf8 · outbound
Most General Explanations of Tree Ensembles (Extended Version) Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Reference 43
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Most General Explanations of Tree Ensembles (Extended Version) Implicit hitting set algorithms for re a- soning beyond NP
Reference 44
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Observation f513dba6-8a8b-48cb-84ef-4cb775a4647a · outbound
Most General Explanations of Tree Ensembles (Extended Version) Towards explainable artificial intelligence
Reference 45
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Observation 0c2cdedd-e919-446d-88dc-1e68c6bfcc25 · outbound
Most General Explanations of Tree Ensembles (Extended Version) Anders, and Klaus- Robert M¨ uller
Reference 46
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Observation 86c33a0f-8edc-48b4-bcfb-f709277e9b1e · outbound
Most General Explanations of Tree Ensembles (Extended Version) Prediction is deduction but explanation is abduction
Reference 47
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Observation 55586326-3c30-4a06-8ca8-f5846e64fe95 · outbound
Most General Explanations of Tree Ensembles (Extended Version) Fooling LIME and SHAP: adversarial attacks on post hoc explanation methods
Reference 49
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Observation 85d90568-fe72-4271-b336-26e8dfe5798a · outbound
Most General Explanations of Tree Ensembles (Extended Version) Swartout
Reference 50
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Most General Explanations of Tree Ensembles (Extended Version) The computational complexity of understanding binary classifier decisions
Reference 53
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Reference 54
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Reference 55
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Most General Explanations of Tree Ensembles (Extended Version) Copy number variation in plasma as a tool for lung cancer prediction using extreme gradient boosting (xgboost) classifier
Reference 56
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Observation b417fe91-e7e1-45ba-a05c-f5b4c5c0fb27 · outbound
Most General Explanations of Tree Ensembles (Extended Version) On Formal Feature Attribution and Its Approximation
Reference 57
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Observation d71f4aa2-1c24-4252-9c10-c675aa1cec4a · outbound
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Reference 58
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Most General Explanations of Tree Ensembles (Extended Version) Swartout
Reference 1977
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Observation 3904aaa0-c4fc-4e86-9ffd-9ff499fbfd87 · outbound
Most General Explanations of Tree Ensembles (Extended Version) https://archive.ics.uci.edu/ml,
Reference 1983
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Observation c87ff411-6f15-4b79-93ba-9fe8d45ff74e · outbound
Most General Explanations of Tree Ensembles (Extended Version) A symbolic approach to explaining bayesian net- work classifiers
Reference 1989
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Observation 40167ccb-6c70-454c-b5c6-718827b577a7 · outbound
Most General Explanations of Tree Ensembles (Extended Version) Karp, Erick Moreno-Centeno, and Santosh S
Reference 2001
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Most General Explanations of Tree Ensembles (Extended Version) Logic for explainable AI
Reference 2003
Source-reported events for the cited work
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Observation 8fdbb4d0-197c-4c18-a951-7fd1cdfaacdd · outbound
Most General Explanations of Tree Ensembles (Extended Version) To- wards formal XAI: formally approximate minimal expla- nations of neural networks
Reference 2005
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Most General Explanations of Tree Ensembles (Extended Version) XGBoost: A scalable tree boosting system
Reference 2011
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Observation 4829a8a4-a242-4d59-8319-c3161e72f2c4 · outbound
Most General Explanations of Tree Ensembles (Extended Version) Liffiton, Alessandro Previti, Ammar Malik, and Jo˜ ao Marques-Silva
Reference 2013
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Reference 2015
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Reference 2016
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Most General Explanations of Tree Ensembles (Extended Version) Explainability is not a game
Reference 2017
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Most General Explanations of Tree Ensembles (Extended Version) Interpretable machine learning: Fundamental prin- ciples and 10 grand challenges
Reference 2018
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Reference 2019
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Observation 46abe68c-2699-49f8-b251-5948263670ab · outbound
Most General Explanations of Tree Ensembles (Extended Version) Stuckey, and Jo˜ ao Marques-Silva
Reference 2020
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Observation af78fbc9-126c-4bcc-bd7c-d925df164f1f · outbound
Most General Explanations of Tree Ensembles (Extended Version) Lobo, Vignesh Viswanathan, and Y air Zick
Reference 2021
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Reference 2022
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Reference 2023
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Most General Explanations of Tree Ensembles (Extended Version) Random forests
Reference 2024
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Reference 2025
Source-reported events for the cited work
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No inbound Pith citation observations are available.