Paper Citation Record · LEDGER

Exploring the Rashomon Set for Concept-Based Models

As of 10 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2511.19636.

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

pith.paper-citation-record.v1
2511.19636 v2

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T20:33:53.932064Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T10:46:55.114471Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

verified exact0
verified fuzzy0
unresolved50
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ddcf4ec-f1ef-41d5-ac86-370bd43f535b · outbound

This paper cites Advancing vision-language models with adapter ensemble strategies.

Exploring the Rashomon Set for Concept-Based Models Advancing vision-language models with adapter ensemble strategies

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:46.485024Z

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Observation ae27499d-0cc0-432d-81ca-8742e01ec3e8 · outbound

This paper cites Model multiplicity: Opportunities, concerns, and solutions.

Exploring the Rashomon Set for Concept-Based Models Model multiplicity: Opportunities, concerns, and solutions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:46.580160Z

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Observation 33874a2d-8ece-4885-9039-1c7ec29a1b4f · outbound

This paper cites Using noise to infer aspects of simplicity without learning.Advances in Neural Information Process- ing Systems, 37:131824–131858, 2024.

Exploring the Rashomon Set for Concept-Based Models Using noise to infer aspects of simplicity without learning.Advances in Neural Information Process- ing Systems, 37:131824–131858, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:46.699152Z

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Observation 9d58590c-d493-4738-959b-18c9b4f0a6e4 · outbound

This paper cites Statistical modeling: The two cultures (with comments and a rejoinder by the author).Statistical science, 16(3):199–231, 2001.

Exploring the Rashomon Set for Concept-Based Models Statistical modeling: The two cultures (with comments and a rejoinder by the author).Statistical science, 16(3):199–231, 2001

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:46.823504Z

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Observation 25288086-8992-40fa-968f-24ba9f2c4048 · outbound

This paper cites an unresolved cited work.

Exploring the Rashomon Set for Concept-Based Models Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:46.948400Z

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Observation ecd68ea8-41dd-43e6-82d6-32c85e48d8a3 · outbound

This paper cites AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition.

Exploring the Rashomon Set for Concept-Based Models AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:47.072558Z

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Observation a562d3a1-a35c-4708-84d7-200680fab731 · outbound

This paper cites Concept whitening for interpretable image recognition.Nature Machine Intelli- gence, 2(12):772–782, 2020.

Exploring the Rashomon Set for Concept-Based Models Concept whitening for interpretable image recognition.Nature Machine Intelli- gence, 2(12):772–782, 2020

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:47.263615Z

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Observation f71c6955-8b72-454b-bed0-fdd18bea0743 · outbound

This paper cites Vision Transformer Adapter for Dense Predictions.

Exploring the Rashomon Set for Concept-Based Models Vision Transformer Adapter for Dense Predictions

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:47.381192Z

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Observation e4758cbe-bafe-43d4-858f-1c32ef31b99f · outbound

This paper cites Diversifying deep ensembles: A saliency map approach for enhanced ood detection, calibration, and accuracy.

Exploring the Rashomon Set for Concept-Based Models Diversifying deep ensembles: A saliency map approach for enhanced ood detection, calibration, and accuracy

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:47.517392Z

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Observation f49f5516-4cd7-466f-ba7b-357a07855c09 · outbound

This paper cites Exploring the cloud of vari- able importance for the set of all good models.Nature Ma- chine Intelligence, 2(12):810–824, 2020.

Exploring the Rashomon Set for Concept-Based Models Exploring the cloud of vari- able importance for the set of all good models.Nature Ma- chine Intelligence, 2(12):810–824, 2020

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:47.694567Z

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Observation e8d43be5-6b00-444d-95eb-153166714b67 · outbound

This paper cites Rashomon sets for prototypical-part networks: Editing interpretable models in real-time.

Exploring the Rashomon Set for Concept-Based Models Rashomon sets for prototypical-part networks: Editing interpretable models in real-time

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:47.836964Z

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Observation 85bd968e-0b8a-450d-952c-d91e2c371783 · outbound

This paper cites Underspecification presents challenges for credibility in modern machine learning.Journal of Machine Learning Research, 2020.

Exploring the Rashomon Set for Concept-Based Models Underspecification presents challenges for credibility in modern machine learning.Journal of Machine Learning Research, 2020

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:47.952147Z

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Observation 9d6f4e0a-fe37-427e-b093-19e9aa8ecb63 · outbound

This paper cites Concept embedding mod- els: Beyond the accuracy-explainability trade-off.Advances in neural information processing systems, 35:21400–21413,.

Exploring the Rashomon Set for Concept-Based Models Concept embedding mod- els: Beyond the accuracy-explainability trade-off.Advances in neural information processing systems, 35:21400–21413,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:48.145602Z

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Observation 8376c598-d453-4b44-8c32-9d601842dc18 · outbound

This paper cites an unresolved cited work.

Exploring the Rashomon Set for Concept-Based Models Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:48.260114Z

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Observation 1591e577-4fab-4aed-bcba-88f4e02df218 · outbound

This paper cites Deep Ensembles: A Loss Landscape Perspective.

Exploring the Rashomon Set for Concept-Based Models Deep Ensembles: A Loss Landscape Perspective

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:48.466572Z

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Observation 72e6fe20-b148-4f81-8244-60fc98d8c4cd · outbound

This paper cites Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning.

Exploring the Rashomon Set for Concept-Based Models Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:48.646440Z

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Observation c1701811-b390-49bc-a8fc-820eaa5a37d6 · outbound

This paper cites Merging Experts into One: Improving Computational Efficiency of Mixture of Experts.

Exploring the Rashomon Set for Concept-Based Models Merging Experts into One: Improving Computational Efficiency of Mixture of Experts

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:48.758182Z

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Observation 0237cca2-177a-4ff5-aee6-8b8bd97b2a1f · outbound

This paper cites Parameter-efficient transfer learning for NLP.

Exploring the Rashomon Set for Concept-Based Models Parameter-efficient transfer learning for NLP

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:48.917410Z

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Observation e4d77e6b-4650-4328-87c1-a111b585ea7e · outbound

This paper cites Rashomon capacity: A met- ric for predictive multiplicity in classification.

Exploring the Rashomon Set for Concept-Based Models Rashomon capacity: A met- ric for predictive multiplicity in classification

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.064275Z

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Observation 6c6e272f-289b-4cfe-aae1-d755ffbb1552 · outbound

This paper cites Dropout-based rashomon set exploration for efficient predic- tive multiplicity estimation.

Exploring the Rashomon Set for Concept-Based Models Dropout-based rashomon set exploration for efficient predic- tive multiplicity estimation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.180530Z

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Observation df049be5-febe-4566-aad4-ceb96c610262 · outbound

This paper cites Lora: Low- rank adaptation of large language models.

Exploring the Rashomon Set for Concept-Based Models Lora: Low- rank adaptation of large language models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.297770Z

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Observation be41b5e6-6d5b-43a9-a299-603bbfd41643 · outbound

This paper cites Probabilistic concept bottleneck models.

Exploring the Rashomon Set for Concept-Based Models Probabilistic concept bottleneck models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.413318Z

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Observation 47c395a1-a37b-4fdf-829f-3f66c7e83f6d · outbound

This paper cites Eq-cbm: A probabilistic concept bottle- neck with energy-based models and quantized vectors, 2024.

Exploring the Rashomon Set for Concept-Based Models Eq-cbm: A probabilistic concept bottle- neck with energy-based models and quantized vectors, 2024

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.526034Z

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Observation f0c37326-cdad-4d0a-834f-c4de53299580 · outbound

This paper cites Concept bottleneck models.

Exploring the Rashomon Set for Concept-Based Models Concept bottleneck models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.653281Z

Source-reported events for the cited work

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Observation f311d7dd-0fff-4832-992a-c72bd15ed5d9 · outbound

This paper cites Similarity of neural network represen- tations revisited.

Exploring the Rashomon Set for Concept-Based Models Similarity of neural network represen- tations revisited

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.804741Z

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Observation 48bc3d9a-8b24-4a14-a82a-c92976d19daa · outbound

This paper cites Learning multiple layers of features from tiny images.

Exploring the Rashomon Set for Concept-Based Models Learning multiple layers of features from tiny images

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:49.919025Z

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Observation 9df445ac-4a25-4197-99c6-24780686c80f · outbound

This paper cites Simple and scalable predictive uncertainty esti- mation using deep ensembles.

Exploring the Rashomon Set for Concept-Based Models Simple and scalable predictive uncertainty esti- mation using deep ensembles

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:50.110357Z

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Observation c208dc31-24bb-4ee2-9f80-76def4a089ef · outbound

This paper cites Ensembles of Low-Rank Expert Adapters.

Exploring the Rashomon Set for Concept-Based Models Ensembles of Low-Rank Expert Adapters

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:50.303976Z

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Observation 825a5720-0c9d-4391-86b1-ab954f2d9a57 · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

Exploring the Rashomon Set for Concept-Based Models DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:50.465223Z

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Observation f367c008-c733-4ea6-a4bc-07524683b66b · outbound

This paper cites Deep learning face attributes in the wild.

Exploring the Rashomon Set for Concept-Based Models Deep learning face attributes in the wild

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:50.645957Z

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Observation 53ab2893-f85f-4248-ad08-04aec91764b0 · outbound

This paper cites A unified approach to interpreting model predictions.Advances in neural informa- tion processing systems, 30, 2017.

Exploring the Rashomon Set for Concept-Based Models A unified approach to interpreting model predictions.Advances in neural informa- tion processing systems, 30, 2017

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:50.843487Z

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Observation 13172ca2-5438-4654-b9f6-6b962a339e49 · outbound

This paper cites Predictive multiplicity in classification.

Exploring the Rashomon Set for Concept-Based Models Predictive multiplicity in classification

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:51.024368Z

Source-reported events for the cited work

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Observation 2fc14ee9-1be9-45e6-b82d-09a956983615 · outbound

This paper cites Lora-ensemble: Efficient uncertainty modelling for self-attention networks.

Exploring the Rashomon Set for Concept-Based Models Lora-ensemble: Efficient uncertainty modelling for self-attention networks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:51.192581Z

Source-reported events for the cited work

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Observation da509acb-8c9b-4e25-8007-090cf2721bd5 · outbound

This paper cites Label-Free Concept Bottleneck Models.

Exploring the Rashomon Set for Concept-Based Models Label-Free Concept Bottleneck Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:51.329478Z

Source-reported events for the cited work

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Observation 6063fb56-25b7-4873-b8d4-5672ac4891c4 · outbound

This paper cites Learning multiple visual domains with residual adapters.

Exploring the Rashomon Set for Concept-Based Models Learning multiple visual domains with residual adapters

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:51.461545Z

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Observation 28992cee-9390-41da-abd2-3583fbea10fc · outbound

This paper cites MELoRA: Mini-Ensemble Low-Rank Adapters for Parameter-Efficient Fine-Tuning.

Exploring the Rashomon Set for Concept-Based Models MELoRA: Mini-Ensemble Low-Rank Adapters for Parameter-Efficient Fine-Tuning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:51.637493Z

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Observation da3a6a00-9357-4eef-9ce1-317d39eaa0b6 · outbound

This paper cites Amazing things come from having many good models.

Exploring the Rashomon Set for Concept-Based Models Amazing things come from having many good models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:51.757838Z

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Observation b6decb95-12f4-4dcc-a725-6450ce552459 · outbound

This paper cites On the ex- istence of simpler machine learning models.

Exploring the Rashomon Set for Concept-Based Models On the ex- istence of simpler machine learning models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:51.944122Z

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Observation 235aef1e-64a7-4944-8d87-c5da906140ae · outbound

This paper cites A path to simpler models starts with noise.Ad- vances in neural information processing systems, 36:3362– 3401, 2023.

Exploring the Rashomon Set for Concept-Based Models A path to simpler models starts with noise.Ad- vances in neural information processing systems, 36:3362– 3401, 2023

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:52.034656Z

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Observation 1664c983-782e-474e-bcf2-a638d6eca694 · outbound

This paper cites Diversity regularization in deep ensembles.

Exploring the Rashomon Set for Concept-Based Models Diversity regularization in deep ensembles

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:52.160825Z

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Observation 63a0ad9c-eaf8-4fb0-b034-2430fe0b56d2 · outbound

This paper cites Diverse Ensembles Improve Calibration.

Exploring the Rashomon Set for Concept-Based Models Diverse Ensembles Improve Calibration

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:52.302530Z

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Observation 820423b7-09be-4638-8dba-cf2510c4b7d3 · outbound

This paper cites El- liCE: Efficient and provably robust algorithmic recourse via the rashomon sets.

Exploring the Rashomon Set for Concept-Based Models El- liCE: Efficient and provably robust algorithmic recourse via the rashomon sets

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:52.498650Z

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Observation 1f6d9810-866d-461e-bc89-131eeb2c5d62 · outbound

This paper cites Stochastic Concept Bottleneck Models.

Exploring the Rashomon Set for Concept-Based Models Stochastic Concept Bottleneck Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:52.628274Z

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Observation c2780607-214a-4960-bce4-8857c2e6bffc · outbound

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Exploring the Rashomon Set for Concept-Based Models Unresolved cited work

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:52.827842Z

Source-reported events for the cited work

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Observation c41daff7-2212-4013-af7a-cc16b3733b5a · outbound

This paper cites Predictive multiplicity in probabilistic classification.

Exploring the Rashomon Set for Concept-Based Models Predictive multiplicity in probabilistic classification

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:53.028175Z

Source-reported events for the cited work

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Observation 98deea80-843c-4e8b-80fd-b0a1abd6e124 · outbound

This paper cites Decorrelating Structure via Adapters Makes Ensemble Learning Practical for Semi-supervised Learning.

Exploring the Rashomon Set for Concept-Based Models Decorrelating Structure via Adapters Makes Ensemble Learning Practical for Semi-supervised Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:53.198296Z

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Observation feb7f1c7-2ef1-4fe3-ac26-9e199839e02c · outbound

This paper cites Lampert, Bernt Schiele, and Zeynep Akata.

Exploring the Rashomon Set for Concept-Based Models Lampert, Bernt Schiele, and Zeynep Akata

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:53.362782Z

Source-reported events for the cited work

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Observation 10e520fa-67de-4e69-aea1-2b8be8b17df5 · outbound

This paper cites Exploring the whole rashomon set of sparse decision trees.Advances in neural information processing systems, 35:14071–14084, 2022.

Exploring the Rashomon Set for Concept-Based Models Exploring the whole rashomon set of sparse decision trees.Advances in neural information processing systems, 35:14071–14084, 2022

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:53.537261Z

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Observation 17dd9eb0-569b-42f6-a2d6-0b0a6f7929f8 · outbound

This paper cites Energy-based concept bottleneck models: Unifying predic- tion, concept intervention, and probabilistic interpretations.

Exploring the Rashomon Set for Concept-Based Models Energy-based concept bottleneck models: Unifying predic- tion, concept intervention, and probabilistic interpretations

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:53.702346Z

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Observation 7a87a103-9711-4764-b55d-5b98e5a94e9f · outbound

This paper cites The diversified ensemble neural network.

Exploring the Rashomon Set for Concept-Based Models The diversified ensemble neural network

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T20:33:53.819496Z

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Observation 59e6a855-e16b-45a1-8a3d-55c0b067c43c · outbound

This paper cites stripes” and “stalker.

Exploring the Rashomon Set for Concept-Based Models stripes” and “stalker

Reference 51

Resolution: malformed identifier; no resolver link, observed 2026-08-03T20:33:53.932064Z

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Pith citing papers

Observation 2fb46d6d-f41b-48dc-b7ee-2c1b6dd9329a · inbound

Position: Explainability Research Must Prioritize Foundations over Ad-hoc Methods cites this paper.

Position: Explainability Research Must Prioritize Foundations over Ad-hoc Methods Exploring the Rashomon Set for Concept-Based Models

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-02T10:46:55.114471Z

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