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Paper Citation Record · LEDGER

Beyond Accuracy: Measuring Logical Compliance of Predictive Models

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2606.20208.

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

pith.paper-citation-record.v1
2606.20208 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T17:30:46.782503Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

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  • verified fuzzy0
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

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Outbound references

Observation f132effb-5996-4ad1-9ee7-bc58083f71ec · outbound

This paper cites Freebase: a collaboratively created graph database for structuring human knowledge.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Freebase: a collaboratively created graph database for structuring human knowledge

Reference 1

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Observation 89560d7c-0b91-4563-824a-e17147391977 · outbound

This paper cites Translating embeddings for modeling multi-relational data.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Translating embeddings for modeling multi-relational data

Reference 2

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Observation 2587a0d0-a2b6-46d6-bcce-213ee57827c1 · outbound

This paper cites Kanatsoulis, and Jure Leskovec.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Kanatsoulis, and Jure Leskovec

Reference 3

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Observation 75cfc144-0055-4282-b87a-dd779df32538 · outbound

This paper cites Uniker: A unified framework for combining embedding and definite horn rule reasoning for knowledge graph inference.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Uniker: A unified framework for combining embedding and definite horn rule reasoning for knowledge graph inference

Reference 4

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Observation 3a586d7e-d037-44fe-b34e-3127da2a871f · outbound

This paper cites Warrens, and Giuseppe Jurman.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Warrens, and Giuseppe Jurman

Reference 5

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source=pdf_text observed=2026-06-26T17:30:46.782503Z digest=sha256:ddea2ac146dfc0b2af4d79d969d4cd71a44fb0a56571866a66ccff4d750400d4

Observation abf2ee11-b15c-475f-9659-de0d3aed78f1 · outbound

This paper cites A comparative anal- ysis of neurosymbolic methods for link prediction.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models A comparative anal- ysis of neurosymbolic methods for link prediction

Reference 6

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Observation 3d880f35-0237-4fbf-a261-d74a21340f20 · outbound

This paper cites Denham.The Detection of Patterns in Alyawarra Nonverbal Behavior.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Denham.The Detection of Patterns in Alyawarra Nonverbal Behavior

Reference 7

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Observation 754d1efa-b8c3-4068-a13b-aff48afdc9ee · outbound

This paper cites An introduction to ROC analysis.Pattern Recognition Letters, 27(8):861–874, 2006.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models An introduction to ROC analysis.Pattern Recognition Letters, 27(8):861–874, 2006

Reference 8

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Observation ea9f7ea7-740f-48e3-9e13-cffcab15f005 · outbound

This paper cites Dv3f - donnée pour l’analyse des marchés fonciers et immobiliers.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Dv3f - donnée pour l’analyse des marchés fonciers et immobiliers

Reference 9

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Observation 40e7f881-0af7-4c44-910d-13188385c746 · outbound

This paper cites Suchanek.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Suchanek

Reference 10

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Observation 9bd34922-4acf-47ca-b01e-e9722747c055 · outbound

This paper cites RelBench v2: A Large-Scale Benchmark and Repository for Relational Data.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models RelBench v2: A Large-Scale Benchmark and Repository for Relational Data

Reference 11

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 968dd697-1f63-42bd-a09d-d069c1e0089c · outbound

This paper cites Inductive representation learning on large graphs.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Inductive representation learning on large graphs

Reference 12

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Observation fe703973-c8cb-4f41-866c-01c032bdfc2d · outbound

This paper cites Sem@k: Is my knowl- edge graph embedding model semantic-aware? Conference on Empirical Methods in Natural Language Processing, 2023.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Sem@k: Is my knowl- edge graph embedding model semantic-aware? Conference on Empirical Methods in Natural Language Processing, 2023

Reference 13

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Observation 63421415-8b57-4bf4-99a7-480327b85afe · outbound

This paper cites McDermott, Haoran Zhang, Lasse Hyldig Hansen, Giovanni Angelotti, and Jack Gallifant.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models McDermott, Haoran Zhang, Lasse Hyldig Hansen, Giovanni Angelotti, and Jack Gallifant

Reference 14

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Observation fe56bc08-282f-4b0c-82eb-819dcd690df9 · outbound

This paper cites Anytime bottom-up rule learning for large-scale knowledge graph completion: C.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Anytime bottom-up rule learning for large-scale knowledge graph completion: C

Reference 15

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Observation 50bebc45-003d-43b3-adfd-e1b2bf85ca11 · outbound

This paper cites an unresolved cited work.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Unresolved cited work

Reference 16

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Observation 25e617ed-b8b3-4ef6-9fc6-5e1a9fc62434 · outbound

This paper cites Evaluation: From precision, recall and f-measure to roc, informedness, marked- ness & correlation.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Evaluation: From precision, recall and f-measure to roc, informedness, marked- ness & correlation

Reference 17

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Observation 24e7a133-7806-47d0-acd2-11179fcc167a · outbound

This paper cites an unresolved cited work.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Unresolved cited work

Reference 18

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Observation abe0ba93-1972-4da3-a57c-f001eafe5a14 · outbound

This paper cites The precision-recall plot is more informative than the roc plot when evaluating binary classifiers on imbalanced datasets.PLOS ONE, 10(3):e0118432, 2015.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models The precision-recall plot is more informative than the roc plot when evaluating binary classifiers on imbalanced datasets.PLOS ONE, 10(3):e0118432, 2015

Reference 19

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Observation e37408ac-7a95-4689-ac06-bbecd6da2730 · outbound

This paper cites A systematic analysis of performance measures for clas- sification tasks.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models A systematic analysis of performance measures for clas- sification tasks

Reference 20

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Observation 8f7d705d-0ee3-43d8-9842-dbb2cd796cc0 · outbound

This paper cites Observed versus latent features for knowledge base and text inference.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Observed versus latent features for knowledge base and text inference

Reference 21

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Observation ed74f73f-f622-4c0f-9734-5123959b3688 · outbound

This paper cites Composition-based Multi-Relational Graph Convolutional Networks.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Composition-based Multi-Relational Graph Convolutional Networks

Reference 22

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Source-reported events for the cited work

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Observation 7931d5b2-a670-4f50-9d5b-0a5e43adedef · outbound

This paper cites Willmott and Kenji Matsuura.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Willmott and Kenji Matsuura

Reference 23

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Observation 53c3ca54-96c5-4bc5-bffc-9e4cf9b75918 · outbound

This paper cites Large language models are good rela- tional learners.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Large language models are good rela- tional learners

Reference 24

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Observation 2279d97f-983e-4045-8230-0eb49c695815 · outbound

This paper cites A semantic loss function for deep learning with symbolic knowledge.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models A semantic loss function for deep learning with symbolic knowledge

Reference 25

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Observation 11f7f1e9-5c2d-435e-87fc-1a3579ecc192 · outbound

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Beyond Accuracy: Measuring Logical Compliance of Predictive Models Unresolved cited work

Reference 26

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Observation e66e8aab-9b9b-4354-b4d9-a6434a154a27 · outbound

This paper cites Efficient probabilistic logic reasoning with graph neural networks.ICLR, February 2020.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Efficient probabilistic logic reasoning with graph neural networks.ICLR, February 2020

Reference 27

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Observation 94f0f5b6-c9c4-466f-b7df-565ea0727ba7 · outbound

This paper cites Neural bellman-ford networks: a general graph neural network framework for link prediction.

Beyond Accuracy: Measuring Logical Compliance of Predictive Models Neural bellman-ford networks: a general graph neural network framework for link prediction

Reference 28

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Pith citing papers

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