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Paper Citation Record · LEDGER

Scalable Explanation of Inferences on Large Graphs

As of 16 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:1908.06482.

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

pith.paper-citation-record.v1
1908.06482 v2

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:41:57.293081Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

51 of 51 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 284f70c0-f6bb-4619-a9da-ae6e67b9bb79 · outbound

This paper cites On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems.

Scalable Explanation of Inferences on Large Graphs On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems

Reference 1

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Observation 0fe74f50-87e9-45fc-bd5d-8ca127f8f374 · outbound

This paper cites How to explain individual classification decisions.

Scalable Explanation of Inferences on Large Graphs How to explain individual classification decisions

Reference 2

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Observation 8a7571db-a51c-4343-971a-e2fb12f0b90b · outbound

This paper cites Diverse m-best solutions in markov random fields.

Scalable Explanation of Inferences on Large Graphs Diverse m-best solutions in markov random fields

Reference 3

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Observation 94e61bd2-c5ec-4ad6-9b14-da38b912d6f8 · outbound

This paper cites Case-based explanation of non-case-based learning methods.

Scalable Explanation of Inferences on Large Graphs Case-based explanation of non-case-based learning methods

Reference 4

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Observation 366e5ae2-ced7-4fef-a031-327b3cf728a7 · outbound

This paper cites Sensitivity analysis in markov networks.

Scalable Explanation of Inferences on Large Graphs Sensitivity analysis in markov networks

Reference 5

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Observation ef11865d-8929-4fd3-a4c6-b5f4c2aeda25 · outbound

This paper cites Reading tea leaves: How humans interpret topic models.

Scalable Explanation of Inferences on Large Graphs Reading tea leaves: How humans interpret topic models

Reference 6

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Observation 73cf1b56-bbbc-4ed9-93b1-2a9e3f82c177 · outbound

This paper cites A differential approach to inference in bayesian networks.

Scalable Explanation of Inferences on Large Graphs A differential approach to inference in bayesian networks

Reference 7

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Observation edfe845b-8434-43f5-8757-90f061ca2031 · outbound

This paper cites Sparse inverse covariance estimation with the graphical lasso.

Scalable Explanation of Inferences on Large Graphs Sparse inverse covariance estimation with the graphical lasso

Reference 8

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Source-reported events for the cited work

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Observation 17e7c3d6-edd2-472b-aecf-5e4536458e12 · outbound

This paper cites Residual splash for optimally parallelizing belief propagation.

Scalable Explanation of Inferences on Large Graphs Residual splash for optimally parallelizing belief propagation

Reference 9

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Observation 77fa244e-e963-40c7-af24-6511f44cf92b · outbound

This paper cites European union regulations on algorithmic decision-making and a right to explanation.

Scalable Explanation of Inferences on Large Graphs European union regulations on algorithmic decision-making and a right to explanation

Reference 10

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Observation 7e54b94e-057f-4ebf-acf8-9493f54db9f8 · outbound

This paper cites An introduction to variable and feature selection.

Scalable Explanation of Inferences on Large Graphs An introduction to variable and feature selection

Reference 11

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Observation cb3ee1b9-2033-4db5-820e-c75b30c8b9bd · outbound

This paper cites Norm-product belief propa- gation: Primal-dual message-passing for approximate inference.

Scalable Explanation of Inferences on Large Graphs Norm-product belief propa- gation: Primal-dual message-passing for approximate inference

Reference 12

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Observation 44eb9c76-2892-4a0f-a59f-ce57279e3604 · outbound

This paper cites Variable selection for gaussian graphical models.

Scalable Explanation of Inferences on Large Graphs Variable selection for gaussian graphical models

Reference 13

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Observation ac3156a7-63b7-427f-b4e9-e19e70a3df18 · outbound

This paper cites An efficient network querying method based on conditional random fields.

Scalable Explanation of Inferences on Large Graphs An efficient network querying method based on conditional random fields

Reference 14

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Source-reported events for the cited work

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Observation 6d14f9d7-323c-4380-b2f5-8147f78287f7 · outbound

This paper cites Fast and scalable distributed loopy belief propagation on real-world graphs.

Scalable Explanation of Inferences on Large Graphs Fast and scalable distributed loopy belief propagation on real-world graphs

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 571c6362-fbb8-4496-a63f-01c254f83f09 · outbound

This paper cites Composing graphical models with neural networks for structured representations and fast in- ference.

Scalable Explanation of Inferences on Large Graphs Composing graphical models with neural networks for structured representations and fast in- ference

Reference 16

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation d383e8f8-f742-4ab3-ad56-0d204e568e89 · outbound

This paper cites Inference of beliefs on billion-scale graphs.

Scalable Explanation of Inferences on Large Graphs Inference of beliefs on billion-scale graphs

Reference 17

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Observation 818b2cbb-7503-4da1-8059-7e6d6d3bb537 · outbound

This paper cites Markov random fields and their applications.

Scalable Explanation of Inferences on Large Graphs Markov random fields and their applications

Reference 18

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Observation 430a3e46-d8f7-4339-8869-4ce36c8e1c2f · outbound

This paper cites Understanding black-box predictions via influence functions.

Scalable Explanation of Inferences on Large Graphs Understanding black-box predictions via influence functions

Reference 19

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Scalable Explanation of Inferences on Large Graphs Probabilistic graphical models: principles and techniques

Reference 20

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Observation 02356f4d-b04f-46bd-923f-d87469dcb1a3 · outbound

This paper cites Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models.

Scalable Explanation of Inferences on Large Graphs Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models

Reference 21

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Observation 8df47564-418d-496b-a6f3-02a1260566c9 · outbound

This paper cites An Evaluation of the Human-Interpretability of Explanation.

Scalable Explanation of Inferences on Large Graphs An Evaluation of the Human-Interpretability of Explanation

Reference 22

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Observation 5d3f8603-7b05-44fd-903f-60efded385c5 · outbound

This paper cites Rationalizing Neural Predictions.

Scalable Explanation of Inferences on Large Graphs Rationalizing Neural Predictions

Reference 23

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Scalable Explanation of Inferences on Large Graphs Protein– protein interaction site prediction based on conditional random fields

Reference 24

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Scalable Explanation of Inferences on Large Graphs The structure and function of explanations

Reference 25

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Scalable Explanation of Inferences on Large Graphs Intelligible models for classification and regression

Reference 26

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Scalable Explanation of Inferences on Large Graphs Reviews, reputation, and revenue: The case of yelp

Reference 27

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This paper cites The magical number seven, plus or minus two: Some limits on our capacity for processing information.

Scalable Explanation of Inferences on Large Graphs The magical number seven, plus or minus two: Some limits on our capacity for processing information

Reference 28

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Scalable Explanation of Inferences on Large Graphs Collective graph identification

Reference 29

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Scalable Explanation of Inferences on Large Graphs An analysis of approximations for maximizing submod- ular set functions

Reference 30

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Scalable Explanation of Inferences on Large Graphs An explanation mechanism for bayesian inferencing systems

Reference 31

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Observation 5b0108f0-12e5-4fe6-9a2e-0251f0de413b · outbound

This paper cites Probabilistic reasoning in intelligent systems: networks of plausible inference.

Scalable Explanation of Inferences on Large Graphs Probabilistic reasoning in intelligent systems: networks of plausible inference

Reference 32

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Observation 9d8a14e8-e0a3-4553-8b4b-2ace7fda3737 · outbound

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Scalable Explanation of Inferences on Large Graphs Deepwalk: Online learning of social representations

Reference 33

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Scalable Explanation of Inferences on Large Graphs Collective opinion spam detection: Bridging review networks and metadata

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Scalable Explanation of Inferences on Large Graphs Why should i trust you?: Explaining the predictions of any classifier

Reference 35

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Observation ee21ac19-aa0d-4784-9b37-71ea4895fd73 · outbound

This paper cites Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations.

Scalable Explanation of Inferences on Large Graphs Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations

Reference 36

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Unavailable: canonical work link unavailable.

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Observation d9c0ac30-7260-4ac4-8844-9bd2f0ff847f · outbound

This paper cites Efficient Search for Diverse Coherent Explanations.

Scalable Explanation of Inferences on Large Graphs Efficient Search for Diverse Coherent Explanations

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:41:57.366483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 6b888dd5-220f-4e46-9308-7903d3c9a3ee · outbound

This paper cites Constructing the call graph of a pro- gram.

Scalable Explanation of Inferences on Large Graphs Constructing the call graph of a pro- gram

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.593439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.238082Z digest=sha256:4c198fa705f598a6bae926667a6e5d1f05f21088f73cd6e28daa413221579480

Observation a2a65e5e-e0e2-451a-9013-cf3abdd9d320 · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Scalable Explanation of Inferences on Large Graphs Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-14T13:41:57.242447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:41:57.242447Z digest=sha256:e562818724114a0a768f08af72e0673d19c6bb99481c0a94565155e93c64544f

Observation 99d22b3e-9bc1-4af3-a559-9de671efbf48 · outbound

This paper cites Integrating rich user feedback into intelligent user interfaces.

Scalable Explanation of Inferences on Large Graphs Integrating rich user feedback into intelligent user interfaces

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.577850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.247239Z digest=sha256:3a1a29f31d2830c711bef452d47cdad71f937bc51026a35a13f46f92943d9153

Observation 6721c856-7964-4f38-a2d5-c26d47616676 · outbound

This paper cites Explanation in bayesian belief networks.

Scalable Explanation of Inferences on Large Graphs Explanation in bayesian belief networks

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.563168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.251860Z digest=sha256:871018f56441cadb601dd93f260aeca26732a9c9a4d028132ab9dbbbcefc3ab6

Observation 66c9ac26-0244-490c-966e-88153caca60b · outbound

This paper cites An introduction to conditional random fields.

Scalable Explanation of Inferences on Large Graphs An introduction to conditional random fields

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.548528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.256362Z digest=sha256:236eacefa613992bc8d19eaac13aa3f50dd21215921a269c6af48cffba60af94

Observation 83ca9146-2fd6-4c70-a491-e87b6903664b · outbound

This paper cites Relational learning via latent social dimensions.

Scalable Explanation of Inferences on Large Graphs Relational learning via latent social dimensions

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.533672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 610a2881-9eee-4edc-8434-9ea77e8e20f4 · outbound

This paper cites Learning to infer social ties in large networks.

Scalable Explanation of Inferences on Large Graphs Learning to infer social ties in large networks

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.518267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.265358Z digest=sha256:918b54f943ad5cf9c03fb52f264f91914000da56625bf06bc478d4c5038b583b

Observation 2dcace2f-17b6-4c00-b3d1-9e06be1cb9fe · outbound

This paper cites An analysis of physi- cian attitudes regarding computer-based clinical consultation systems.

Scalable Explanation of Inferences on Large Graphs An analysis of physi- cian attitudes regarding computer-based clinical consultation systems

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.501108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.269905Z digest=sha256:2abe5e12f01dfa747b5cacd59ec9cc0b6871d980b3c3b0ad66a6b0c9ec443777

Observation d8ab04e5-50e9-4401-b7c7-a0a6a93da7cb · outbound

This paper cites Counter- factual explanations without opening the black box: Automated decisions and the gpdr.

Scalable Explanation of Inferences on Large Graphs Counter- factual explanations without opening the black box: Automated decisions and the gpdr

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.485674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.274392Z digest=sha256:362f32d9bb01b904c15e708afa0979f42e57294953e6c97cd03c606ea67192ff

Observation cd0cb393-7772-4241-8c9a-8fa15209e723 · outbound

This paper cites influence sketching: Finding influential samples in large-scale regressions.

Scalable Explanation of Inferences on Large Graphs influence sketching: Finding influential samples in large-scale regressions

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.470217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.279102Z digest=sha256:3abe7c2b8ab022c98f5604d5158d6e1f91bd7343ee048f268bc5296283f7ab00

Observation b79d283a-2fd2-47b2-a270-bb128a1507d0 · outbound

This paper cites Linear program- ming relaxations and belief propagation–an empirical study.

Scalable Explanation of Inferences on Large Graphs Linear program- ming relaxations and belief propagation–an empirical study

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.455140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.283806Z digest=sha256:f6e10ae67112d489978a98be5ef75f2f4e4051b144d02128d46d6b6867f6ea94

Observation a1cf0203-bdcc-40c8-a597-11b2ddd6b38e · outbound

This paper cites Smoke Screener or Straight Shooter: Detecting Elite Sybil Attacks in User-Review Social Networks.

Scalable Explanation of Inferences on Large Graphs Smoke Screener or Straight Shooter: Detecting Elite Sybil Attacks in User-Review Social Networks

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-14T13:41:57.288103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:41:57.288103Z digest=sha256:584a33c4e41fe0535f05d1751dd05c369a6ed859e748365c6bc4be1fa34325f5

Observation 2297024d-e6ea-4483-904b-0e1bacdfdabd · outbound

This paper cites Predicting multicellular function through multi-layer tissue networks.

Scalable Explanation of Inferences on Large Graphs Predicting multicellular function through multi-layer tissue networks

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:41:57.440448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.293081Z digest=sha256:1dceed320d0eb844092a999bbb58eabbab77f67c5baf92b570feba8625a2792d

Observation 592850fb-5225-45fc-98b8-b1aa08214201 · outbound

This paper cites an unresolved cited work.

Scalable Explanation of Inferences on Large Graphs Unresolved cited work

Reference 212

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:41:58.002052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T13:41:57.083937Z digest=sha256:24ea6a2cd8f2000fb1b366da804ffd8b01adafaa68b6449d62857d68bbd01f79

Pith citing papers

No inbound Pith citation observations are available.