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Paper Citation Record · LEDGER

Semi-Supervised Learning using Differentiable Reasoning

As of 17 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:1908.04700.

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

pith.paper-citation-record.v1
1908.04700 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:38:13.001450Z

measured 33 of 33 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

33 of 33 outbound references displayed

  • verified exact1
  • verified fuzzy27
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afa9d83e-ea6e-4f66-bab9-d58a06e7be15 · outbound

This paper cites An introduction to many-valued and fuzzy logic: semantics, algebras, and derivation systems.

Semi-Supervised Learning using Differentiable Reasoning An introduction to many-valued and fuzzy logic: semantics, algebras, and derivation systems

Reference 1

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verified fuzzy
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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 d25bb85f-3964-4d60-bc29-50959211367e · outbound

This paper cites Semi-supervised learning.

Semi-Supervised Learning using Differentiable Reasoning Semi-supervised learning

Reference 2

Resolution
verified fuzzy
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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 82674087-2be7-4a65-b22f-efa99b1506e9 · outbound

This paper cites Detect what you can: Detecting and representing objects using holistic models and body parts.

Semi-Supervised Learning using Differentiable Reasoning Detect what you can: Detecting and representing objects using holistic models and body parts

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.313882Z

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 5b4608d1-b9e0-4da0-b477-eff237ddcc59 · outbound

This paper cites SDD: A new canonical representation of propositional knowledge bases.

Semi-Supervised Learning using Differentiable Reasoning SDD: A new canonical representation of propositional knowledge bases

Reference 4

Resolution
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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 dc958c30-5956-4694-80b3-3c6f61d45145 · outbound

This paper cites Lifted rule injection for relation embeddings.

Semi-Supervised Learning using Differentiable Reasoning Lifted rule injection for relation embeddings

Reference 5

Resolution
verified fuzzy
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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 9841ae6c-9be4-4c91-9438-f8c1651c2174 · outbound

This paper cites Regularizing relation representa- tions by first-order implications.

Semi-Supervised Learning using Differentiable Reasoning Regularizing relation representa- tions by first-order implications

Reference 6

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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 1d7af21c-2fdf-44d3-83bc-0e9502613876 · outbound

This paper cites d’Avila Garcez.

Semi-Supervised Learning using Differentiable Reasoning d’Avila Garcez

Reference 7

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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 a1068c5e-38c0-406b-bfa0-87829c94179a · outbound

This paper cites Indicative conditionals.

Semi-Supervised Learning using Differentiable Reasoning Indicative conditionals

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.268027Z

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 157b6446-6043-4657-8417-b2f2fa870213 · outbound

This paper cites Fast r-cnn.

Semi-Supervised Learning using Differentiable Reasoning Fast r-cnn

Reference 9

Resolution
verified fuzzy
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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 eaa530b5-a251-4c1c-8679-84cdcb362a7b · outbound

This paper cites Studies in the logic of confirmation (i.).

Semi-Supervised Learning using Differentiable Reasoning Studies in the logic of confirmation (i.)

Reference 10

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verified fuzzy
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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 faff8743-5203-475c-82b9-1ea4b00e060c · outbound

This paper cites Harnessing deep neural networks with logic rules.

Semi-Supervised Learning using Differentiable Reasoning Harnessing deep neural networks with logic rules

Reference 11

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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 13615a68-4e48-4709-bbba-8264f98b4982 · outbound

This paper cites Fuzzy Implications, volume 231.

Semi-Supervised Learning using Differentiable Reasoning Fuzzy Implications, volume 231

Reference 12

Resolution
verified fuzzy
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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 221f3234-8031-40fe-84f7-ad04204b6f52 · outbound

This paper cites Image retrieval using scene graphs.

Semi-Supervised Learning using Differentiable Reasoning Image retrieval using scene graphs

Reference 13

Resolution
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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 17b680a4-f175-4eff-8887-c68ced9c4d36 · outbound

This paper cites Semi-supervised classification with graph convolutional networks.

Semi-Supervised Learning using Differentiable Reasoning Semi-supervised classification with graph convolutional networks

Reference 14

Resolution
verified fuzzy
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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 29bff6b4-50d1-44c5-9b59-a88fecfe00bb · outbound

This paper cites Visual genome: Connecting 14 DIFFERENTIABLE REASONING language and vision using crowdsourced dense image annotations.

Semi-Supervised Learning using Differentiable Reasoning Visual genome: Connecting 14 DIFFERENTIABLE REASONING language and vision using crowdsourced dense image annotations

Reference 15

Resolution
verified fuzzy
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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 ded2292c-a1ad-440d-be77-10265bd4d0a0 · outbound

This paper cites Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks.

Semi-Supervised Learning using Differentiable Reasoning Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks

Reference 16

Resolution
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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 8d104485-9930-4967-89dc-ef4a41c35f4c · outbound

This paper cites DeepProbLog: Neural Probabilistic Logic Programming.

Semi-Supervised Learning using Differentiable Reasoning DeepProbLog: Neural Probabilistic Logic Programming

Reference 17

Resolution
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no resolver link, observed 2026-08-14T13:38:12.951792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8321c1f4-7838-457a-9051-414b6c3988a9 · outbound

This paper cites an unresolved cited work.

Semi-Supervised Learning using Differentiable Reasoning Unresolved cited work

Reference 18

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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 46e0f598-44d4-4f90-a53d-383864ae4e1a · outbound

This paper cites Cubuk, and Ian J.

Semi-Supervised Learning using Differentiable Reasoning Cubuk, and Ian J

Reference 19

Resolution
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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 0e021187-c0a5-43ad-8f1e-a926f24da004 · outbound

This paper cites Combining Representation Learning with Logic for Language Processing.

Semi-Supervised Learning using Differentiable Reasoning Combining Representation Learning with Logic for Language Processing

Reference 20

Resolution
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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 57461bda-f6c3-47e5-b81d-cc4e2ab5d205 · outbound

This paper cites End-to-end differentiable proving.

Semi-Supervised Learning using Differentiable Reasoning End-to-end differentiable proving

Reference 21

Resolution
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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 d6f481c3-bc78-44aa-9103-521fdb58b4a1 · outbound

This paper cites Injecting logical background knowl- edge into embeddings for relation extraction.

Semi-Supervised Learning using Differentiable Reasoning Injecting logical background knowl- edge into embeddings for relation extraction

Reference 22

Resolution
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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 f1d8d629-026d-40d2-bdb4-c6ca240b2431 · outbound

This paper cites On the hardness of approximate reasoning.

Semi-Supervised Learning using Differentiable Reasoning On the hardness of approximate reasoning

Reference 23

Resolution
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raw_fallback, observed 2026-08-14T13:38:13.143906Z

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 bb310d57-04ae-4f2f-970d-d9b6e277f7c2 · outbound

This paper cites Berg, and Li Fei-Fei.

Semi-Supervised Learning using Differentiable Reasoning Berg, and Li Fei-Fei

Reference 24

Resolution
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no resolver link, observed 2026-08-14T13:38:12.974272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f51ab02b-56e4-4840-a828-5901dbbe92a3 · outbound

This paper cites Modeling Relational Data with Graph Convolutional Networks.

Semi-Supervised Learning using Differentiable Reasoning Modeling Relational Data with Graph Convolutional Networks

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.129506Z

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=2026-08-14T13:38:12.977210Z digest=sha256:0eb4459ba3dc6bce2d6d74a8fd0d3b7a11efdb98eb3c88f8385094cb256a3a28

Observation 4e84de0b-b68c-4018-abee-b05c668f2ee1 · outbound

This paper cites Logic tensor networks: Deep learning and logical reasoning from data and knowledge.

Semi-Supervised Learning using Differentiable Reasoning Logic tensor networks: Deep learning and logical reasoning from data and knowledge

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.119974Z

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=2026-08-14T13:38:12.980288Z digest=sha256:8e362bda44e46966101452f7ba5dd5ae090ad82e51a956ba67ce1be2d6203f4b

Observation 7a6e393a-da7f-439c-b172-7a2efa2c8d83 · outbound

This paper cites Reasoning with neural tensor networks for knowledge base completion.

Semi-Supervised Learning using Differentiable Reasoning Reasoning with neural tensor networks for knowledge base completion

Reference 27

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no resolver link, observed 2026-08-14T13:38:12.983249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:38:12.983249Z digest=sha256:dfed58c67bd484146e784579a393eac0427d196096cb3e2e784a073adeaa8615

Observation e88bf1a9-1984-4d9e-b38a-136e598a53af · outbound

This paper cites Logic and structure.

Semi-Supervised Learning using Differentiable Reasoning Logic and structure

Reference 28

Resolution
verified fuzzy
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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 71c82d88-d250-463a-9012-04a313316f9e · outbound

This paper cites an unresolved cited work.

Semi-Supervised Learning using Differentiable Reasoning Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-14T13:38:13.095078Z

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 4bab5fa4-f439-4e21-827b-540db18d72f9 · outbound

This paper cites The effect of class distribution on classifier learning: an empirical study.

Semi-Supervised Learning using Differentiable Reasoning The effect of class distribution on classifier learning: an empirical study

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.085175Z

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=2026-08-14T13:38:12.992229Z digest=sha256:5cfc984a8c241924776dd9543b450a18c83fe17aca0a3ee12437b9666bd7016a

Observation b2047430-7f88-4186-94fd-ae4cd5f44ca3 · outbound

This paper cites A semantic 15 VAN KRIEKEN , ACAR AND VAN HARMELEN loss function for deep learning with symbolic knowledge.

Semi-Supervised Learning using Differentiable Reasoning A semantic 15 VAN KRIEKEN , ACAR AND VAN HARMELEN loss function for deep learning with symbolic knowledge

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.075353Z

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=2026-08-14T13:38:12.995343Z digest=sha256:88e19bb2f771c4681616891d53912e76dd3fa03241d6a2d348fe7d93e6bca7da

Observation 01083f31-db7c-4dc7-93eb-c2fe28d5ae01 · outbound

This paper cites Cohen, and Ruslan Salakhutdinov.

Semi-Supervised Learning using Differentiable Reasoning Cohen, and Ruslan Salakhutdinov

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.065295Z

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=2026-08-14T13:38:12.998305Z digest=sha256:24918cb5604889681c7379b9f94e30e548d6c65cf927b95528bd8504e5da9666

Observation baaecd44-bf12-47c3-ae95-231bcd3f9eb1 · outbound

This paper cites Semi-supervised learning using gaussian fields and harmonic functions.

Semi-Supervised Learning using Differentiable Reasoning Semi-supervised learning using gaussian fields and harmonic functions

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:38:13.055617Z

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=2026-08-14T13:38:13.001450Z digest=sha256:e3135c7173138bd066c2b3e8813744a0ffc1dcacfd4df033456d8ef55deb1557

Pith citing papers

No inbound Pith citation observations are available.