Paper Citation Record · LEDGER

Weak Supervision for Real World Graphs

As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2506.02451.

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

pith.paper-citation-record.v1
2506.02451 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:26:49.490578Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

45 of 45 outbound references displayed

verified exact3
verified fuzzy36
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8bf454c8-e1d5-4ef9-b35e-86d52b4c72d8 · outbound

This paper cites Kipf and Max Welling.

Weak Supervision for Real World Graphs Kipf and Max Welling

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:46.262043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a16b5b6-4d12-45ff-8412-2c07064bea1e · outbound

This paper cites Graph attention networks.

Weak Supervision for Real World Graphs Graph attention networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:56.248110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6f37c9ef-9855-4d52-a98d-aab663a408dc · outbound

This paper cites Multi-stage self-supervised learning for graph convolutional networks on graphs with few labeled nodes.

Weak Supervision for Real World Graphs Multi-stage self-supervised learning for graph convolutional networks on graphs with few labeled nodes

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:56.119060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ca9ab240-4e83-4f40-a85b-03218c7973ff · outbound

This paper cites Effective Stabilized Self-Training on Few-Labeled Graph Data.

Weak Supervision for Real World Graphs Effective Stabilized Self-Training on Few-Labeled Graph Data

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:26:50.050041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4ab1a447-6106-4e7b-bbbb-b27144c026a9 · outbound

This paper cites T-net: Weakly supervised graph learning for combatting human trafficking.

Weak Supervision for Real World Graphs T-net: Weakly supervised graph learning for combatting human trafficking

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:56.031539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 31a25d81-e7f2-4456-a117-1d1106c720e7 · outbound

This paper cites Scaling up fact-checking using the wisdom of crowds.

Weak Supervision for Real World Graphs Scaling up fact-checking using the wisdom of crowds

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.903293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3053a621-fd1f-40b1-b040-d9236f58a9e6 · outbound

This paper cites Justice in misinformation detection systems: An analysis of algorithms, stakeholders, and potential harms.

Weak Supervision for Real World Graphs Justice in misinformation detection systems: An analysis of algorithms, stakeholders, and potential harms

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.771817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 20cdf1e5-9468-4807-b45f-c738df2f9a85 · outbound

This paper cites Data programming: Creating large training sets, quickly.

Weak Supervision for Real World Graphs Data programming: Creating large training sets, quickly

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.654725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 33105a9c-5153-4ce7-9151-39b6f8e30765 · outbound

This paper cites Learning hyper label model for programmatic weak supervision.

Weak Supervision for Real World Graphs Learning hyper label model for programmatic weak supervision

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.548001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0e4f4821-380b-4bb7-8645-caae6ca96d3f · outbound

This paper cites Bigbio: a framework for data-centric biomedical natural language processing.

Weak Supervision for Real World Graphs Bigbio: a framework for data-centric biomedical natural language processing

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.433543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 42c668c4-c3c9-4b16-8198-7bff85c457e3 · outbound

This paper cites Resonant anomaly detection with multiple reference datasets.

Weak Supervision for Real World Graphs Resonant anomaly detection with multiple reference datasets

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.321397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a95d902f-7e80-47a7-b1f5-9c8aafaaebf0 · outbound

This paper cites Hamilton, Pietro Liò, Yoshua Bengio, and R Devon Hjelm.

Weak Supervision for Real World Graphs Hamilton, Pietro Liò, Yoshua Bengio, and R Devon Hjelm

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.172421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6abc4766-31ab-4a58-a167-97408ceee087 · outbound

This paper cites Supervised Contrastive Learning.

Weak Supervision for Real World Graphs Supervised Contrastive Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:47.062630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a110723f-76f8-44cc-8d1c-3c22a13d06c1 · outbound

This paper cites Clusterscl: cluster-aware supervised contrastive learning on graphs.

Weak Supervision for Real World Graphs Clusterscl: cluster-aware supervised contrastive learning on graphs

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:55.057570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 92637ce7-3214-45b1-9394-3832c7390272 · outbound

This paper cites Automating the construction of internet portals with machine learning.

Weak Supervision for Real World Graphs Automating the construction of internet portals with machine learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.965481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0e1ffc22-5c19-445d-a1f6-11f7945124be · outbound

This paper cites liar, liar pants on fire.

Weak Supervision for Real World Graphs liar, liar pants on fire

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.816190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2e8b8e2d-43f4-4bcc-b6c1-510c5ac2ddbd · outbound

This paper cites A Survey on Programmatic Weak Supervision.

Weak Supervision for Real World Graphs A Survey on Programmatic Weak Supervision

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:47.432114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b14f9325-42d4-4684-b068-a061ebd98151 · outbound

This paper cites Training complex models with multi-task weak supervision.

Weak Supervision for Real World Graphs Training complex models with multi-task weak supervision

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.641332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ceb63db0-fe59-448b-a70f-78dbf800b389 · outbound

This paper cites Multi-resolution weak supervision for sequential data.

Weak Supervision for Real World Graphs Multi-resolution weak supervision for sequential data

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.486778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fb45f4d7-75b6-40e6-b7eb-7dbdaef7aedc · outbound

This paper cites Fast and three-rious: Speeding up weak supervision with triplet methods.

Weak Supervision for Real World Graphs Fast and three-rious: Speeding up weak supervision with triplet methods

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.363305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9accfc0a-892a-4e7b-8cdc-78fd9ff1e514 · outbound

This paper cites NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs.

Weak Supervision for Real World Graphs NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:26:49.855554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 65b3c965-bfff-4ebc-906f-0ed9bb88e5e9 · outbound

This paper cites Noise-robust graph learning by estimating and leveraging pairwise interactions.

Weak Supervision for Real World Graphs Noise-robust graph learning by estimating and leveraging pairwise interactions

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.229552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 19e3312e-80f7-41cd-a021-941bf67f8e7a · outbound

This paper cites Learning on graphs under label noise.

Weak Supervision for Real World Graphs Learning on graphs under label noise

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.166914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 755e6f53-6186-42ed-b2c2-91bf3f347540 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Weak Supervision for Real World Graphs A simple framework for contrastive learning of visual representations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.115730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9218f044-8bc2-4a08-8362-84c4a97b7322 · outbound

This paper cites Graph contrastive learning with augmentations.

Weak Supervision for Real World Graphs Graph contrastive learning with augmentations

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:54.031577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0e6b676e-b58c-46ff-90dd-ae78e9721aa7 · outbound

This paper cites Contrastive multi-view representation learning on graphs.

Weak Supervision for Real World Graphs Contrastive multi-view representation learning on graphs

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:53.886534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 04b7a613-b6ca-4987-bbeb-00db2904449e · outbound

This paper cites Deep graph contrastive representation learning.

Weak Supervision for Real World Graphs Deep graph contrastive representation learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:53.641196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 34737c25-8f0b-4ed4-a191-aca539c687aa · outbound

This paper cites CSGCL: Community-Strength-Enhanced Graph Contrastive Learning.

Weak Supervision for Real World Graphs CSGCL: Community-Strength-Enhanced Graph Contrastive Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:48.298293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd38ee4c-fe2c-4d1a-a0ac-6a5d052c07b2 · outbound

This paper cites Graph contrastive learning with adaptive augmentation.

Weak Supervision for Real World Graphs Graph contrastive learning with adaptive augmentation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:53.435040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7374fc40-f4b0-418b-bb55-74a587bf9b47 · outbound

This paper cites Large-scale representation learning on graphs via bootstrapping.

Weak Supervision for Real World Graphs Large-scale representation learning on graphs via bootstrapping

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:53.235080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation af15549d-85c4-4ab3-afac-5bc75b98758d · outbound

This paper cites Graph Representation Learning via Graphical Mutual Information Maximization.

Weak Supervision for Real World Graphs Graph Representation Learning via Graphical Mutual Information Maximization

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:53.083184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 341bbd93-b9e2-4817-a525-ee04108c921e · outbound

This paper cites Simple unsupervised graph representation learning.

Weak Supervision for Real World Graphs Simple unsupervised graph representation learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:52.886757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b7617a91-bded-4ee3-b741-4e9ee06df7c9 · outbound

This paper cites Augmentation-free graph contrastive learning of invariant-discriminative representations.IEEE Transactions on Neural Networks and Learning Systems, 2023.

Weak Supervision for Real World Graphs Augmentation-free graph contrastive learning of invariant-discriminative representations.IEEE Transactions on Neural Networks and Learning Systems, 2023

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:52.631432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 93588fd6-3645-479d-bed5-6465c7a10220 · outbound

This paper cites Kefato and Sarunas Girdzijauskas.

Weak Supervision for Real World Graphs Kefato and Sarunas Girdzijauskas

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:52.376420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5da0234f-9359-40c3-890e-0fbb7c35b385 · outbound

This paper cites Jgcl: Joint self-supervised and supervised graph contrastive learning.

Weak Supervision for Real World Graphs Jgcl: Joint self-supervised and supervised graph contrastive learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:52.112615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1341c78b-194e-4e2d-910c-2c42fab46102 · outbound

This paper cites Weakly supervised contrastive learning.

Weak Supervision for Real World Graphs Weakly supervised contrastive learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:51.784031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 28c207a5-7d6b-42d8-a924-619208136816 · outbound

This paper cites Rethinking Weak Supervision in Helping Contrastive Learning.

Weak Supervision for Real World Graphs Rethinking Weak Supervision in Helping Contrastive Learning

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:26:49.664556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 799645f8-90dd-45f9-a1c2-6247721260c8 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Weak Supervision for Real World Graphs Representation Learning with Contrastive Predictive Coding

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:49.034679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68c918df-ff57-40f1-9f67-aaf1d21ef192 · outbound

This paper cites Combating misinformation in the age of llms: Opportunities and challenges.

Weak Supervision for Real World Graphs Combating misinformation in the age of llms: Opportunities and challenges

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:51.508600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 58c35708-d600-4be0-852e-d786bb22f997 · outbound

This paper cites Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4.

Weak Supervision for Real World Graphs Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:49.145945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0ef18c1-e582-4dbd-bdec-890197d3edab · outbound

This paper cites Citeseer: An automatic citation indexing system.

Weak Supervision for Real World Graphs Citeseer: An automatic citation indexing system

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:51.186034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 34db01c6-e89d-4461-8da9-beb48d52d925 · outbound

This paper cites Hyperbolic graph convolutional neural networks.

Weak Supervision for Real World Graphs Hyperbolic graph convolutional neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:50.910141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 23b256fb-a389-4b84-8871-a771190e973d · outbound

This paper cites Microsoft academic graph: When experts are not enough.

Weak Supervision for Real World Graphs Microsoft academic graph: When experts are not enough

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:50.608674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 816cf4c0-34be-4c5e-9883-1d5a9db1ee9f · outbound

This paper cites Image-based recommendations on styles and substitutes.

Weak Supervision for Real World Graphs Image-based recommendations on styles and substitutes

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:50.404468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 91122ac3-2fa2-4488-9fff-77e88fff57f5 · outbound

This paper cites Graphmix: Improved training of gnns for semi-supervised learning.

Weak Supervision for Real World Graphs Graphmix: Improved training of gnns for semi-supervised learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:26:50.218641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.