Paper Citation Record · LEDGER

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering

As of 13 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.14867.

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

pith.paper-citation-record.v1
2412.14867 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:55:32.848128Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

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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

43 of 43 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8334359c-ff6a-45dc-8c0d-356ed95a04fc · outbound

This paper cites Regularized bi-directional co-clustering.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Regularized bi-directional co-clustering

Reference 1

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This paper cites A semi-nmf-pca unified framework for data clustering.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering A semi-nmf-pca unified framework for data clustering

Reference 2

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This paper cites Simultaneous spectral data embedding and clustering.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Simultaneous spectral data embedding and clustering

Reference 3

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This paper cites k-means++: The advantages of careful seeding.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering k-means++: The advantages of careful seeding

Reference 4

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This paper cites A dendrite method for cluster analysis.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering A dendrite method for cluster analysis

Reference 5

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This paper cites H., T ANG , T.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering H., T ANG , T

Reference 6

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This paper cites L., AND BOULDIN , D.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering L., AND BOULDIN , D

Reference 7

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Observation b3490122-0462-42c5-9db3-919909077744 · outbound

This paper cites Analysis of named entity recognition and linking for tweets.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Analysis of named entity recognition and linking for tweets

Reference 8

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This paper cites M., T HONET , T., AND GAUSSIER , E.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering M., T HONET , T., AND GAUSSIER , E

Reference 9

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Observation 157d8294-2932-4354-b220-a0d8930d6171 · outbound

This paper cites Protoformer: Embedding prototypes for transformers.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Protoformer: Embedding prototypes for transformers

Reference 10

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Observation 3c49a35a-d78e-4031-ab0b-1e4106cce1f7 · outbound

This paper cites Efficient graph convolution for joint node representation learning and clustering.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Efficient graph convolution for joint node representation learning and clustering

Reference 11

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Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Unresolved cited work

Reference 12

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Observation c2c2fdc4-d8cb-4275-9c35-8608a2e8101f · outbound

This paper cites Beyond words: a comparative analysis of llm embeddings for effective clustering.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Beyond words: a comparative analysis of llm embeddings for effective clustering

Reference 13

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Observation 3c06fac6-9ecd-4197-adef-485a672dd3bb · outbound

This paper cites K.-S., AND NASRIDINOV , A.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering K.-S., AND NASRIDINOV , A

Reference 14

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Observation 17320d84-f697-49a6-ba42-326a4a33173e · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Semi-Supervised Classification with Graph Convolutional Networks

Reference 15

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This paper cites Variational Graph Auto-Encoders.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Variational Graph Auto-Encoders

Reference 16

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This paper cites Efficient regularized spectral data embedding.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Efficient regularized spectral data embedding

Reference 17

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Observation 1dccd6ba-6456-456b-afec-d9ccb4c083fd · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 18

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This paper cites Some methods for classification and analysis of multivariate observations.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Some methods for classification and analysis of multivariate observations

Reference 19

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This paper cites Efficient Estimation of Word Representations in Vector Space.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Efficient Estimation of Word Representations in Vector Space

Reference 20

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Observation bbcbaf41-d676-4a49-b0db-e9c78c12f0ef · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering MTEB: Massive Text Embedding Benchmark

Reference 21

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Observation abcd3fc9-0b79-466f-9118-b2ff863e4165 · outbound

This paper cites On spectral clustering: Analysis and an algorithm.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering On spectral clustering: Analysis and an algorithm

Reference 22

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This paper cites L., W ANG , C.-D., G U, Z., AND LI, Y.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering L., W ANG , C.-D., G U, Z., AND LI, Y

Reference 23

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This paper cites Improving language understanding by generative pre-training.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Improving language understanding by generative pre-training

Reference 24

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Observation e4d733e9-97e7-4a94-83ab-547ce96ee30c · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 25

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Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Unresolved cited work

Reference 26

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This paper cites Directional co-clustering.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Directional co-clustering

Reference 27

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This paper cites Simple and effective graph autoencoders with one-hop linear models.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Simple and effective graph autoencoders with one-hop linear models

Reference 28

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Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering D., AND RAGHAVAN, P

Reference 29

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This paper cites MLSUM: The Multilingual Summarization Corpus.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering MLSUM: The Multilingual Summarization Corpus

Reference 30

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This paper cites Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!

Reference 31

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Observation 7ea82f97-614d-4300-8912-8e7e3034a532 · outbound

This paper cites Properties of the hubert-arable adjusted rand index.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Properties of the hubert-arable adjusted rand index

Reference 32

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Observation 47f08fd4-a717-45e7-80f9-ba1e5943db51 · outbound

This paper cites Cluster ensembles—a knowledge reuse framework for combining multiple partitions.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Cluster ensembles—a knowledge reuse framework for combining multiple partitions

Reference 33

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This paper cites T-NER: An all-round python library for transformer-based named entity recognition.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering T-NER: An all-round python library for transformer-based named entity recognition

Reference 34

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This paper cites Attention is all you need.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Attention is all you need

Reference 35

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Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering L., L IÒ, P., B ENGIO , Y., AND HJELM , R

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:55:33.231376Z

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Observation 482e0ec8-e8be-4d9a-b1eb-2168c4206fe4 · outbound

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Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Structural deep network embedding

Reference 37

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Observation 6a73b83e-7da0-434e-b7bc-e0f3f0913831 · outbound

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Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Unresolved cited work

Reference 38

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Observation 08b0f16b-335b-4385-9b9f-a39ff9c550b7 · outbound

This paper cites A semantic approach for text clustering using wordnet and lexical chains.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering A semantic approach for text clustering using wordnet and lexical chains

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:55:33.169707Z

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Observation 08bc8a4d-c8cb-4224-be57-d8b0557c9749 · outbound

This paper cites Simplifying graph convolutional networks.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Simplifying graph convolutional networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:55:33.152022Z

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Observation 656cbf82-2296-4bbe-97d8-c10ed238750b · outbound

This paper cites D., AND HONG , M.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering D., AND HONG , M

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:55:33.132172Z

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Observation 11d891e8-b1e7-486a-a94d-d98becd79fa9 · outbound

This paper cites Graph contrastive learning with augmenta- tions.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Graph contrastive learning with augmenta- tions

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:55:33.114212Z

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Observation 7e301eab-f487-490a-b2ac-ccf2c002c57b · outbound

This paper cites Graph-Bert: Only Attention is Needed for Learning Graph Representations.

Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Graph-Bert: Only Attention is Needed for Learning Graph Representations

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T11:55:32.848128Z

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Pith citing papers

No inbound Pith citation observations are available.