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Paper Citation Record · LEDGER

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression

As of 10 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2601.08187.

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

pith.paper-citation-record.v1
2601.08187 v3

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measured 56 of 56 reference resolution

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measured 56 of 56 standing notices

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measured 0 of 0 inbound itemization

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56 of 56 outbound references displayed

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Outbound references

Observation 13891f4f-a54b-4dbf-b58c-54775a85c484 · outbound

This paper cites A survey of large language models for graphs.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression A survey of large language models for graphs

Reference 1

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This paper cites Large language models on graphs: A comprehensive survey.IEEE Transactions on Knowledge and Data Engineering, 36(12):8622–8642, 2024.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Large language models on graphs: A comprehensive survey.IEEE Transactions on Knowledge and Data Engineering, 36(12):8622–8642, 2024

Reference 2

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Observation f77932a5-eb4d-4e5e-8efe-f1de522e76fb · outbound

This paper cites Graphgpt: Graph instruction tuning for large language models.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Graphgpt: Graph instruction tuning for large language models

Reference 3

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This paper cites Language is all a graph needs.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Language is all a graph needs

Reference 4

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This paper cites When do LLMs help with node classification? a comprehensive analysis.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression When do LLMs help with node classification? a comprehensive analysis

Reference 5

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Observation 5fa783ad-3434-4562-86f9-f66e54a87bb1 · outbound

This paper cites Llaga: Large language and graph assistant.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Llaga: Large language and graph assistant

Reference 6

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This paper cites Beyond the limits: a survey of techniques to extend the context length in large language models.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Beyond the limits: a survey of techniques to extend the context length in large language models

Reference 7

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This paper cites Are Large Language Models In-Context Graph Learners?.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Are Large Language Models In-Context Graph Learners?

Reference 8

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This paper cites Exploring the potential of large language models (llms)in learning on graphs.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Exploring the potential of large language models (llms)in learning on graphs

Reference 9

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This paper cites Talk like a graph: Encoding graphs for large language models.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Talk like a graph: Encoding graphs for large language models

Reference 10

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This paper cites Graph condensation for graph neural networks.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Graph condensation for graph neural networks

Reference 11

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Observation d2138a66-40ae-4692-a69b-16f40a121ea4 · outbound

This paper cites Condensing graphs via one-step gradient matching.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Condensing graphs via one-step gradient matching

Reference 12

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This paper cites Structural information and dynamical complexity of networks.IEEE Transactions on Information Theory, 62(6):3290–3339, 2016.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Structural information and dynamical complexity of networks.IEEE Transactions on Information Theory, 62(6):3290–3339, 2016

Reference 13

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This paper cites Graph out-of-distribution generalization based on structural-entropy-guided information bottleneck.ACM Transactions on Knowledge Discovery from Data, 20(1):1–34, 2025.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Graph out-of-distribution generalization based on structural-entropy-guided information bottleneck.ACM Transactions on Knowledge Discovery from Data, 20(1):1–34, 2025

Reference 14

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This paper cites Structural entropy guided unsupervised graph out-of-distribution detection.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Structural entropy guided unsupervised graph out-of-distribution detection

Reference 15

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This paper cites Incremental measurement of structural entropy for dynamic graphs.Artificial Intelligence, 334:104175, 2024.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Incremental measurement of structural entropy for dynamic graphs.Artificial Intelligence, 334:104175, 2024

Reference 16

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Unresolved cited work

Reference 17

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This paper cites Se-gsl: A general and effective graph structure learning framework through structural entropy optimization.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Se-gsl: A general and effective graph structure learning framework through structural entropy optimization

Reference 18

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Sega: Structural entropy guided anchor view for graph contrastive learning

Reference 19

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression A simple yet effective method for graph classification

Reference 20

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Structural entropy guided graph hierarchical pooling

Reference 21

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Unresolved cited work

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This paper cites Resistance maximization principle for defending networks against virus attack.Physica A: Statistical Mechanics and its Applications, 466:211–223, 2017.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Resistance maximization principle for defending networks against virus attack.Physica A: Statistical Mechanics and its Applications, 466:211–223, 2017

Reference 23

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This paper cites Achieving graph clustering privacy preservation based on structure entropy in social iot.IEEE Internet of Things Journal, 9(4):2761–2777, 2022.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Achieving graph clustering privacy preservation based on structure entropy in social iot.IEEE Internet of Things Journal, 9(4):2761–2777, 2022

Reference 24

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Unresolved cited work

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Unresolved cited work

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Sebot: Structural entropy guided multi-view contrastive learning for social bot detection

Reference 27

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This paper cites Valence-based homophily on twitter: Network analysis of emotions and political talk in the 2012 presidential election.New media & society, 18(7):1382–1400, 2016.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Valence-based homophily on twitter: Network analysis of emotions and political talk in the 2012 presidential election.New media & society, 18(7):1382–1400, 2016

Reference 28

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 29

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Open graph benchmark: datasets for machine learning on graphs

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Harnessing explanations: LLM-to-LM interpreter for enhanced text-attributed graph representation learning

Reference 31

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This paper cites Can gnn be good adapter for llms? InProceedings of the ACM Web Conference 2024, WWW-24, page 893–904, 2024.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Can gnn be good adapter for llms? InProceedings of the ACM Web Conference 2024, WWW-24, page 893–904, 2024

Reference 32

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Cohen, and Ruslan Salakhutdinov

Reference 33

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This paper cites Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models, 2024.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models, 2024

Reference 34

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Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Kipf and Max Welling

Reference 35

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Observation c17c4ab2-93ae-40d5-8601-9a74c4a8c4c1 · outbound

This paper cites Graph attention networks.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Graph attention networks

Reference 36

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Observation f074a0a6-92c4-4251-bc2f-c2cc4d0ec014 · outbound

This paper cites How powerful are graph neural networks? In International Conference on Learning Representations, ICLR-19, 2019.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression How powerful are graph neural networks? In International Conference on Learning Representations, ICLR-19, 2019

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Observation 9470dc1c-5b81-4cf3-a39f-04ad8968ecb4 · outbound

This paper cites Inductive representation learning on large graphs.Proceedings of the 31st International Conference on Neural Information Processing Systems, NeurIPS-17, 30, 2017.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Inductive representation learning on large graphs.Proceedings of the 31st International Conference on Neural Information Processing Systems, NeurIPS-17, 30, 2017

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Observation 963ca38d-6500-41df-aacc-265d02690794 · outbound

This paper cites Degree-based stratification of nodes in graph neural networks.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Degree-based stratification of nodes in graph neural networks

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Observation 0acde30a-abd9-4bf2-9bea-18106d0307ff · outbound

This paper cites Graph-skeleton:˜ 1% nodes are sufficient to represent billion-scale graph.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Graph-skeleton:˜ 1% nodes are sufficient to represent billion-scale graph

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Observation b7d3fa8c-de05-4505-aff3-b01a9ca129d3 · outbound

This paper cites The Llama 3 Herd of Models.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression The Llama 3 Herd of Models

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Observation 9051ff6c-924a-4c49-aa7e-26f001cad6dc · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Judging llm-as-a-judge with mt-bench and chatbot arena

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Observation 5c4ee624-02b9-4815-a913-2ecaffdb5f40 · outbound

This paper cites Multi-scale heterogeneous text-attributed graph datasets from diverse domains.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Multi-scale heterogeneous text-attributed graph datasets from diverse domains

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Observation 4e860ce4-419c-4099-b8bc-67bdfd791084 · outbound

This paper cites A survey of structural entropy: Theory, methods, and applications.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression A survey of structural entropy: Theory, methods, and applications

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Observation 317fa7a4-48a7-48e3-84b7-deb820653789 · outbound

This paper cites Item recommendation on monotonic behavior chains.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Item recommendation on monotonic behavior chains

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source=pdf_text observed=2026-08-03T10:56:56.375324Z digest=sha256:134d4b85ace99e9ec11a39368d3ea917d6ae00315a7344a83266efb8e592a3e6

Observation b9d80670-e868-42ea-a879-06a4d021e67b · outbound

This paper cites Oag-bench: a human-curated benchmark for academic graph mining.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Oag-bench: a human-curated benchmark for academic graph mining

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source=pdf_text observed=2026-08-03T10:56:56.378300Z digest=sha256:730f9bb1a7d6576053b8a59f224e8e1a5ab3040bc7cc1f506bdcb711d87adce2

Observation 1bbffd43-3c72-44a7-a9c4-efd682901aae · outbound

This paper cites Explainability in graph neural networks: A taxonomic survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(5):5782–5799, 2023.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Explainability in graph neural networks: A taxonomic survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(5):5782–5799, 2023

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Observation daca6e33-c014-4305-9793-9fad972c7c5e · outbound

This paper cites Moleculenet: a benchmark for molecular machine learning.Chemical science, 9(2):513–530, 2018.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Moleculenet: a benchmark for molecular machine learning.Chemical science, 9(2):513–530, 2018

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Observation 06b90d97-c4f9-4ce3-a73b-4d1b24c523be · outbound

This paper cites Graph coarsening via convolution matching for scalable graph neural network training.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Graph coarsening via convolution matching for scalable graph neural network training

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Observation 6cc697fb-cb3a-4fd4-a626-aeac477b130d · outbound

This paper cites Featured graph coarsening with similarity guarantees.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Featured graph coarsening with similarity guarantees

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source=pdf_text observed=2026-08-03T10:56:56.390682Z digest=sha256:5ebaafb1700b7a6b8b147f04fd7049350821128df621635676f1baa3b1ac5fec

Observation 17675f82-3206-43cb-a16f-584b9b30bf25 · outbound

This paper cites Ugc: universal graph coarsening.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Ugc: universal graph coarsening

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Observation 97843ffd-c0c9-466e-bcb1-8999cce1f4aa · outbound

This paper cites Quantifying node importance over network structural stability.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Quantifying node importance over network structural stability

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Observation 23024b9e-435c-41a7-9ffb-c08847c4f6a1 · outbound

This paper cites an unresolved cited work.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Unresolved cited work

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source=pdf_text observed=2026-08-03T10:56:56.400612Z digest=sha256:bf2a655fcaae895c27e9b2ec0b025b492c56db15139e575b42df5268f487164f

Observation a2069f97-91f0-40aa-869c-db4db8167f2f · outbound

This paper cites Answer: Box 5The Aggregation prompt template for Molecule Property Prediction Datasets.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Answer: Box 5The Aggregation prompt template for Molecule Property Prediction Datasets

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source=pdf_text observed=2026-08-03T10:56:56.403527Z digest=sha256:fec4715af6d7894c6e2652ffd20a39e77468875e09f747f5669cdea8729d85fb

Observation 7e1305bc-d892-4eb9-ad7b-e5f091f41e5b · outbound

This paper cites an unresolved cited work.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression Unresolved cited work

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source=pdf_text observed=2026-08-03T10:56:56.406438Z digest=sha256:84b0e2e92cf931531d0097a1c108957f9533d473c19cb2e26f9d5e98e03aa765

Observation 9fbf609f-5cc9-40ff-82ab-7a40c5be6434 · outbound

This paper cites is similar to.

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression is similar to

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