Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching | Paper Citation Record

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This paper cites Open graph benchmark: Datasets for machine learning on graphs.Advances in neural information processing systems, 33:22118–22133, 2020.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Open graph benchmark: Datasets for machine learning on graphs.Advances in neural information processing systems, 33:22118–22133, 2020

Reference 1

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This paper cites Revisiting semi-supervised learning with graph embeddings.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Revisiting semi-supervised learning with graph embeddings

Reference 2

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This paper cites Collective classification in network data.AI magazine, 29(3):93–93, 2008.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Collective classification in network data.AI magazine, 29(3):93–93, 2008

Reference 3

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This paper cites Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning

Reference 4

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This paper cites Language models are few-shot learners.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Language models are few-shot learners

Reference 5

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This paper cites GPT-4 Technical Report.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching GPT-4 Technical Report

Reference 6

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This paper cites The Llama 3 Herd of Models.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching The Llama 3 Herd of Models

Reference 7

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This paper cites Label-free Node Classification on Graphs with Large Language Models (LLMS).

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Label-free Node Classification on Graphs with Large Language Models (LLMS)

Reference 8

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Observation 52d64aff-e398-4d81-991b-ea8a7c16f341 · outbound

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

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Graphgpt: Graph instruction tuning for large language models

Reference 9

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This paper cites Language is all a graph needs.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Language is all a graph needs

Reference 10

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This paper cites LLaGA: Large Language and Graph Assistant.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching LLaGA: Large Language and Graph Assistant

Reference 11

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This paper cites One for All: Towards Training One Graph Model for All Classification Tasks.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching One for All: Towards Training One Graph Model for All Classification Tasks

Reference 12

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Observation 160f253e-893e-44ee-b517-215b822dbd03 · outbound

This paper cites Learning on Large-scale Text-attributed Graphs via Variational Inference.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Learning on Large-scale Text-attributed Graphs via Variational Inference

Reference 13

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This paper cites Instructgraph: Boosting large language models via graph-centric instruction tuning and preference alignment.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Instructgraph: Boosting large language models via graph-centric instruction tuning and preference alignment

Reference 14

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This paper cites Graph prototypical networks for few-shot learning on attributed networks.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Graph prototypical networks for few-shot learning on attributed networks

Reference 15

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This paper cites Meta propagation networks for graph few-shot semi-supervised learning.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Meta propagation networks for graph few-shot semi-supervised learning

Reference 16

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This paper cites Graph few-shot learning with task-specific structures.Advances in Neural Information Processing Systems, 35:38925–38936, 2022.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Graph few-shot learning with task-specific structures.Advances in Neural Information Processing Systems, 35:38925–38936, 2022

Reference 17

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This paper cites Graph meta learning via local subgraphs.Advances in neural information processing systems, 33:5862–5874, 2020.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Graph meta learning via local subgraphs.Advances in neural information processing systems, 33:5862–5874, 2020

Reference 18

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

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Multi-stage self-supervised learning for graph convolutional networks on graphs with few labeled nodes

Reference 19

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

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Semi-Supervised Classification with Graph Convolutional Networks

Reference 20

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Observation 7b439bcf-f5e5-4a74-84a0-5c0f9093596e · outbound

This paper cites Simplifying graph convolutional networks.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Simplifying graph convolutional networks

Reference 21

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This paper cites Predict then Propagate: Graph Neural Networks meet Personalized PageRank.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Predict then Propagate: Graph Neural Networks meet Personalized PageRank

Reference 22

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Observation 4bcca94e-566d-4617-9cfb-3a2b2de28d4b · outbound

This paper cites Representation learning on graphs with jumping knowledge networks.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Representation learning on graphs with jumping knowledge networks

Reference 23

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This paper cites Deeper insights into graph convolutional networks for semi-supervised learning.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Deeper insights into graph convolutional networks for semi-supervised learning

Reference 24

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This paper cites Beyond homophily in graph neural networks: Current limitations and effective designs.Advances in neural information processing systems, 33:7793–7804, 2020.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Beyond homophily in graph neural networks: Current limitations and effective designs.Advances in neural information processing systems, 33:7793–7804, 2020

Reference 25

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This paper cites Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?

Reference 26

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This paper cites When Do LLMs Help With Node Classification? A Comprehensive Analysis.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching When Do LLMs Help With Node Classification? A Comprehensive Analysis

Reference 27

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This paper cites How do large language models understand graph patterns? a benchmark for graph pattern comprehension.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching How do large language models understand graph patterns? a benchmark for graph pattern comprehension

Reference 28

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This paper cites GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

Reference 29

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This paper cites Grenade: Graph-centric language model for self-supervised representation learning on text-attributed graphs.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Grenade: Graph-centric language model for self-supervised representation learning on text-attributed graphs

Reference 30

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This paper cites Graphformers: Gnn-nested transformers for representation learning on textual graph.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Graphformers: Gnn-nested transformers for representation learning on textual graph

Reference 31

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This paper cites Llms as zero-shot graph learners: Alignment of gnn representations with llm token embeddings.Advances in neural information processing systems, 37: 5950–5973, 2024.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Llms as zero-shot graph learners: Alignment of gnn representations with llm token embeddings.Advances in neural information processing systems, 37: 5950–5973, 2024

Reference 32

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This paper cites Let’s ask gnn: Empowering large language model for graph in-context learning.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Let’s ask gnn: Empowering large language model for graph in-context learning

Reference 33

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This paper cites GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback

Reference 34

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This paper cites Direct preference optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741, 2023.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Direct preference optimization: Your language model is secretly a reward model.Advances in neural information processing systems, 36:53728–53741, 2023

Reference 35

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This paper cites Augmenting low-resource text classification with graph-grounded pre-training and prompting.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Augmenting low-resource text classification with graph-grounded pre-training and prompting

Reference 36

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This paper cites Leveraging large language models for node generation in few-shot learning on text-attributed graphs.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Leveraging large language models for node generation in few-shot learning on text-attributed graphs

Reference 37

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This paper cites Llms are noisy oracles! llm-based noise-aware graph active learning for node classification.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Llms are noisy oracles! llm-based noise-aware graph active learning for node classification

Reference 38

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This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels.Advances in neural information processing systems, 31, 2018.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Co-teaching: Robust training of deep neural networks with extremely noisy labels.Advances in neural information processing systems, 31, 2018

Reference 39

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This paper cites How does disagreement help generalization against label corruption? InInternational conference on machine learning, pages 7164–7173.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching How does disagreement help generalization against label corruption? InInternational conference on machine learning, pages 7164–7173

Reference 40

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This paper cites DivideMix: Learning with Noisy Labels as Semi-supervised Learning.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching DivideMix: Learning with Noisy Labels as Semi-supervised Learning

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This paper cites Deep co-training for semi-supervised image recognition.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Deep co-training for semi-supervised image recognition

Reference 42

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Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Self-paced co-training

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This paper cites Self-paced learning for latent variable models.Advances in neural information processing systems, 23, 2010.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Self-paced learning for latent variable models.Advances in neural information processing systems, 23, 2010

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This paper cites Natarajan, I.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Natarajan, I

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This paper cites Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion

Reference 46

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This paper cites Understanding and utilizing deep neural networks trained with noisy labels.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Understanding and utilizing deep neural networks trained with noisy labels

Reference 47

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This paper cites Learning with Instance-Dependent Label Noise: A Sample Sieve Approach.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Learning with Instance-Dependent Label Noise: A Sample Sieve Approach

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This paper cites RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response

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This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching The Curse of Recursion: Training on Generated Data Makes Models Forget

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

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks

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This paper cites Uncertainty-aware self-training for few-shot text classifica- tion.Advances in Neural Information Processing Systems, 33:21199–21212, 2020.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Uncertainty-aware self-training for few-shot text classifica- tion.Advances in Neural Information Processing Systems, 33:21199–21212, 2020

Reference 52

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This paper cites In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:07:47.669402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 959397b6-1532-49d2-97b0-2a8e2010190a · outbound

This paper cites Unifying Graph Convolutional Neural Networks and Label Propagation.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Unifying Graph Convolutional Neural Networks and Label Propagation

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:07:47.628648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b64c0cd4-b3d9-463d-91bf-da3208e3b2f6 · outbound

This paper cites Confidence may cheat: Self-training on graph neural networks under distribution shift.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Confidence may cheat: Self-training on graph neural networks under distribution shift

Reference 55

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation d2c3c64a-1d5f-40b6-a3b4-5df49ee200de · outbound

This paper cites Active Learning for Graph Embedding.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Active Learning for Graph Embedding

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-07-03T09:07:47.633831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a563c487-2d52-439b-ba92-c6bad21553c4 · outbound

This paper cites Rim: Reliable influence-based active learning on graphs.Advances in neural information processing systems, 34:27978–27990, 2021.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Rim: Reliable influence-based active learning on graphs.Advances in neural information processing systems, 34:27978–27990, 2021

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation 7ba6991a-565d-4936-8271-93530a641746 · outbound

This paper cites Deep rein- forcement learning from human preferences.Advances in neural information processing systems, 30, 2017.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Deep rein- forcement learning from human preferences.Advances in neural information processing systems, 30, 2017

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation 1c8d0c81-0361-4a5e-9256-62007aa951b7 · outbound

This paper cites Learning to summarize with human feedback.Advances in neural information processing systems, 33:3008–3021, 2020.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Learning to summarize with human feedback.Advances in neural information processing systems, 33:3008–3021, 2020

Reference 59

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation a6b1f78a-be5d-49ac-85f0-5ee32a4e7457 · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 60

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation aef310f8-9cb8-4462-a9fa-28ec94366541 · outbound

This paper cites A general theoretical paradigm to understand learning from human preferences.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching A general theoretical paradigm to understand learning from human preferences

Reference 61

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation 66d2f810-c05f-45ca-ba32-ed9c3d95e8c7 · outbound

This paper cites Model alignment as prospect theoretic optimization.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Model alignment as prospect theoretic optimization

Reference 62

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation b1ac8191-28ef-441e-93f4-4533642a347d · outbound

This paper cites Simpo: Simple preference optimization with a reference-free reward.Advances in Neural Information Processing Systems, 37:124198–124235, 2024.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Simpo: Simple preference optimization with a reference-free reward.Advances in Neural Information Processing Systems, 37:124198–124235, 2024

Reference 63

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation 96a6d5b6-b5ec-4741-a3ff-ac1fd174b222 · outbound

This paper cites Group Preference Optimization: Few-Shot Alignment of Large Language Models.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Group Preference Optimization: Few-Shot Alignment of Large Language Models

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:07:47.639938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 216197a9-8b32-46ca-80c3-a607f5bc6878 · outbound

This paper cites Direct preference optimization with an offset.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Direct preference optimization with an offset

Reference 65

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation 1bda99a8-64b9-47e0-b0d1-1a307d0eef46 · outbound

This paper cites Orpo: Monolithic preference optimization without reference model.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Orpo: Monolithic preference optimization without reference model

Reference 66

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation e3cb08df-f17e-484d-a671-2b4539fd5924 · outbound

This paper cites Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks

Reference 67

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:07:47.674460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c76b0ed5-9179-437a-a21e-6423a745f558 · outbound

This paper cites Graph attention networks.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Graph attention networks

Reference 68

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation ee2421c6-0342-4e09-8957-faef5ffd02a0 · outbound

This paper cites Inductive representation learning on large graphs.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Inductive representation learning on large graphs

Reference 69

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation edf6ae7c-9bd5-4eeb-ade6-708d442f1a98 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

Reference 70

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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Observation 40514518-95d0-455d-a812-fc261ce90dc5 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-07-03T09:07:47.676775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4fc0c5c3-98fb-4509-8142-7e8baf68c205 · outbound

This paper cites both wrong.

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching both wrong

Reference 72

Resolution: unresolved; no resolver link, observed 2026-06-27T10:33:02.954683Z

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