Paper Citation Record · LEDGER

OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2103.09430.

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

pith.paper-citation-record.v1
2103.09430 v3

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:38:41.516652Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T20:08:56.289279Z

Reference resolution

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External citation measurements

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Outbound references

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Pith citing papers

Observation 7681ad86-0246-462a-8580-7738111eeec4 · inbound

Instant Policy: In-Context Imitation Learning via Graph Diffusion cites this paper.

Instant Policy: In-Context Imitation Learning via Graph Diffusion OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 9

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Observation cb047a84-49c7-4002-a96e-bb93e93e5d87 · inbound

A Theory for Compressibility of Graph Transformers for Transductive Learning cites this paper.

A Theory for Compressibility of Graph Transformers for Transductive Learning OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T17:05:46.756901Z

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Observation 0022b4a1-44fb-4b2b-8b8f-17b4b7c4bfe5 · inbound

Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers cites this paper.

Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 28

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Observation c7ed99bf-f545-4909-834b-d77c9bbcb6b5 · inbound

Even Sparser Graph Transformers cites this paper.

Even Sparser Graph Transformers OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 18

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Observation 90752192-4720-431c-ac44-be7fff05591b · inbound

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model cites this paper.

GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:02.375213Z

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Observation 0724e81e-b051-4c27-89eb-b66bf6e1e72f · inbound

Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning cites this paper.

Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T00:55:51.696239Z

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Observation 1a12bb70-ec9b-4d5e-b143-2cbb301fb9c0 · inbound

Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization cites this paper.

Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T21:45:03.507093Z

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Observation 0fae4930-b84c-49fb-a7d6-4033ec952511 · inbound

From Molecules to Mixtures: Learning Representations of Olfactory Mixture Similarity using Inductive Biases cites this paper.

From Molecules to Mixtures: Learning Representations of Olfactory Mixture Similarity using Inductive Biases OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T13:41:14.442560Z

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Observation 53bfae05-aa51-45ea-bdd4-079b336a55d9 · inbound

Pretraining a Foundation Model for Small-Molecule Natural Products cites this paper.

Pretraining a Foundation Model for Small-Molecule Natural Products OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:35:13.393908Z

Source-reported events for the cited work

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Observation 715b4563-a9d9-4424-b693-2ab21b939f87 · inbound

PTCL: Pseudo-Label Temporal Curriculum Learning for Label-Limited Dynamic Graph cites this paper.

PTCL: Pseudo-Label Temporal Curriculum Learning for Label-Limited Dynamic Graph OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 23

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Observation b515385b-8423-4da6-9377-be0a92abeb7a · inbound

GraphPrompter: Multi-stage Adaptive Prompt Optimization for Graph In-Context Learning cites this paper.

GraphPrompter: Multi-stage Adaptive Prompt Optimization for Graph In-Context Learning OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:02.302363Z

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Observation 469ca954-f018-4c3b-aaaa-cf4fbb0944ad · inbound

EquiHGNN: Scalable Rotationally Equivariant Hypergraph Neural Networks cites this paper.

EquiHGNN: Scalable Rotationally Equivariant Hypergraph Neural Networks OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:49.330959Z

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Observation 969ea932-fe5d-4edc-a647-5e563b5bedb6 · inbound

Graph Prompting for Graph Learning Models: Recent Advances and Future Directions cites this paper.

Graph Prompting for Graph Learning Models: Recent Advances and Future Directions OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 25

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Observation 4f2137dc-44f2-4be6-834c-977d2dbd385d · inbound

Are We Really Measuring Progress? Transferring Insights from Evaluating Recommender Systems to Temporal Link Prediction cites this paper.

Are We Really Measuring Progress? Transferring Insights from Evaluating Recommender Systems to Temporal Link Prediction OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T00:49:58.909465Z

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Observation 7dbb230a-a6d0-460d-801e-645660901246 · inbound

Pieceformer: Similarity-Driven Knowledge Transfer via Scalable Graph Transformer in VLSI cites this paper.

Reference 11

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Observation cf4d4fdf-dd8e-46e6-ad55-c5337c34118b · inbound

A Benchmark for Quantum Chemistry Relaxations via Machine Learning Interatomic Potentials cites this paper.

A Benchmark for Quantum Chemistry Relaxations via Machine Learning Interatomic Potentials OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T21:57:40.414127Z

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Observation f8c1e866-e03a-48a0-8e66-e27a4bb5c682 · inbound

MolVision: Molecular Property Prediction with Vision Language Models cites this paper.

MolVision: Molecular Property Prediction with Vision Language Models OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T20:19:29.266556Z

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Observation 84660675-7b4b-4f5c-82f4-da2d19e23c2c · inbound

OmniVec2 -- A Novel Transformer based Network for Large Scale Multimodal and Multitask Learning cites this paper.

OmniVec2 -- A Novel Transformer based Network for Large Scale Multimodal and Multitask Learning OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T19:50:18.119583Z

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Observation 2289f3dc-4327-4629-9c15-e5f5d7df9f68 · inbound

Mayura: Exploiting Similarities in Motifs for Temporal Co-Mining cites this paper.

Mayura: Exploiting Similarities in Motifs for Temporal Co-Mining OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T15:54:11.019454Z

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Observation d16b9fc7-9d0b-42b7-84fc-b3c6dec83aa0 · inbound

DisRFM: Polar Riemannian Flow Matching for Structure-Preserving Graph Domain Adaptation cites this paper.

DisRFM: Polar Riemannian Flow Matching for Structure-Preserving Graph Domain Adaptation OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:07:39.218162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 45ba559b-e4e0-4933-aeba-955d377c3ee7 · inbound

AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation cites this paper.

AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:31:39.334412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 02100fa2-e1b0-48c1-9707-76a92d547dd5 · inbound

DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation cites this paper.

DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:38:10.575175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 16492a57-cb39-4713-8ce6-791696d86da2 · inbound

The limits of bio-molecular modeling with large language models : a cross-scale evaluation cites this paper.

The limits of bio-molecular modeling with large language models : a cross-scale evaluation OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:13:13.928552Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 519f41a3-8783-44a0-84eb-f15a09f79486 · inbound

Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery cites this paper.

Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:11:16.860435Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1992e74c-e9a9-4310-9850-a59dc915435d · inbound

Fused Gromov-Wasserstein Distance with Feature Selection cites this paper.

Fused Gromov-Wasserstein Distance with Feature Selection OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:42:20.934836Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d3948587-6392-4ac9-84a6-56939f017505 · inbound

Leveraging Graph Structure in Seq2Seq Models for Knowledge Graph Link Prediction cites this paper.

Leveraging Graph Structure in Seq2Seq Models for Knowledge Graph Link Prediction OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:48:13.026174Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0bdc422c-da31-4760-a9eb-ce5af8738856 · inbound

Graph Hierarchical Recurrence for Long-Range Generalization cites this paper.

Graph Hierarchical Recurrence for Long-Range Generalization OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:08:17.752903Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation dd9901d4-859e-4e70-9249-7ab60f155ebf · inbound

Safe-Subspace Pseudo-Label Refinement for Source-Free Graph Domain Adaptation cites this paper.

Safe-Subspace Pseudo-Label Refinement for Source-Free Graph Domain Adaptation OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:22:34.292402Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 18807322-841a-4119-9043-f23448b98419 · inbound

GFFMERGE: Efficient Merging of Graph Neural Force Fields and Beyond cites this paper.

GFFMERGE: Efficient Merging of Graph Neural Force Fields and Beyond OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:06:26.655637Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ce6f685a-7801-4a9d-a932-b4d9ebeba6db · inbound

GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs cites this paper.

GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T11:08:03.224018Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4f846af2-dfb6-45c1-b32a-2860e0804772 · inbound

Handling Feature Heterogeneity with Learnable Graph Patches cites this paper.

Handling Feature Heterogeneity with Learnable Graph Patches OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:08:56.291862Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 152dbf20-e656-4a9f-a78e-5b5619d9106e · inbound

Cross-Resolution Semantic Learning for Graph Domain Adaptation cites this paper.

Cross-Resolution Semantic Learning for Graph Domain Adaptation OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T08:31:24.031275Z

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Observation c5ec75bd-f688-41d5-8383-0a332bb55718 · inbound

LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs cites this paper.

LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T00:24:53.826395Z

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