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Paper Citation Record · LEDGER

Graph Neural Networks with Learnable Structural and Positional Representations

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2110.07875.

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

pith.paper-citation-record.v1
2110.07875 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:40:12.348683Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

25
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2d0bc7c6-f38e-4376-a60b-192fdc37726f · inbound

A Generalizable Anomaly Detection Method in Dynamic Graphs cites this paper.

A Generalizable Anomaly Detection Method in Dynamic Graphs Graph Neural Networks with Learnable Structural and Positional Representations

Reference 17

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no resolver link, observed 2026-08-11T10:37:43.624011Z

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Unavailable: canonical work link unavailable.

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Observation 10c05888-8766-4d6d-8393-b6e5ad6f44dc · inbound

ASTRA: A Scene-aware TRAnsformer-based model for trajectory prediction cites this paper.

ASTRA: A Scene-aware TRAnsformer-based model for trajectory prediction Graph Neural Networks with Learnable Structural and Positional Representations

Reference 43

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no resolver link, observed 2026-08-10T19:42:13.678613Z

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Unavailable: canonical work link unavailable.

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Observation 42826f10-840a-476b-8e95-c03692270f8a · inbound

Policy Guided Tree Search for Enhanced LLM Reasoning cites this paper.

Policy Guided Tree Search for Enhanced LLM Reasoning Graph Neural Networks with Learnable Structural and Positional Representations

Reference 14

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no resolver link, observed 2026-08-09T11:20:31.750244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:20:31.750244Z digest=sha256:13dffcd8b28b784eedb63257c8e49db05e069d4f013190fea0b9d2797cb64168

Observation 6e3221b5-3195-4390-b026-153ea356a54c · inbound

ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans cites this paper.

ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans Graph Neural Networks with Learnable Structural and Positional Representations

Reference 10

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no resolver link, observed 2026-08-08T11:23:58.464828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T11:23:58.464828Z digest=sha256:de493263d91d2db9619385abf388cfbbd25b93c0e3b9dc2a9978ce9369fd6707

Observation 5aab17d2-b986-49d0-822d-8dc3c16fd87e · inbound

Enhancing the Utility of Higher-Order Information in Relational Learning cites this paper.

Enhancing the Utility of Higher-Order Information in Relational Learning Graph Neural Networks with Learnable Structural and Positional Representations

Reference 1991

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no resolver link, observed 2026-08-07T21:04:19.403666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:04:19.403666Z digest=sha256:bce1122eed0391af9cf7fc32a52ddb8b9ef1638f5258cb2a8402ced7cf8a1705

Observation 0c2fd9a3-9a8c-4eac-9923-621af432743e · inbound

polyGen: A Learning Framework for Atomic-level Polymer Structure Generation cites this paper.

polyGen: A Learning Framework for Atomic-level Polymer Structure Generation Graph Neural Networks with Learnable Structural and Positional Representations

Reference 35

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no resolver link, observed 2026-08-16T10:40:12.348683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6d0db7b6-e23d-4166-aac6-5ce8dcea216e · inbound

Structural-Temporal Coupling Anomaly Detection with Dynamic Graph Transformer cites this paper.

Structural-Temporal Coupling Anomaly Detection with Dynamic Graph Transformer Graph Neural Networks with Learnable Structural and Positional Representations

Reference 7

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unresolved
no resolver link, observed 2026-08-15T22:02:48.025198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:02:48.025198Z digest=sha256:f9d4075cbf0f18daa60d44156da9e6eb2106030431eb2db99db1d1b597d12a0f

Observation 2609c3b8-fc9d-4185-adbe-3ea06df3ecec · inbound

Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach cites this paper.

Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach Graph Neural Networks with Learnable Structural and Positional Representations

Reference 21

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no resolver link, observed 2026-08-15T20:56:12.283150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:56:12.283150Z digest=sha256:856cb32f2600aa9bddea42627f680c73f6339d1fef3c96a6a3e8e2034a0e91d2

Observation b13e6a0e-d41d-405c-9cb1-4e0c29e4d9f8 · inbound

HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations cites this paper.

HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations Graph Neural Networks with Learnable Structural and Positional Representations

Reference 17

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no resolver link, observed 2026-08-07T15:23:03.080450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:23:03.080450Z digest=sha256:8f38578fdc2171852dd8d072ec8db0c2fa2b2c3047146a162da1ff8991587b3b

Observation 72c490ff-e8ea-48fa-b54b-6058dca65eb6 · inbound

Graph Positional Autoencoders as Self-supervised Learners cites this paper.

Graph Positional Autoencoders as Self-supervised Learners Graph Neural Networks with Learnable Structural and Positional Representations

Reference 11

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no resolver link, observed 2026-08-07T12:54:18.485020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:54:18.485020Z digest=sha256:0523aa3ffdc9fba0634596fd68599aec9449da6c4d4ae9f7a63f60d79574fa19

Observation 7a881b6f-05b3-4391-a297-585d533ebb4e · inbound

Joint Embedding Predictive Architecture for self-supervised pretraining on polymer molecular graphs cites this paper.

Joint Embedding Predictive Architecture for self-supervised pretraining on polymer molecular graphs Graph Neural Networks with Learnable Structural and Positional Representations

Reference 38

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no resolver link, observed 2026-08-15T18:57:34.042826Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:57:34.042826Z digest=sha256:383d999d7d9428f7e6daaf272e617c2257ab4ca7a3225417d717fb4406d74651

Observation 1f342c6b-e7be-41fb-83cb-eaf61ffa1993 · inbound

SaGIF: Improving Individual Fairness in Graph Neural Networks via Similarity Encoding cites this paper.

SaGIF: Improving Individual Fairness in Graph Neural Networks via Similarity Encoding Graph Neural Networks with Learnable Structural and Positional Representations

Reference 42

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no resolver link, observed 2026-08-06T23:21:07.764761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:21:07.764761Z digest=sha256:3fb486464132b747c28784d0d18a4b556e04e35f5c54249a67b5645c57b23bc3

Observation 7bad4e64-1838-4027-9ca3-0a3e89d49a62 · inbound

GraphPPD: Posterior Predictive Modelling for Graph-Level Inference cites this paper.

GraphPPD: Posterior Predictive Modelling for Graph-Level Inference Graph Neural Networks with Learnable Structural and Positional Representations

Reference 4

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no resolver link, observed 2026-08-15T17:14:45.458857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:14:45.458857Z digest=sha256:7e7a3eae76d1529b7147b4e7fba8d5d5ce881eecf19d5f49ce1178329fb9a341

Observation c2855bef-b5ea-4b75-aebe-a51043d163d9 · inbound

M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations cites this paper.

M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations Graph Neural Networks with Learnable Structural and Positional Representations

Reference 2015

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unresolved
no resolver link, observed 2026-08-04T17:48:34.403907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:48:34.403907Z digest=sha256:9bd3c38c9ccbbb2b17578eadb9a5fd1ef13f9bbc7007f6eefdd844ecdd2cc14d

Observation 9921554a-859d-426c-9d7c-cd2400ab563a · inbound

Feature Augmentation of GNNs for ILPs: Local Uniqueness Suffices cites this paper.

Feature Augmentation of GNNs for ILPs: Local Uniqueness Suffices Graph Neural Networks with Learnable Structural and Positional Representations

Reference 7

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verified exact
arxiv_id, observed 2026-05-18T14:26:28.505241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-18T14:23:46.287363Z digest=sha256:333e7bf6d0592cbfd21c6bcdd548d5648d447a3aeb08c7ed6abbda6a9e4f84e2

Observation 005fa4e5-5d0b-4494-a96a-25b3f28c7a3e · inbound

How Embeddings Shape Graph Neural Networks: Classical vs Quantum-Oriented Node Representations cites this paper.

How Embeddings Shape Graph Neural Networks: Classical vs Quantum-Oriented Node Representations Graph Neural Networks with Learnable Structural and Positional Representations

Reference 1

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arxiv_id, observed 2026-05-10T12:20:22.941731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 23ba5cdd-e7ef-4c72-9173-d5d1e0051dcf · inbound

Frequency-Corrupt Based Graph Self-Supervised Learning cites this paper.

Frequency-Corrupt Based Graph Self-Supervised Learning Graph Neural Networks with Learnable Structural and Positional Representations

Reference 8

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verified exact
arxiv_id, observed 2026-05-10T08:32:52.064244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation a904b1ed-361b-4b44-936f-a3834f5b16db · inbound

Frequency-Corrupt Based Graph Self-Supervised Learning cites this paper.

Frequency-Corrupt Based Graph Self-Supervised Learning Graph Neural Networks with Learnable Structural and Positional Representations

Reference 8

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unresolved
no resolver link, observed 2026-08-02T16:10:59.616151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c13c86a4-035b-4f23-9dd7-9009002962a6 · inbound

VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation cites this paper.

VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation Graph Neural Networks with Learnable Structural and Positional Representations

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:21:07.602831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 718492de-7ae0-49b9-af64-8a12263e23f0 · inbound

A Transferable Machine Learning Approach to Predict Optimized Orbitals for Electronic Structure Problems cites this paper.

A Transferable Machine Learning Approach to Predict Optimized Orbitals for Electronic Structure Problems Graph Neural Networks with Learnable Structural and Positional Representations

Reference 37

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metadata mismatch
arxiv_id, observed 2026-05-11T17:11:17.558953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 08dd424b-3559-47fd-a1ec-e649cda420de · inbound

Teaching LLMs to See Graphs: Unifying Text and Structural Reasoning cites this paper.

Teaching LLMs to See Graphs: Unifying Text and Structural Reasoning Graph Neural Networks with Learnable Structural and Positional Representations

Reference 5

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verified exact
arxiv_id, observed 2026-05-12T05:21:32.147575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-12T05:16:50.681352Z digest=sha256:4a6bc4c19cf5904c7c9fa741fba1f99268ab3d309e4a21f0320e15382079e4a6

Observation 7828dd3f-fa02-402b-86bb-e7eca0721580 · inbound

Rethinking Positional Encoding for Neural Vehicle Routing cites this paper.

Rethinking Positional Encoding for Neural Vehicle Routing Graph Neural Networks with Learnable Structural and Positional Representations

Reference 2

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verified exact
arxiv_id, observed 2026-05-13T06:02:23.493112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ee0d8a63-ae91-4835-9e17-3dcc60f750bb · inbound

EvoStruct: Bridging Evolutionary and Structural Priors for Antibody CDR Design via Protein Language Model Adaptation cites this paper.

EvoStruct: Bridging Evolutionary and Structural Priors for Antibody CDR Design via Protein Language Model Adaptation Graph Neural Networks with Learnable Structural and Positional Representations

Reference 227

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arxiv_id, observed 2026-05-21T05:09:38.666686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-21T05:06:06.626303Z digest=sha256:ee275cb55747ffb4b5adca298e51503e53eab43b8e0a2af9ebe2e7d386ada435

Observation 2f0e3bc4-0984-46fd-9590-21bf3e1783bf · inbound

ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning cites this paper.

ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning Graph Neural Networks with Learnable Structural and Positional Representations

Reference 227

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arxiv_id, observed 2026-05-22T09:31:22.577626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-22T09:29:45.993792Z digest=sha256:e16acee196b9c401e874a78feb3f132fb6fd861e6f5478107aa1ef7d7bfd07ff

Observation 86e17705-067e-4416-96c4-a8f16d50544c · inbound

AgForce Enables Antigen-conditioned Generative Antibody Design cites this paper.

AgForce Enables Antigen-conditioned Generative Antibody Design Graph Neural Networks with Learnable Structural and Positional Representations

Reference 227

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arxiv_id, observed 2026-05-22T09:21:20.440858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-22T09:21:17.324165Z digest=sha256:32b5bdeea6b5d8e94b9f8746039a866eb25b6a84adf69d1e264f684a157de1f4

Observation 77460c03-7957-4679-aca4-1fbdb4a573b8 · inbound

Learning Dynamic Stability Landscapes in Synchronization Networks cites this paper.

Learning Dynamic Stability Landscapes in Synchronization Networks Graph Neural Networks with Learnable Structural and Positional Representations

Reference 177

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verified exact
arxiv_id, observed 2026-05-25T05:05:21.312786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-25T05:04:16.957305Z digest=sha256:944536dd515a5423ab80389a1cc9b27dfda8b69d667df903360a51bb2c23869a

Observation 91611ed0-68b9-445f-b527-ee7c52f34edf · inbound

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning cites this paper.

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning Graph Neural Networks with Learnable Structural and Positional Representations

Reference 205

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arxiv_id, observed 2026-07-02T07:06:44.061311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 5c752b2e-80d5-46e3-b485-4232b34f039f · inbound

Ramanujan Graph Rewiring with Non Negative Resistance Curvature cites this paper.

Ramanujan Graph Rewiring with Non Negative Resistance Curvature Graph Neural Networks with Learnable Structural and Positional Representations

Reference 26

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arxiv_id, observed 2026-07-04T06:29:37.546922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation b5683143-f1b9-4beb-a6da-9d84d5ec0415 · inbound

Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation cites this paper.

Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation Graph Neural Networks with Learnable Structural and Positional Representations

Reference 118

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verified exact
arxiv_id, observed 2026-06-26T11:09:23.764198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-26T10:59:25.867813Z digest=sha256:06f5df05e89e132c747355122cc60eb2f5b12260795ddf77bb511411c2e08114

Observation 06e3b392-4647-4a07-b35d-bc37c85752ca · inbound

Canopy: A Heterograph Foundation Model for Metabolic Engineering cites this paper.

Canopy: A Heterograph Foundation Model for Metabolic Engineering Graph Neural Networks with Learnable Structural and Positional Representations

Reference 20

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verified exact
local_arxiv, observed 2026-07-08T13:04:56.632633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-07-08T13:00:45.071926Z digest=sha256:9c8e5c178ff063ee4fca7dc1ca12fc909d7d57d0a62532e8ad57697be08db3ae

Observation e7ea232e-70cf-421b-a660-5bf8f9893f77 · inbound

Learning Adaptive Solvers for Distributed Factor Graph Optimization on Matrix Lie Groups cites this paper.

Learning Adaptive Solvers for Distributed Factor Graph Optimization on Matrix Lie Groups Graph Neural Networks with Learnable Structural and Positional Representations

Reference 159

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local_arxiv, observed 2026-07-10T02:26:43.063663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-07-10T02:19:53.978233Z digest=sha256:a10269a5cbc08890b0dedcbe1f6a5f3d4c586ae1304d9f7f3c4980a989665946

Observation f086195c-3ae9-4d99-8b86-dd2675d98943 · inbound

Distance-Preserving Embeddings in Inhomogeneous Random Graphs cites this paper.

Distance-Preserving Embeddings in Inhomogeneous Random Graphs Graph Neural Networks with Learnable Structural and Positional Representations

Reference 177

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no resolver link, observed 2026-07-14T00:37:04.989965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T00:37:04.989965Z digest=sha256:1ef382ecb494fab0f93a44fe142c7e7998e72ee7a1c44ae87d32ee124d18b2d8

Observation b3863fa5-677f-4fbf-b055-ce3b52c232e7 · inbound

Scalable and Efficient Joint Spiking Embedding Predictive Architecture for Large-Scale Dynamic Graphs cites this paper.

Scalable and Efficient Joint Spiking Embedding Predictive Architecture for Large-Scale Dynamic Graphs Graph Neural Networks with Learnable Structural and Positional Representations

Reference 11

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no resolver link, observed 2026-08-01T15:32:32.347207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T15:32:32.347207Z digest=sha256:f24734880e6812ad1f0aec4fe4ed767378004cb1d71eaf64e568a71764f58ad2

Observation af5d4f5f-ffef-4552-9b60-0230d1ce19aa · inbound

iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data cites this paper.

iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data Graph Neural Networks with Learnable Structural and Positional Representations

Reference 19

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no resolver link, observed 2026-08-08T19:23:23.227707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:23:23.227707Z digest=sha256:202af50338f200e7ea7d3ca292736c23a75690d7712521b8661508d89349d128

Observation 604d6e6d-adb6-4ec6-baf7-f3baad7ff16f · inbound

Guixu: Valuation-Driven Data Discovery for Autonomous AI Agents with On-Chain Attestation cites this paper.

Guixu: Valuation-Driven Data Discovery for Autonomous AI Agents with On-Chain Attestation Graph Neural Networks with Learnable Structural and Positional Representations

Reference 23

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no resolver link, observed 2026-08-12T00:39:39.437167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T00:39:39.437167Z digest=sha256:11bf7912e360890310d2e23b58b98833d47c9c2c66768a9daf4639df2ba7a7b8