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Paper Citation Record · LEDGER

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation

As of 15 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2412.11180.

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

pith.paper-citation-record.v1
2412.11180 v3

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:18:23.788315Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

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

51 of 51 outbound references displayed

  • verified exact3
  • verified fuzzy35
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 35887879-f25b-41a5-9cb9-42e3044db97c · outbound

This paper cites Distilhubert: Speech representation learning by layer-wise distillation of hidden-unit bert.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Distilhubert: Speech representation learning by layer-wise distillation of hidden-unit bert

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.403635Z digest=sha256:c045f2c59ad107b328a402ae3a42597b7967128ef11424f55a065cfe93832e90

Observation bbeb55d8-bb2e-448f-99ae-2efa12cc4d6d · outbound

This paper cites Measuring and relieving the over-smoothing problem for graph neural networks from the topological view.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Measuring and relieving the over-smoothing problem for graph neural networks from the topological view

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:27.067843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.465637Z digest=sha256:db6202b79ac9ea14fa7f698d730cc81612a9b8cbf4d6899181e42a21aa507bf9

Observation 1a501718-74b2-4a6f-8d3d-271074d17cd0 · outbound

This paper cites On graph neural networks versus graph-augmented mlps.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation On graph neural networks versus graph-augmented mlps

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:27.044285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.532956Z digest=sha256:0fd3d2dee6c5ffe457f13e41cafa8596a15beaf7399d65d3bdb74d71433909ac

Observation 2c45e650-5563-4785-97d6-8ca44749acf4 · outbound

This paper cites Simple and deep graph convolutional networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Simple and deep graph convolutional networks

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:27.018404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.593720Z digest=sha256:84ca8d8c7c1b99a2d5f1a0e1cf549793b8dc1e007fddc5fc5eb8c0106f1b722a

Observation 3f9c89ff-5434-4254-b080-28e545a63f4e · outbound

This paper cites Graph-free knowledge distillation for graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Graph-free knowledge distillation for graph neural networks

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.987585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.661988Z digest=sha256:783a3f5087f15984a21f97d0e4dc0345bdfd749c667a05c8ddc625b0fe04b5f7

Observation e0464db3-42d0-4498-931e-97e4b0cead08 · outbound

This paper cites Effective illicit account detection on large cryptocurrency multigraphs.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Effective illicit account detection on large cryptocurrency multigraphs

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.958064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.729384Z digest=sha256:2dca36b27364024567f2a82d25a10aca0d4ac3928662dc9766862def64165dfc

Observation 335db149-2297-4f7e-b41b-8ed01577149c · outbound

This paper cites Rayleigh quotient graph neural networks for graph-level anomaly detection.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Rayleigh quotient graph neural networks for graph-level anomaly detection

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.812643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.739229Z digest=sha256:9a971072ba6ea03ae5fa4468f43ef614841438aa3240212a128d144f0c0dec95

Observation 901d99d9-116b-4d80-a4bd-cef7045721fa · outbound

This paper cites Spacegnn: Multi-space graph neural network for node anomaly detection with extremely limited labels.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Spacegnn: Multi-space graph neural network for node anomaly detection with extremely limited labels

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.597439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.748065Z digest=sha256:01f2554781c9e3625df9fc5c88536097ca88b5af42baaa39cfa8d9921a596213

Observation f9328c73-4a85-4f93-864e-69ab27b908c8 · outbound

This paper cites Smoothgnn: Smoothing-aware gnn for unsupervised node anomaly detection.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Smoothgnn: Smoothing-aware gnn for unsupervised node anomaly detection

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.569941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.755341Z digest=sha256:7c3310021ca2500c4e4365400e5b920f16cd89bbaa8f15df61d9c54b34a6d2dc

Observation 5e373ede-bc9b-41c2-8990-964442df251c · outbound

This paper cites Freekd: Free-direction knowledge distillation for graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Freekd: Free-direction knowledge distillation for graph neural networks

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.540873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.761988Z digest=sha256:1d48d23b1a698402b019f94b6026b7a46b35911b2d472fd6bb2dbefe7c214cf9

Observation 727d583d-2600-4584-b221-d277727867d4 · outbound

This paper cites Hamilton, Rex Ying, and Jure Leskovec.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Hamilton, Rex Ying, and Jure Leskovec

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.510495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.769235Z digest=sha256:2452a9a976f3b27ec2f11b17a1a58c4851748db5543009cf4a074d152d9501ce

Observation 55037a33-7eb4-4bb4-a839-b6e63d19e6f7 · outbound

This paper cites Mlpinit: Embarrassingly simple GNN training acceleration with MLP initialization.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Mlpinit: Embarrassingly simple GNN training acceleration with MLP initialization

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.470788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.778207Z digest=sha256:4cd0e050993ac06c0dec6bdf3a5aba9fedcde7dbfc850805a83c039cd1c66a6c

Observation 675057e2-88b0-4507-96e3-4f6dbde30fdf · outbound

This paper cites Open graph benchmark: Datasets for machine learning on graphs.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Open graph benchmark: Datasets for machine learning on graphs

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T15:18:22.795138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:22.795138Z digest=sha256:258e8a496dd60e0f492a70444f9296f33f2be31fe5998a9fd8c90a98485f16d2

Observation 930b5f90-d78c-42c0-9095-429673c09d8a · outbound

This paper cites Graph-MLP: Node Classification without Message Passing in Graph.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Graph-MLP: Node Classification without Message Passing in Graph

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T15:18:22.806558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:22.806558Z digest=sha256:dea5ede3cb00254e465db6d925556de801f59e0c31c59c834904c1bb34a0d70f

Observation 798dea18-9119-45b9-8609-a344344babd5 · outbound

This paper cites A Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation A Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting

Reference 16

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unresolved
no resolver link, observed 2026-08-11T15:18:22.816573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:22.816573Z digest=sha256:b6382eb33bd2bf00fb01f770c15a1c969866dad18bb2b0ac6d1e3f7fa13698bf

Observation a951d897-434a-4ff0-9671-219789973b9f · outbound

This paper cites Redundancy-free computation for graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Redundancy-free computation for graph neural networks

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.416172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.822432Z digest=sha256:f7ce69c098488b87e726c343c1c1a7c6624b617dde05c0faee92d658360f06ea

Observation 8996d4ea-f67d-42c8-8a78-c45341cfa5a5 · outbound

This paper cites Tinybert: Distilling BERT for natural language understanding.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Tinybert: Distilling BERT for natural language understanding

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.233951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.834225Z digest=sha256:ff236f57f729e7d3291f856eb57ed0535e389c5dc64fc9cbf20c28a5ef9e1dd3

Observation ecd47cf7-2e4e-4cd8-9908-a3204f266be5 · outbound

This paper cites Kingma and Jimmy Ba.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Kingma and Jimmy Ba

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T15:18:22.844389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:22.844389Z digest=sha256:d3a2e4888307183a83153ed275ad8d1ea70565857b2183dc08d033882fa0b3b9

Observation 9d4926d7-0f35-4a57-844e-9d9192678739 · outbound

This paper cites Kipf and Max Welling.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Kipf and Max Welling

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-11T15:18:22.853778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:22.853778Z digest=sha256:dda9cb80c4d8d0113d9f0ccfd1b5c362c08c7925cb9c3607bca33f0c9eabe87b

Observation ac38aabb-9555-4ffe-932e-3bdb1d6f389b · outbound

This paper cites Predict then propagate: Graph neural networks meet personalized pagerank.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Predict then propagate: Graph neural networks meet personalized pagerank

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.111921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.863714Z digest=sha256:e35ffa6b34a92fabf25b67a004f1af4c4a25ad68e39616314fbc99c430705abb

Observation af2e3e90-a8cd-4b4a-9705-0cf700ee6270 · outbound

This paper cites Graph-based Knowledge Distillation by Multi-head Attention Network.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Graph-based Knowledge Distillation by Multi-head Attention Network

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-11T15:18:24.041153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.871724Z digest=sha256:42ffcba31e3151f3216cea6284e6f0391a24f91a4018f337baafe7d33fb98330

Observation d77ba041-e2a0-4782-8830-ec52305a8fd3 · outbound

This paper cites Layer-level knowledge distillation for deep neural network learning.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Layer-level knowledge distillation for deep neural network learning

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:26.070328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.877960Z digest=sha256:5a5e5735c476ed8bd772f3d2d55efe6cdfc245d7976a10a2009bcd29073a9d37

Observation 0c4d863d-6573-4a38-9b1a-29dbb23f7d20 · outbound

This paper cites Distance encoding: Design provably more powerful neural networks for graph representation learning.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Distance encoding: Design provably more powerful neural networks for graph representation learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.923548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.884878Z digest=sha256:94ffa00792a0dd380f77b3fdfdf8e904699afb297ba5c9604067265915570823

Observation 8017047e-69ed-406b-b6a9-1e62fc1a7b11 · outbound

This paper cites Less is more: Task-aware layer-wise distillation for language model compression.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Less is more: Task-aware layer-wise distillation for language model compression

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.723737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.935513Z digest=sha256:ba1f0ef1946fa06bff2bebbfe06eaf554d4cded4753f4010b3b2a1c7eb72f9e3

Observation b2b46f3a-18b7-4e6e-b631-74b8b009f6d2 · outbound

This paper cites Towards deeper graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Towards deeper graph neural networks

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.642835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:22.998758Z digest=sha256:f20e5b542341544ae1b4196162bf365e7d706f62c14301d9c4bdcfa66efbe11d

Observation 8c4f26e7-4ec5-45d9-9cbb-16f7107c8dc2 · outbound

This paper cites A critical look at the evaluation of gnns under heterophily: Are we really making progress? ICLR, 2023.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation A critical look at the evaluation of gnns under heterophily: Are we really making progress? ICLR, 2023

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.613758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.067676Z digest=sha256:d38f10f28d4e26d2184fe13c9adc7fa969d55b5968178ab06b8e16a7467ef543

Observation e03f70dd-5a52-45d6-bd3e-99bf49a3877e · outbound

This paper cites Multi-scale attributed node embedding.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Multi-scale attributed node embedding

Reference 28

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unresolved
no resolver link, observed 2026-08-11T15:18:23.137488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:23.137488Z digest=sha256:fb5d6bb127f5ae533f017c78b58b30694e7484ea4b4c7acf0b2147c9031a6388

Observation d8b9b2c7-d76d-4463-b269-78d0bdf7a10f · outbound

This paper cites A Survey on Oversmoothing in Graph Neural Networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation A Survey on Oversmoothing in Graph Neural Networks

Reference 29

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unresolved
no resolver link, observed 2026-08-11T15:18:23.232153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:23.232153Z digest=sha256:c765851c6f2d6efa8be828aa4f9523bc884affac2c5608d46227a0ba562ff9f2

Observation 0643a534-9dcd-4bae-8eaf-18b6ae34c464 · outbound

This paper cites Learning mlps on graphs: A unified view of effectiveness, robustness, and efficiency.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Learning mlps on graphs: A unified view of effectiveness, robustness, and efficiency

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.566455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.290372Z digest=sha256:f9683427e2d311d5837b77ae7782ec2131bba4870a84bb950d80a93bb0105d60

Observation d0702eeb-1cce-4173-87ef-86123528ec5c · outbound

This paper cites Knowledge Distillation on Graphs: A Survey.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Knowledge Distillation on Graphs: A Survey

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-11T15:18:23.962938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.296947Z digest=sha256:6191dfdbc32e59ca5eb661836c5500469b32fc596c18aee30243a2cabf989c4a

Observation 6cf586e0-a91c-4878-b914-b76053ef5bb7 · outbound

This paper cites Graph attention networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Graph attention networks

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T15:18:23.305335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:23.305335Z digest=sha256:8dd0e94310b818466eb3328099dd19011a835d085e4e815de4e739248cd43b24

Observation 47795ecc-6447-43dc-af3e-b0e1a95afef1 · outbound

This paper cites Equivariant and stable positional encoding for more powerful graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Equivariant and stable positional encoding for more powerful graph neural networks

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.416095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.311715Z digest=sha256:0f81b9d2e49e20794f0b7c26b4380b477d6d4c027449dbee0811b08a6f6771a9

Observation 7a9f6519-860a-4d27-8cc1-82ccda70d0cf · outbound

This paper cites Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Reference 34

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unresolved
no resolver link, observed 2026-08-11T15:18:23.322842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:23.322842Z digest=sha256:7cea2c947ad0882dc39db73a2e880bcb40e7f25391e1f77dfeb4926b4185b53a

Observation 533fffd7-3e78-49c1-9389-b4ebb74fa3f1 · outbound

This paper cites an unresolved cited work.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-11T15:18:25.196652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.331036Z digest=sha256:66ed8071351a3b13f00da5a6633e3224e3af6eb303cf15614fcfc6b49bf9e9e5

Observation bf80fe3f-9722-4834-9077-f228048842f4 · outbound

This paper cites an unresolved cited work.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-11T15:18:25.098188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.339995Z digest=sha256:03bc4e9a4bed96884b0494632ccd7906078ef3c6fc5b998e6763dead75107eb9

Observation a053731e-eb1e-455b-940a-240feb286de1 · outbound

This paper cites A comprehensive survey on graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation A comprehensive survey on graph neural networks

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.065038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.352441Z digest=sha256:be1012a1a7421ae1ac011bb8f1debd99f9aa6f73a8e30e03daf844b5d956b918

Observation 8e3af4bf-0946-4ca1-a571-cf3048c48259 · outbound

This paper cites Tinygnn: Learning efficient graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Tinygnn: Learning efficient graph neural networks

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:25.040341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.363351Z digest=sha256:4e1855fa738099de8710eeabac1355fb0a23fce9c863171718c6a0ba1794c9fb

Observation a80cec34-0e58-4ed4-92ea-40bfe6851cfc · outbound

This paper cites Extract the knowledge of graph neural networks and go beyond it: An effective knowledge distillation framework.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Extract the knowledge of graph neural networks and go beyond it: An effective knowledge distillation framework

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T15:18:23.374131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:23.374131Z digest=sha256:ab234d043a9c079c655962445fe3f235797e6b02433fb13a7cb276e11fc6e09d

Observation 7633f529-ddb7-45d4-b0a4-0a4fab096be3 · outbound

This paper cites Vqgraph: Rethinking graph representation space for bridging gnns and mlps.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Vqgraph: Rethinking graph representation space for bridging gnns and mlps

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.988011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.383523Z digest=sha256:5f0117893c69d95d14aff52e29a6a400f3a2abac0dcf4392a6e19125bc6edade

Observation 9e1f048c-3a5c-4303-bb67-40e0738707d8 · outbound

This paper cites Distilling knowledge from graph convolutional networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Distilling knowledge from graph convolutional networks

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.901592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.391621Z digest=sha256:bdbcd2401f899f83f4a7a3c78fce6e16e2b7956c9f15b499a4ff9c49523697e2

Observation 989f2dac-c010-4812-a725-9e7109170abd · outbound

This paper cites Position-aware graph neural networks.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Position-aware graph neural networks

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.687725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.402011Z digest=sha256:861a8bb252ef440a62db43157aa91f71590c5ffb47092874f658daee1adc7034

Observation 86330d6d-c460-4a1b-b1ea-0052762212f2 · outbound

This paper cites Diving into unified data-model sparsity for class-imbalanced graph representation learning.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Diving into unified data-model sparsity for class-imbalanced graph representation learning

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.660185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.414380Z digest=sha256:209e7973850f34d87fa2bb61b0c9ec8e4b15978f46e50db8bdf084698eed1378

Observation 2bc6512b-67c6-42d0-8a4c-91835e699a5b · outbound

This paper cites Heterogeneous graph neural network.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Heterogeneous graph neural network

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.631874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.422689Z digest=sha256:6965fb92dee9ec3769811cfe96325b7dee0a9f7280ff1fed2c707906f53ca4b8

Observation ff89b15c-238e-4f41-ba91-4a72a0c26f11 · outbound

This paper cites AGL: a Scalable System for Industrial-purpose Graph Machine Learning.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation AGL: a Scalable System for Industrial-purpose Graph Machine Learning

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-11T15:18:23.877331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.431382Z digest=sha256:33cb22e7bcd82d00933fc9b54dd68e2fb3ac4d955589a85b99b11b7e9bba25b2

Observation 00baefc0-6285-4173-9b83-84433e9ef8f0 · outbound

This paper cites Graph-less neural networks: Teaching old mlps new tricks via distillation.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Graph-less neural networks: Teaching old mlps new tricks via distillation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.595741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.444652Z digest=sha256:732d06d11d16b7a2da866118780fdb5079d4412b2142180ef79eacb0e6732551

Observation a1388a0a-eb35-411f-b7ac-8096a2838baa · outbound

This paper cites Cold brew: Distilling graph node representations with incomplete or missing neighborhoods.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Cold brew: Distilling graph node representations with incomplete or missing neighborhoods

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.568458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.451261Z digest=sha256:3b38088aab978706bf28eae1756b7e0f69043ba8547035884948e0f21ed60d0c

Observation a12ffba8-ea4f-409a-98d7-f3013845be32 · outbound

This paper cites Graph neural networks: A review of methods and applications.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Graph neural networks: A review of methods and applications

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.545406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.457431Z digest=sha256:631e3b2d51d65b14df9a82cae2613e898b113e2b69cd8953d64d1e15257b313d

Observation a5063654-a473-4ff1-8654-43d71ccecf21 · outbound

This paper cites Slotgat: Slot-based message passing for heterogeneous graphs.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Slotgat: Slot-based message passing for heterogeneous graphs

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.510726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.517352Z digest=sha256:4021144b78235fb13a6005b336d009cb8979cdd14c859d966c1aa158cd173e6a

Observation 0eabfd60-f70c-4ddc-8d7a-a2e76abbcef6 · outbound

This paper cites Effective stabilized self-training on few-labeled graph data.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Effective stabilized self-training on few-labeled graph data

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.393646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.615550Z digest=sha256:c59acc23dde59e1ef9be5d57f47b6d2db2d10cb426ae0233c73b4dadcb577b3f

Observation 185dbdad-18d7-453c-8ec9-ef8e7a3c6a2d · outbound

This paper cites Interpreting and unifying graph neural networks with an optimization framework.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation Interpreting and unifying graph neural networks with an optimization framework

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:18:24.190642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T15:18:23.701287Z digest=sha256:c1450322a34abb800a986f2f0d773d23816e0df00be3c280dd838f496c0c724b

Observation ce27870e-5645-40ec-80e9-5e55b9f2c336 · outbound

This paper cites write newline.

TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation write newline

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T15:18:23.788315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:18:23.788315Z digest=sha256:d5c31257d497d1fb9d94b97b27d6ba6badd6165a2b7acbdbd27be8d51e7c2d48

Pith citing papers

No inbound Pith citation observations are available.