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Paper Citation Record · LEDGER

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs

As of 13 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2411.10957.

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

pith.paper-citation-record.v1
2411.10957 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:12:29.020671Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

13 of 13 outbound references displayed

  • verified exact2
  • verified fuzzy7
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fb4a98ac-e048-4d14-abf2-1fef663c7db9 · outbound

This paper cites Data for t = 2018 and t = 2019 were excluded, and no scaling corrections were applied.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Data for t = 2018 and t = 2019 were excluded, and no scaling corrections were applied

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:12:29.172115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:29.002464Z digest=sha256:986b241e999d1ec709c195f3540ed9513421f04cd77164e858ea591d5ec6f43e

Observation f31e0727-0eb0-49fb-b6e5-4170abeaf1b5 · outbound

This paper cites A.2 T OY EXPERIMENT The purpose of toy experiment was to compare test accuracy obtained when dataset was split chrono- logically and split randomly regardless of time information.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs A.2 T OY EXPERIMENT The purpose of toy experiment was to compare test accuracy obtained when dataset was split chrono- logically and split randomly regardless of time information

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:12:29.158066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:29.006799Z digest=sha256:be10115b242d3d826dc6b976d9c4f5403f77bf4bf737524c546ddd693eed6d86

Observation cb904834-6b1e-4110-9038-427afe6699c1 · outbound

This paper cites SIGN: Scalable Inception Graph Neural Networks.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs SIGN: Scalable Inception Graph Neural Networks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T19:12:28.984329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:12:28.984329Z digest=sha256:e3a053d88057d7f5cd7f77f0c16ce1321efa9ac5356107e0627c8bb532be9ff2

Observation 338cf7cf-d674-4ec3-8daf-180a019e5a45 · outbound

This paper cites Heterogeneous Graph Neural Networks with Loss-decrease-aware Curriculum Learning.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Heterogeneous Graph Neural Networks with Loss-decrease-aware Curriculum Learning

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-12T19:12:29.068772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:28.988795Z digest=sha256:32fdcc8f4c35b5a9f3ee638ac63a51afd8ff6f52081597452ee391df6e5fd4cc

Observation 1cab827f-99ed-4d6f-92d2-005c580582f0 · outbound

This paper cites The figure on the right considers only the 15 labels with the most nodes, redrawing the graph for clarity.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs The figure on the right considers only the 15 labels with the most nodes, redrawing the graph for clarity

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:12:29.185377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:28.998167Z digest=sha256:e622ed2132b0a88c672784772c0e002f9d062b9902412b09417ca56542876297

Observation a1e727f6-4495-403d-a3e8-55aa55470db8 · outbound

This paper cites The performance metric is accuracy, representing the proportion of correctly labeled nodes among all test nodes.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs The performance metric is accuracy, representing the proportion of correctly labeled nodes among all test nodes

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:12:29.144862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:29.010638Z digest=sha256:4c437fde14790c6cb93a86762693134741cc247b4f31637018f4f372af82c214

Observation 4f9f1fa1-152e-480c-bdd2-680867842431 · outbound

This paper cites an unresolved cited work.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-12T19:12:29.116861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:29.020671Z digest=sha256:23f06ada73fd59df09875acda70478c2d8a48168d1b4962fee403f9257723266

Observation df45d156-6b4a-48d2-adcf-f4137f3ae661 · outbound

This paper cites Efficient Heterogeneous Graph Learning via Random Projection.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Efficient Heterogeneous Graph Learning via Random Projection

Reference 1983

Resolution
verified exact
local_arxiv, observed 2026-08-12T19:12:29.102808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:28.975828Z digest=sha256:de74535fa2bc9f0da8c0b22a740e53a513f4259aa99bde27886c3963a24b335c

Observation 02d1c187-d27d-4e88-9f76-4341a23f1971 · outbound

This paper cites Node feature extraction by self-supervised multi-scale neighborhood predic- tion.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Node feature extraction by self-supervised multi-scale neighborhood predic- tion

Reference 2010

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:12:29.210893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:28.971752Z digest=sha256:a28059da9ed3d502673ae9028d50448b1f2ff8d7116d499a3fcf0d66f62685e4

Observation c7b96676-a6ad-4643-9d72-cb1ff2d115b1 · outbound

This paper cites Temporal graph neural networks for social recommendation.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Temporal graph neural networks for social recommendation

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-12T19:12:28.967726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:12:28.967726Z digest=sha256:2f4615e8e89022d194e78c1d93b33f1cd51b12da0d829daefda19c19f2959a06

Observation 3b549dac-4dbe-4e11-8c0a-37f9f829b9bb · outbound

This paper cites Theoretical analysis of domain adaptation with optimal transport.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Theoretical analysis of domain adaptation with optimal transport

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:12:29.198360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:28.980151Z digest=sha256:c60514d5ee0a9f6313625745ce8a3d83974a0a152a5f8a98fe2a6b1e012ab09e

Observation a739f1e5-f047-41f4-9641-b68d56dbe3fb · outbound

This paper cites approximate of expectation.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs approximate of expectation

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:12:29.131034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:12:29.015643Z digest=sha256:19875606a917d151a305e05f917301086d393e38ae41aba4f69d61f4d6d07536

Observation 76805763-43db-45dc-860f-a275c1e929bb · outbound

This paper cites Loss-aware Curriculum Learning for Heterogeneous Graph Neural Networks.

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Loss-aware Curriculum Learning for Heterogeneous Graph Neural Networks

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-12T19:12:28.994090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:12:28.994090Z digest=sha256:ffe73047e9468b132d32a2ef0bab3328e3316b28834d76ef8cc0095193e1f454

Pith citing papers

No inbound Pith citation observations are available.