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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:a0f67692dcfc3b09cdbadf9e7259c15ac14fbf6ba28ab4dd86b8c8e8e1ef0f2c

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=sha256:67ea675404b22a8ed92bcfde582d674917955cfc081c96b7108dbc0102d9ff48

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=sha256:6a03eb268327c4a58bb16359570399fef0e80b03c627e2831726a6a6dc2a5d4e

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=sha256:266754b3685388a6838329a9d819fa60797bbded1bb05b2bea17241e104de411

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:a9bccff466c95f19e48c42f2a4cfed7e8dfa1cee1be2a361d0b11a9b788215e7

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=sha256:03fb624fa4e9bc15167d4f83624e6c94f8aefe05fe9fa26466e58f5a145172f8

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=sha256:93605ba410363e8e8f8396a7683a1253183ded720c8972af88fa942d4f541c0a

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=sha256:1036049209e8d8a9b4fdf62e8e2e43696ef7f700c4ceb3e6e7c7b5d8cb8a9946

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=sha256:9ed483d2e858e3605eaff9cf0cca238877613a702fa31f863873b8fd3b93b359

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=sha256:9ac867b90e3a15f39864036613b17375e53ff77adbca4df3f6d6eb28ddd5afcd

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:d59af2a984829b5559608b35325dfa94c40631b28d47a6479cb421b5b2e50bc5

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=sha256:1d80227eaa2a5a0bc2b83c11fd98ac3fa9e75096004fe5fb8c15c007aa86f97a

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:ca0df8595deb547d9eedf5c1be993aedac702f88cdf39bc11ce208a228cf5b82

Pith citing papers

No inbound Pith citation observations are available.