Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:12:29.020671Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:12:29.020671Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
13 of 13 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation fb4a98ac-e048-4d14-abf2-1fef663c7db9 · outbound
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
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.
Observation f31e0727-0eb0-49fb-b6e5-4170abeaf1b5 · outbound
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
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.
Observation cb904834-6b1e-4110-9038-427afe6699c1 · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs SIGN: Scalable Inception Graph Neural Networks
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 338cf7cf-d674-4ec3-8daf-180a019e5a45 · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Heterogeneous Graph Neural Networks with Loss-decrease-aware Curriculum Learning
Reference 6
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.
Observation 1cab827f-99ed-4d6f-92d2-005c580582f0 · outbound
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
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.
Observation a1e727f6-4495-403d-a3e8-55aa55470db8 · outbound
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
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.
Observation 4f9f1fa1-152e-480c-bdd2-680867842431 · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Unresolved cited work
Reference 13
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.
Observation df45d156-6b4a-48d2-adcf-f4137f3ae661 · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Efficient Heterogeneous Graph Learning via Random Projection
Reference 1983
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.
Observation 02d1c187-d27d-4e88-9f76-4341a23f1971 · outbound
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
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.
Observation c7b96676-a6ad-4643-9d72-cb1ff2d115b1 · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Temporal graph neural networks for social recommendation
Reference 2017
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b549dac-4dbe-4e11-8c0a-37f9f829b9bb · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Theoretical analysis of domain adaptation with optimal transport
Reference 2020
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.
Observation a739f1e5-f047-41f4-9641-b68d56dbe3fb · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs approximate of expectation
Reference 2023
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.
Observation 76805763-43db-45dc-860f-a275c1e929bb · outbound
IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs Loss-aware Curriculum Learning for Heterogeneous Graph Neural Networks
Reference 2024
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.