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Paper Citation Record · LEDGER

On the Power of Heuristics in Temporal Graphs

As of 9 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 2 inbound Pith citation observations for arXiv:2502.04910.

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

pith.paper-citation-record.v1
2502.04910 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:05:08.099495Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:09:39.803775Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation c49efd29-b3f9-4c24-87d6-824250fc358f · outbound

This paper cites write newline.

On the Power of Heuristics in Temporal Graphs write newline

Reference 1

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unresolved
no resolver link, observed 2026-08-08T21:05:07.995940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:07.995940Z digest=sha256:326e8867a5d0a0b931bffbe690f6a470cc677ec2a3703a3d90cbf314c0211ee3

Observation 559be85f-746a-4d57-9068-0c356fc9cb69 · outbound

This paper cites Bringing light into the dark: A large-scale evaluation of knowledge graph embedding models under a unified framework.

On the Power of Heuristics in Temporal Graphs Bringing light into the dark: A large-scale evaluation of knowledge graph embedding models under a unified framework

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.776876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation c7eca132-26a4-444d-99fb-2e47ede171a0 · outbound

This paper cites Bias and debias in recommender system: A survey and future directions.

On the Power of Heuristics in Temporal Graphs Bias and debias in recommender system: A survey and future directions

Reference 3

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unresolved
no resolver link, observed 2026-08-08T21:05:08.004468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:08.004468Z digest=sha256:ae2ae9bb9dd38e6231c436cba46e62d5b7cfaec53ef6a8f9b842eb00bac35dad

Observation 3defc9ca-9973-4c08-88f0-24a26704c041 · outbound

This paper cites Do we really need complicated model architectures for temporal networks? In The Eleventh International Conference on Learning Representations, 2023.

On the Power of Heuristics in Temporal Graphs Do we really need complicated model architectures for temporal networks? In The Eleventh International Conference on Learning Representations, 2023

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.759183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.008301Z digest=sha256:a2820540950c78c1fdeeb28902e8b451cbed10e22d4205c88ac1586b880e5ea9

Observation a167497a-2678-4dbd-a2a0-a44c1010c468 · outbound

This paper cites A new data structure for cumulative frequency tables.

On the Power of Heuristics in Temporal Graphs A new data structure for cumulative frequency tables

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.748672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.016250Z digest=sha256:2bb8b3382c04c8e2833728bd45cb8599838276d64f7d3f599ee2d0ea0163133c

Observation 857345e4-0b44-4f73-a4d4-fc90a0e36feb · outbound

This paper cites Long range propagation on continuous-time dynamic graphs.

On the Power of Heuristics in Temporal Graphs Long range propagation on continuous-time dynamic graphs

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.738817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 73fe9920-b5a2-4445-b0bb-dc90275aceee · outbound

This paper cites Benchtemp: A general benchmark for evaluating temporal graph neural networks.

On the Power of Heuristics in Temporal Graphs Benchtemp: A general benchmark for evaluating temporal graph neural networks

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.728839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.024366Z digest=sha256:df50120b7b407757fa328a58fa47e33c952f99a40916ca9ce729e337206c14e7

Observation 38ffa7d7-5ef5-4ead-8a02-5afa1ab61153 · outbound

This paper cites Temporal graph benchmark for machine learning on temporal graphs.

On the Power of Heuristics in Temporal Graphs Temporal graph benchmark for machine learning on temporal graphs

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.719485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.028139Z digest=sha256:d1ee7e1853651442dcd7277ec596bf5dfeff841969af59792ef4415e6d74c135

Observation 29f2d414-9152-4f84-a138-64c6787a1934 · outbound

This paper cites Neural temporal walks: Motif-aware representation learning on continuous-time dynamic graphs.

On the Power of Heuristics in Temporal Graphs Neural temporal walks: Motif-aware representation learning on continuous-time dynamic graphs

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.709968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.031836Z digest=sha256:9fb9048a1bdef7b45180077f071806aee817a083bbb2baade311d49033d7390a

Observation a3fb8079-6c7b-49c8-affb-e20eb7a4bc93 · outbound

This paper cites A survey on popularity bias in recommender systems.

On the Power of Heuristics in Temporal Graphs A survey on popularity bias in recommender systems

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.699918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.035012Z digest=sha256:d57f4172ed73754708db9f41558bd936e7f031fb8b4764423827e41908054ce8

Observation b24b10bb-c68a-43e4-8c91-f1d942c2ec6b · outbound

This paper cites On sampled metrics for item recommendation.

On the Power of Heuristics in Temporal Graphs On sampled metrics for item recommendation

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.690656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.038391Z digest=sha256:0932ff4c1ec934405656d15ba6145f4549718a15b9b86bae724d8333380f85c1

Observation 3e3c188c-1a49-4fcc-a4a9-b29b032afe8f · outbound

This paper cites Predicting dynamic embedding trajectory in temporal interaction networks.

On the Power of Heuristics in Temporal Graphs Predicting dynamic embedding trajectory in temporal interaction networks

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T21:05:08.041630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:08.041630Z digest=sha256:094e553d583f0a0c05e38cdc51655d686462795c8eb219946c57f3dd41f14317

Observation 837b85c2-68ce-4b3e-858c-28b3a85198df · outbound

This paper cites Predicting dynamic embedding trajectory in temporal interaction networks.

On the Power of Heuristics in Temporal Graphs Predicting dynamic embedding trajectory in temporal interaction networks

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.680811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.044803Z digest=sha256:5936cd8a8aae1b20eb384ca1d14a0335568c9fcbeb3192e532cdff78d8265901

Observation af1a5177-2ad4-4ef0-850a-e0895bb20a59 · outbound

This paper cites Neighborhood-aware scalable temporal network representation learning.

On the Power of Heuristics in Temporal Graphs Neighborhood-aware scalable temporal network representation learning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.671286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.047996Z digest=sha256:d2b0485aa6ecaf0f10c7f2b7862cd8118c2bd46c1aeb2bbb052ef15ec07b1395

Observation f9b92182-6bb4-4f63-86fc-b43631ed91a7 · outbound

This paper cites Mixture of link predictors on graphs.

On the Power of Heuristics in Temporal Graphs Mixture of link predictors on graphs

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.662195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.051057Z digest=sha256:6abbf121fb293de2538c93af7e382df67249cf2331259d3cc64367e33a839974

Observation eac65dcc-c0ca-4e89-8f75-55e9e0e40b82 · outbound

This paper cites Towards better evaluation for dynamic link prediction.

On the Power of Heuristics in Temporal Graphs Towards better evaluation for dynamic link prediction

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.653362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.054460Z digest=sha256:3667dd6763a569c52940c3a18c1913ff1e13a4716278df64ccbe3f021c2db982

Observation 2d8670b8-4258-4d56-94a9-d7c8107146d7 · outbound

This paper cites A strong node classification baseline for temporal graphs.

On the Power of Heuristics in Temporal Graphs A strong node classification baseline for temporal graphs

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.644754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a36e1893-917d-45af-9550-a5c101ee1c91 · outbound

This paper cites Temporal Graph Networks for Deep Learning on Dynamic Graphs.

On the Power of Heuristics in Temporal Graphs Temporal Graph Networks for Deep Learning on Dynamic Graphs

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T21:05:08.060637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:08.060637Z digest=sha256:bf3424ce935089bc935e34d634bc5f497000d4f417bf6fb538829cabc30a5656

Observation 5bc12c2d-5f26-4afb-8eaf-bf5b1f70f1a5 · outbound

This paper cites Temporal graph networks for deep learning on dynamic graphs.

On the Power of Heuristics in Temporal Graphs Temporal graph networks for deep learning on dynamic graphs

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.635310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.064557Z digest=sha256:2158e0604fb260807672771da3fc00bd42cde6e370f0fe8c44115b433179d8d9

Observation e62ae758-d8bb-4404-9500-8743aee3e651 · outbound

This paper cites Temporal graph analysis with tgx.

On the Power of Heuristics in Temporal Graphs Temporal graph analysis with tgx

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.625619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.067187Z digest=sha256:dac0c689a7c1f600ba242731d6cc68a4f58ad2d0cf7f70aab9b90a34e50373b2

Observation a3d4ef85-163e-474b-927e-5f6540faf81c · outbound

This paper cites Dyrep: Learning representations over dynamic graphs.

On the Power of Heuristics in Temporal Graphs Dyrep: Learning representations over dynamic graphs

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.615406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.069986Z digest=sha256:ea1f3d50746567e9e7e109318bd67903ef9d40e892d3c0ee1dd23bbc54a51a9f

Observation 1c2f9501-203c-4d64-b81a-fa9638f64c2c · outbound

This paper cites TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning.

On the Power of Heuristics in Temporal Graphs TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T21:05:08.072813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:08.072813Z digest=sha256:d4effabf67f2ec90fed7a830a7eb42ae0ccda0c496c5d088c6357df7e372d362

Observation 5e8e0747-5d2a-430f-ba4d-2ef29782f8e9 · outbound

This paper cites Inductive representation learning in temporal networks via causal anonymous walks.

On the Power of Heuristics in Temporal Graphs Inductive representation learning in temporal networks via causal anonymous walks

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.603988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 742df5ec-fb76-42be-8e48-5191b7c74786 · outbound

This paper cites A survey on the fairness of recommender systems.

On the Power of Heuristics in Temporal Graphs A survey on the fairness of recommender systems

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.593307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.078584Z digest=sha256:d66e349abba9ee0fb24046faf0e8c43c04716aaa71cc2e49e63dbca19e07b43a

Observation 1ec4e6cd-eaa6-4c63-9a15-13a89362f681 · outbound

This paper cites On the feasibility of simple transformer for dynamic graph modeling.

On the Power of Heuristics in Temporal Graphs On the feasibility of simple transformer for dynamic graph modeling

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.582698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.081297Z digest=sha256:1a47d86410c7e8ead577b9a30b1649fb9d10422f10830c6756fdb573cdb75ecf

Observation 203e8a82-fe58-4e0c-ac62-558a43c79dd8 · outbound

This paper cites Inductive representation learning on temporal graphs.

On the Power of Heuristics in Temporal Graphs Inductive representation learning on temporal graphs

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.572357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.084048Z digest=sha256:713c54d6cd0665aaf3afa412af5162f2a15e617129c230ecc816de3edcc42f52

Observation a34700b2-d9b3-4a61-aed7-322c6b391571 · outbound

This paper cites Towards better dynamic graph learning: New architecture and unified library.

On the Power of Heuristics in Temporal Graphs Towards better dynamic graph learning: New architecture and unified library

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T21:05:08.561781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.086802Z digest=sha256:5aa19aefeef4d3a00d2c6b02038d8adfa206e5d0fea6e4f0a08d187c16dca222

Observation 6bec8e8d-5c41-41bc-8594-e9576e92a491 · outbound

This paper cites Efficient neural common neighbor for temporal graph link prediction.

On the Power of Heuristics in Temporal Graphs Efficient neural common neighbor for temporal graph link prediction

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-08T21:05:08.089339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:08.089339Z digest=sha256:ba996f1a75341b9660b8e1dad24f4efc45fa78677dc8ff02e39068f0700463bc

Observation 7687732e-8d48-4ae7-af00-b05a6fbda75e · outbound

This paper cites @esa (Ref.

On the Power of Heuristics in Temporal Graphs @esa (Ref

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-08T21:05:08.092458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:08.092458Z digest=sha256:533dcbc31280f5c896776f35acafc28d53c72631c3818b356a3cb294b3030b02

Observation 179a0c0c-4ea3-4e3c-ad8f-a9a656c435bb · outbound

This paper cites an unresolved cited work.

On the Power of Heuristics in Temporal Graphs Unresolved cited work

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T21:05:08.096128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T21:05:08.096128Z digest=sha256:1f821c0702c16b7931675eae9e0a2cf09846fd2fc65bd256820cc1ddfd37d187

Observation c9eab355-7db4-4500-a19d-73e6b0833f7c · outbound

This paper cites Temporal graph models fail to capture global temporal dynamics.

On the Power of Heuristics in Temporal Graphs Temporal graph models fail to capture global temporal dynamics

Reference 32

Resolution
metadata mismatch
local_arxiv, observed 2026-08-08T21:05:08.536168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-08T21:05:08.099495Z digest=sha256:1ca1280295266d2cbaa9cb29fda02d51fd84b12d3b9001b0df8e3a7cc330e7f7

Pith citing papers

Observation a4d652d7-08e9-4c29-9808-ca0de76e3597 · inbound

Are Large Language Models Good Temporal Graph Learners? cites this paper.

Are Large Language Models Good Temporal Graph Learners? On the Power of Heuristics in Temporal Graphs

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T11:09:39.803775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:09:39.803775Z digest=sha256:f346cf0a8db7274fc8970553b68ee305fb53d698ee21577d7bf0209e8d75e9c1

Observation 101f2cf1-93f7-4720-94bb-d02f43ef4fd6 · inbound

Maximizing Reachability via Shifting of Temporal Paths cites this paper.

Maximizing Reachability via Shifting of Temporal Paths On the Power of Heuristics in Temporal Graphs

Reference 231

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:02:17.264771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T05:00:02.957536Z digest=sha256:3993cc417ba4dffb12f838f6e93bcf91daf2ac69f65ca38d52f45826ee93e670