Paper Citation Record · LEDGER

HGMP:Heterogeneous Graph Multi-Task Prompt Learning

As of 14 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.07405.

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

pith.paper-citation-record.v1
2507.07405 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:49:14.516202Z

measured 35 of 35 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

35 of 35 outbound references displayed

verified exact0
verified fuzzy31
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4391e80b-edaf-4891-b52a-000394ef7636 · outbound

This paper cites Knowledge-preserving incremental social event detection via heterogeneous gnns.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Knowledge-preserving incremental social event detection via heterogeneous gnns

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:23.871872Z

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.

Observation 7b7717ab-9cf8-4813-ba60-e0e4aeecf33d · outbound

This paper cites Strategies for Pre-training Graph Neural Networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Strategies for Pre-training Graph Neural Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:10.134810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3627b214-1ff9-47ff-abee-019f49bbcec8 · outbound

This paper cites Heterogeneous graph transformer.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Heterogeneous graph transformer

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:21.915939Z

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.

Observation 3984cdcb-2e14-4b86-a21d-6caf0e58ef7e · outbound

This paper cites Prodigy: Enabling in-context learning over graphs.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Prodigy: Enabling in-context learning over graphs

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:21.537673Z

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.

Observation 4083e4de-56d0-487d-bbe4-c621e4d33470 · outbound

This paper cites A survey on knowl- edge graphs: Representation, acquisition, and applica- tions.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning A survey on knowl- edge graphs: Representation, acquisition, and applica- tions

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:21.164550Z

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.

Observation 4b669f7b-7b64-4c10-ad68-d159c1a6b42b · outbound

This paper cites Hdmi: High-order deep multiplex infomax.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Hdmi: High-order deep multiplex infomax

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:20.837445Z

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.

Observation fa09ff4b-8393-4bc4-bea0-19c6e7bcdaf5 · outbound

This paper cites Semi-supervised classification with graph convolutional networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Semi-supervised classification with graph convolutional networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:20.469456Z

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.

Observation 0e480219-97bd-4366-99c5-1f5db22ecc6d · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning The power of scale for parameter-efficient prompt tuning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:19.761972Z

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.

Observation ef3d9cb3-38da-4e89-9f15-940792fc7c62 · outbound

This paper cites Prefix- tuning: Optimizing continuous prompts for generation.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Prefix- tuning: Optimizing continuous prompts for generation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:19.452579Z

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.

Observation 9ca3b506-4727-48db-b290-1e5967b8ec91 · outbound

This paper cites Graphprompt: Unifying pre-training and downstream tasks for graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Graphprompt: Unifying pre-training and downstream tasks for graph neural networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:19.142558Z

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.

Observation f1023d67-f915-4cc3-ac64-815f3e24d54e · outbound

This paper cites Are we really mak- ing much progress? revisiting, benchmarking and refining heterogeneous graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Are we really mak- ing much progress? revisiting, benchmarking and refining heterogeneous graph neural networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:18.820289Z

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.

Observation c4df9d0e-f2dc-484c-8756-74bfd9997b7f · outbound

This paper cites Hetgpt: Harnessing the power of prompt tuning in pre-trained heterogeneous graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Hetgpt: Harnessing the power of prompt tuning in pre-trained heterogeneous graph neural networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:18.513503Z

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.

Observation 6075917e-9a39-49a8-9a4c-50be92943ca8 · outbound

This paper cites Hinormer: Representation learning on heterogeneous information networks with graph trans- former.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Hinormer: Representation learning on heterogeneous information networks with graph trans- former

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:18.316679Z

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.

Observation bcc47400-ea81-4e95-b9d7-fd82247580f2 · outbound

This paper cites Weisfeiler and leman go neural: Higher-order graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Weisfeiler and leman go neural: Higher-order graph neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:18.103061Z

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.

Observation 967de90b-4123-4a07-9419-081d48f8daef · outbound

This paper cites Unsupervised attributed multiplex network embedding.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Unsupervised attributed multiplex network embedding

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:17.824507Z

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.

Observation cc58424d-169b-46ef-bd89-1b03837d7648 · outbound

This paper cites Gppt: Graph pre-training and prompt tuning to generalize graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Gppt: Graph pre-training and prompt tuning to generalize graph neural networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:17.608743Z

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.

Observation 85e6406d-3474-45da-89ca-9e3fffd10a0f · outbound

This paper cites Graph Prompt Learning: A Comprehensive Survey and Beyond.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Graph Prompt Learning: A Comprehensive Survey and Beyond

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:12.732082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49a6cd69-b282-4c49-8734-59aaca0fcbef · outbound

This paper cites Virtual node tuning for few-shot node clas- sification.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Virtual node tuning for few-shot node clas- sification

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:17.322860Z

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.

Observation e92d563f-2c40-4e94-a7e4-6421be8d779b · outbound

This paper cites Graph Attention Networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Graph Attention Networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:13.067777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9634cbae-280a-4bf9-815f-9577c7539343 · outbound

This paper cites Self-supervised heterogeneous graph neural network with co-contrastive learning.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Self-supervised heterogeneous graph neural network with co-contrastive learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:16.725627Z

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.

Observation e5b66de5-6b15-40b8-ab5c-cd9f04f3ca89 · outbound

This paper cites Simgrace: A simple framework for graph contrastive learning without data augmentation.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Simgrace: A simple framework for graph contrastive learning without data augmentation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:16.449880Z

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.

Observation 0d770f4c-aab5-4f75-adda-192db516db15 · outbound

This paper cites From local structures to size generalization in graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning From local structures to size generalization in graph neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:15.885831Z

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.

Observation cc41381c-971a-423c-9e13-9b268e8263e7 · outbound

This paper cites Graph con- trastive learning with augmentations.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Graph con- trastive learning with augmentations

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:15.716095Z

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.

Observation 59eb6278-997f-4bab-aa00-d2b976829120 · outbound

This paper cites Hgprompt: Bridging homogeneous and heterogeneous graphs for few-shot prompt learning.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Hgprompt: Bridging homogeneous and heterogeneous graphs for few-shot prompt learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:15.431578Z

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.

Observation ff7fa0d2-0fa9-4770-ba6f-5e5d3351ae38 · outbound

This paper cites Graph trans- former networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Graph trans- former networks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:15.205129Z

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.

Observation d9bfde4d-132f-4033-a690-2bbf070ed924 · outbound

This paper cites Few-shot learning on graphs.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Few-shot learning on graphs

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:14.954772Z

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.

Observation 77c3171c-0226-46a4-a752-69288df6ab06 · outbound

This paper cites ProG: A Graph Prompt Learning Benchmark.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning ProG: A Graph Prompt Learning Benchmark

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:14.516202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecc44c19-608e-4ad8-b494-b35c096a029f · outbound

This paper cites Understanding attention and gen- eralization in graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Understanding attention and gen- eralization in graph neural networks

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:20.128670Z

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.

Observation c6324ee3-a948-4490-8622-dc74db65eb6e · outbound

This paper cites Hetero- geneous graph attention network.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Hetero- geneous graph attention network

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:16.993506Z

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.

Observation c3b4d28c-3319-4460-949d-a30761bc554d · outbound

This paper cites Universal prompt tuning for graph neural networks.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Universal prompt tuning for graph neural networks

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:23.359176Z

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.

Observation 857ca0a7-4e1a-4888-9731-a2d3c9c8deef · outbound

This paper cites A survey of graph neural networks for recommender systems: Challenges, methods, and directions.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning A survey of graph neural networks for recommender systems: Challenges, methods, and directions

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:22.653184Z

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.

Observation 79112a52-0f3a-4ae8-ac3e-1b477e0eb5a3 · outbound

This paper cites Unified language model pre- training for natural language understanding and genera- tion.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Unified language model pre- training for natural language understanding and genera- tion

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:23.585917Z

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.

Observation 52b47c15-8406-490d-91ee-32ce4a871a30 · outbound

This paper cites Heterogeneous network rep- resentation learning: A unified framework with survey and benchmark.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Heterogeneous network rep- resentation learning: A unified framework with survey and benchmark

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:16.119108Z

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.

Observation 6a17344d-a5d7-410b-b31a-4c00c2bd993d · outbound

This paper cites Knowledge graphs.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Knowledge graphs

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:22.313735Z

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.

Observation 584056e4-0a1d-449a-955e-194cb13b51c8 · outbound

This paper cites Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding.

HGMP:Heterogeneous Graph Multi-Task Prompt Learning Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:23.058110Z

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.

Pith citing papers

No inbound Pith citation observations are available.