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Paper Citation Record · LEDGER

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams

As of 18 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.19282.

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

pith.paper-citation-record.v1
2506.19282 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:12:04.703179Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

47 of 47 outbound references displayed

  • verified exact3
  • verified fuzzy6
  • unresolved36
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b58bf228-8dfd-4cd4-82d6-0dea39229bc3 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:12:09.984318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:01.769421Z digest=sha256:441d3706b340c7f63f4582ce401609ae2d4dcd67bd829a9b9ed4264b1c79f35a

Observation 0bf46ab9-4c40-45f0-af31-eda8c2e20c90 · outbound

This paper cites Arghal, E.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Arghal, E

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T23:12:09.828953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:01.903983Z digest=sha256:15dcf78b2237bc6bdd2eab80cf485a4360f29ff254eb524abb1ec9aa819e026d

Observation 368e8f84-bdcd-4a54-99f6-5d652a7f1283 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 3

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raw_fallback, observed 2026-08-06T23:12:09.703321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:01.944533Z digest=sha256:cc9fa6bd27bb1a360b243c7d8c17ac49f42693b9fcce3255c0ebaeef48bfd8bb

Observation 143bcd90-730b-492a-a36a-0cb688db44f9 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:12:09.550493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.029043Z digest=sha256:bf1b2d4409849d94238aa51c43e349b883bbc8e56ceb8e3cb520af9b2fd4b3d4

Observation 8a2bc3e0-0e9e-4134-bfa9-f57a404f68da · outbound

This paper cites A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges

Reference 5

Resolution
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no resolver link, observed 2026-08-06T23:12:02.087994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:02.087994Z digest=sha256:a755df2a21e3f786dbc79003f1218f8e4ee651628abf5bee5d6faf038c3033f0

Observation df0748c1-b7d5-424b-b2ff-2d8e8dab72eb · outbound

This paper cites Upper and lower bounds for the Lipschitz constant of random neural networks.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Upper and lower bounds for the Lipschitz constant of random neural networks

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:12:05.296721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.172706Z digest=sha256:551ef487b7e444b8a1aff45a76cd7fdbb6f9375cc44ed1011d46f05f3a30c273

Observation 007c6f6b-1bd3-491f-942d-9827ee460045 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 7

Resolution
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raw_fallback, observed 2026-08-06T23:12:09.385683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.232688Z digest=sha256:45497676319c956f26a19c4d4f42a234f7d644547e8edd2a931f5ac087ccee4b

Observation 22ed8b43-4317-42da-b4fb-8439d6ae6562 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 8

Resolution
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raw_fallback, observed 2026-08-06T23:12:09.271850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.268126Z digest=sha256:7395eb4717e1b3eb5502dfc71525f2d3f1a9dad1f6a116e50143cc8109867dde

Observation d7b47829-7e56-4606-aa91-3b107f4273cc · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 9

Resolution
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no resolver link, observed 2026-08-06T23:12:02.331293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:02.331293Z digest=sha256:55802299f00487e5a4665d1aa537db0859725fc0981e56f2867da355e09ee8a9

Observation 53beb072-f074-4d7e-a588-c1ce1704eeab · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 10

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no resolver link, observed 2026-08-06T23:12:02.373511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:02.373511Z digest=sha256:f296d1f130d41fa44496b6d175b68b4eea29d95596b042decd7635b429a94eb3

Observation b10df4ec-0910-4ec8-9747-89a4496c795a · outbound

This paper cites Hamilton, Rex Ying, and Jure Leskovec.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Hamilton, Rex Ying, and Jure Leskovec

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:12:09.118895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.420518Z digest=sha256:3a096588e43513eb7c76cd9ae0721215cdcc90ffc27eb02ff5c99337574e8c74

Observation ce1288f4-fab0-4783-b97f-68e92f98f70e · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-06T23:12:02.462283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:02.462283Z digest=sha256:b5754acac9cd7fe3a4a511d70cb33f51c625458430eb0ada2460a7f3155ddf9a

Observation a3e3c47e-0567-4564-8142-5d6269c55ea6 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 13

Resolution
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raw_fallback, observed 2026-08-06T23:12:08.827303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.574236Z digest=sha256:505fd07438ea6635de5be1e36c7a84cb1e5d0367f7e5562f4519ca1987ff0ef7

Observation fabcea6f-0cd3-45bd-ae61-b91aaa5009b0 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 14

Resolution
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raw_fallback, observed 2026-08-06T23:12:08.686181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.652209Z digest=sha256:1cccbe1169d11bf3db497e1856d58d1979727d0617f0775b5326ea0a69c2ae1e

Observation 1d932dcc-daa1-4fca-b007-3542984ab0a6 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Semi-Supervised Classification with Graph Convolutional Networks

Reference 15

Resolution
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no resolver link, observed 2026-08-06T23:12:02.731887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:02.731887Z digest=sha256:384ccaf6554a32e531519ee622b94d0e5f9010153e4522ed181f1840c14f58e4

Observation d7d513dc-4dad-4bb0-9a4a-84f045e97628 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 16

Resolution
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raw_fallback, observed 2026-08-06T23:12:08.570195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.769254Z digest=sha256:1b79a7f18b524085706d568b44bb29da0ebe065f48a39b0ab6a6d046d9306d43

Observation 91fa7373-fb5f-4004-ada1-3b47808ddc66 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 17

Resolution
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raw_fallback, observed 2026-08-06T23:12:08.429771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.840213Z digest=sha256:e61fb96cccdf53d0b634163f3dc23d06300f4f27c3a95b5da28661c5a07ac30c

Observation d8e6747f-16d4-4869-94ce-846b73c135cb · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-06T23:12:02.894199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:02.894199Z digest=sha256:7d432ccb2e833e3699d36ff52952e7cd1c4995237525be57c28cc8e2b7ffdc96

Observation 4cac62a6-e8da-40aa-b094-356cb71359ca · outbound

This paper cites Dynamic Graph Learning-Neural Network for Multivariate Time Series Modeling.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Dynamic Graph Learning-Neural Network for Multivariate Time Series Modeling

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:12:05.170054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.954516Z digest=sha256:d4b34604a6be2ad5471a9dddfc404d0adce7c0c413602f8825a08fc54de95465

Observation 90689471-5068-457b-98fb-5c63f3ebe8ba · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 20

Resolution
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raw_fallback, observed 2026-08-06T23:12:08.280180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.019024Z digest=sha256:cbad249564bdeecf918b021b32dd72a7fadd1b5f1137d781d9befbc48954dc6f

Observation 5f3fafe1-291f-428b-8dda-bfa31875abda · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 21

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no resolver link, observed 2026-08-06T23:12:03.066531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:03.066531Z digest=sha256:959beb94d20e18898ee26ec152ff04adfdbc92bfb9fc576d62353db6ef4b09c4

Observation 08156981-c23e-4cab-9799-f5e1eece2a40 · outbound

This paper cites Geom-GCN: Geometric Graph Convolutional Networks.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Geom-GCN: Geometric Graph Convolutional Networks

Reference 22

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no resolver link, observed 2026-08-06T23:12:03.113234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:03.113234Z digest=sha256:4e46b961849b69cf3d832cc427b7d66a952c2ae5458dceb066cf68308702ccf5

Observation 4f476f45-a5df-4ac4-8e56-e41bd833b06a · outbound

This paper cites Understanding Optimization of Deep Learning via Jacobian Matrix and Lipschitz Constant.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Understanding Optimization of Deep Learning via Jacobian Matrix and Lipschitz Constant

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:12:04.988291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.201720Z digest=sha256:2250a4b8888f06a727e31281321db8b0df2e8ce6d895a738ab89a7202ae6b8cf

Observation ccfb032e-6b78-4206-ae7f-0970bb9b1ebe · outbound

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

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Temporal Graph Networks for Deep Learning on Dynamic Graphs

Reference 24

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no resolver link, observed 2026-08-06T23:12:03.253416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:03.253416Z digest=sha256:5d766ae2620ac466d36fe2e9ded470da5e1f877bcfa721792b096f716b5ca33f

Observation 6419544e-9410-427e-a956-1b37cee4e728 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 25

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raw_fallback, observed 2026-08-06T23:12:08.158063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.317954Z digest=sha256:e8aac4d9a05e57209a631684e89569274e01c3571f46f54caf4ac653c3e1e2e8

Observation 161b8baa-cb6f-4253-8677-8fbc8b0208df · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 26

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raw_fallback, observed 2026-08-06T23:12:08.021418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.424586Z digest=sha256:487b7940fa29403c5741db6f61ffdeff0f9dd4450a65e3304becd9a5a2f8cee8

Observation 591511be-d439-43b3-a75d-da6d750b8d88 · outbound

This paper cites PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks

Reference 27

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no resolver link, observed 2026-08-06T23:12:03.489658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:03.489658Z digest=sha256:be123d35463b9fab10c82c0be91e75432c520d1cc923151f162b6485bfdc3ede

Observation 40b30211-68bb-4dc1-88f3-431c4501c4d7 · outbound

This paper cites Szegedy, W.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Szegedy, W

Reference 28

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raw_fallback, observed 2026-08-06T23:12:07.910441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.585992Z digest=sha256:4e2fc18ac2fcdf2a407e82a3efe31cfeb386484f5ec1475fe8e93d1029dea573

Observation 4d284501-88ea-463c-8469-3a06ca97ee95 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-06T23:12:07.710313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.623600Z digest=sha256:fcd5d34194099be2de1818cdd8577d24ed6b5b0724305fad2ddea94db85f5fdc

Observation 332b55c3-25a1-4657-8b93-a40aaa1ed182 · outbound

This paper cites Graph Attention Networks.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Graph Attention Networks

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:03.704804Z digest=sha256:70acd9a38e0e32ef393205fb96e2c6334bb445cf519eaff7104eb9355eeec99d

Observation d85c2999-205d-4041-9999-d9a04ee30308 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 31

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raw_fallback, observed 2026-08-06T23:12:07.518484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.782486Z digest=sha256:b8d123fa37d3218b4eede190f30b3ca57e65d5a1b30b98fee78daabc3d2a2fce

Observation 1564a082-e6c6-4517-bebb-3575418e22aa · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-06T23:12:07.292488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.843793Z digest=sha256:e3510ec4f969256a4fe77c78fdcc5c25092de6dbc33a77b01e63d41ee6daf3e2

Observation ae663a5d-650a-4eb4-bb80-9757dffb7890 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 33

Resolution
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raw_fallback, observed 2026-08-06T23:12:07.060441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:03.925662Z digest=sha256:9779436d6b5fa908c9d24dbd3cb78f1d523f83eb0380b161983e6a3b24c92fa2

Observation 58891532-5e85-4054-a810-85761be6eb2d · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 34

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no resolver link, observed 2026-08-06T23:12:03.976862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:03.976862Z digest=sha256:c2d667e5aa82eee126c6655577e5481cb6ccca94eaa9e3ca779805959b06d585

Observation 5855fcc8-731b-4e88-b3c2-db2edbcc4c08 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 35

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no resolver link, observed 2026-08-06T23:12:04.035417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:04.035417Z digest=sha256:44091d210a92065912b82da9fe49f31428266cb55c7e1145fa114c540c8b4de6

Observation 1a13bc4d-3022-4932-9950-0b3f7ea4f1b1 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 36

Resolution
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raw_fallback, observed 2026-08-06T23:12:06.775343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:04.151682Z digest=sha256:ae62d1a80fb1acd7dd2bc9281e0287cdd98379d5e5620e6cdcc2dc39deea7751

Observation e5784359-d934-4e7f-a347-3019b5d27aca · outbound

This paper cites Hamil- ton, and Jure Leskovec.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Hamil- ton, and Jure Leskovec

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-06T23:12:06.524334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:04.233418Z digest=sha256:7dce8afb891e47de5ce0fd1aa75528af6eebc7c399c5efdd98aa88bf053a27fd

Observation 0059f42a-9cdf-4a54-84e3-06e3aca0b649 · outbound

This paper cites Inductive Representation Learning on Temporal Graphs.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Inductive Representation Learning on Temporal Graphs

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T23:12:04.111354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:04.111354Z digest=sha256:58cedffc330d3f564ee981073bcc4be8f275958264fff119fa1a3afe64864200

Observation 9e309b1e-4a22-4e10-a5b9-f2c14c376a8f · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:12:06.016562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6823225b-f6b5-4cd2-b4ef-fe36ab1ea90f · outbound

This paper cites TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T23:12:04.524177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:04.524177Z digest=sha256:6d75d6ef57d877469c32939aec3afa562eee6af4b1d5e1a6685cd5d82124148d

Observation 09687911-6a94-4a9c-a990-745bc56cdf5c · outbound

This paper cites Mueller, R.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Mueller, R

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:12:06.268427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:04.312617Z digest=sha256:a965df7389bdc057a6e0ea2bdeab1f13d22abe590d8ad12a2aef144732c4925b

Observation 311939f6-b004-4e8d-abf9-e3d25af0d122 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:12:05.739361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:04.665466Z digest=sha256:39bb3f41446d437d5ebda497ee7aa41c4d68fc818084fed3f93bb6c0d046f32b

Observation 96719a7e-a689-44be-b5df-e8c4cdfdc030 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:12:05.871938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:04.467841Z digest=sha256:d55c6c60aa08901547858a66f7ead4e42f9cf8876d665d2b711d47e5c37eaf21

Observation 7d394e6e-15e5-47fa-825a-68771aa3099e · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T23:12:04.607710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:04.607710Z digest=sha256:ac82784aa8b4896f232133b3a1eceb6be62ab8959fa223777806a8ec5bd5cc81

Observation 529f0795-0179-4031-97e5-050813803db2 · outbound

This paper cites an unresolved cited work.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Unresolved cited work

Reference 47

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T23:12:05.600728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:04.703179Z digest=sha256:2dfe118296f5054c1ff79b89fc831f5965c1dec532d0bfc312f8ae5f3e938acc

Observation 3f54cb03-1b82-4c11-9620-bf04c8d8f626 · outbound

This paper cites On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory

Reference 2020

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T23:12:05.452275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:01.858488Z digest=sha256:3ee66ef8b95722d406f5692fcbbe66bbf612b667d34fbc93664daa2aeffa8db1

Observation ce95b0dd-7fe4-4514-af8c-8bc45c22da4e · outbound

This paper cites In Neural Information Processing Systems.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams In Neural Information Processing Systems

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:12:08.982282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T23:12:02.528938Z digest=sha256:83fe4a08b6d9a0d1e0ecc9d5fe0c92fbd7faac96f4daa8982d9d2d5279ee7786

Pith citing papers

No inbound Pith citation observations are available.