Pith. sign in

Paper Citation Record · LEDGER

Continuous Graph Flow

As of 16 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:1908.02436.

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

pith.paper-citation-record.v1
1908.02436 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:51:52.392226Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:33:05.928787Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:39:16.956787Z

Reference resolution

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7bbed681-eadd-466c-acc6-caf4815cc9c2 · outbound

This paper cites Mixed membership stochastic blockmodels.

Continuous Graph Flow Mixed membership stochastic blockmodels

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.884566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.220257Z digest=sha256:f35c9f4652dd16a0af114f78c1581042d2e97ae9b8983f562f15efd8a208a3eb

Observation d47e62c9-af13-4b46-b71e-8a9febf13afd · outbound

This paper cites Statistical mechanics of complex networks.

Continuous Graph Flow Statistical mechanics of complex networks

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.874691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.224718Z digest=sha256:7a2c9c9a2712abe25cdbbc440ddc30eded5e94a878bb651d3fffdf0c7b4640d4

Observation ee04aee3-f1dc-4ef0-81b7-e91742de9fab · outbound

This paper cites Learning structured embeddings of knowledge bases.

Continuous Graph Flow Learning structured embeddings of knowledge bases

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.864280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.228641Z digest=sha256:6b3b4598162efe63f0f4132a4209814e52898c277004fec52a76c6511eae7311

Observation 1103e45d-289e-47ea-804b-cd34af644c73 · outbound

This paper cites Coco-stuff: Thing and stuff classes in context.

Continuous Graph Flow Coco-stuff: Thing and stuff classes in context

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.854659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.232754Z digest=sha256:69d8fefe8db354eae181b20d0aba68ed3a4cf903889e335ee49518b122bdc6cf

Observation dec5eed1-e827-4777-b93c-5ea4c68f7ecb · outbound

This paper cites Neural ordinary differential equations.

Continuous Graph Flow Neural ordinary differential equations

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.844488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.236522Z digest=sha256:df6619681826c6c8471ed7f7aa8aa8b878109bea570656bba1d6e11b69347552

Observation bacb67fc-712a-4a98-89d0-3a0e717c75bc · outbound

This paper cites Density estimation using real nvp.

Continuous Graph Flow Density estimation using real nvp

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.834622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.240196Z digest=sha256:59d5578c6d1c94dee3ed743ede3fdb8dbf6e3ffff3c5489f1fba5ef2570a345a

Observation f9b178a4-00eb-49e7-821f-1ef8e4a5a1e5 · outbound

This paper cites Convolutional networks on graphs for learning molecular fingerprints.

Continuous Graph Flow Convolutional networks on graphs for learning molecular fingerprints

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.824460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.243927Z digest=sha256:3ec7530b1e9ce905e29a3e9b4d8e212ccaa3d7a5372181669a49fd1c3da2a178

Observation a3279211-b5d6-4025-9149-4f9ab67a7579 · outbound

This paper cites On the evolution of random graphs.

Continuous Graph Flow On the evolution of random graphs

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.814219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.247327Z digest=sha256:342eddecf80f2979f6ada0021cb36fbc19b47a62f5d4309b665c6e6b13b6eb27

Observation 36f46bf5-e4fb-4a4f-93f6-df9e771ce443 · outbound

This paper cites Neural message passing for quantum chemistry.

Continuous Graph Flow Neural message passing for quantum chemistry

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.804764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.250936Z digest=sha256:c5cd8b59db97ec0ca7bb491cb6a03bbedd96b35efc8a2ecb75192d377806a109

Observation 1bf779e9-6a10-4fd6-973e-240916188d39 · outbound

This paper cites Ffjord: Free-form continuous dynamics for scalable reversible generative models.

Continuous Graph Flow Ffjord: Free-form continuous dynamics for scalable reversible generative models

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.795239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.254631Z digest=sha256:a6388ab4d9e9b4abe328e65bde5cef07affc05150d46777ccc3a9e6ebc6b192e

Observation c95da8ce-1f94-49a7-b38d-1dd430ff0bc3 · outbound

This paper cites Draw: A recurrent neural network for image generation.

Continuous Graph Flow Draw: A recurrent neural network for image generation

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.785632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.258096Z digest=sha256:5992a2851f117fb8a61734a1eff92dd8afafe229541d9338636e1ce56cea6346

Observation b5d1233c-a87f-4d1e-8438-38dd6f256741 · outbound

This paper cites Graphite: Iterative generative modeling of graphs.

Continuous Graph Flow Graphite: Iterative generative modeling of graphs

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.775898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.261938Z digest=sha256:fb1bab762a84dd21511784fd70194ac3de613f89190596c4663a71e749160a2e

Observation 7416fce1-6f49-42af-8d9a-a164be2ff13d · outbound

This paper cites Variational autoencoders with jointly optimized latent dependency structure.

Continuous Graph Flow Variational autoencoders with jointly optimized latent dependency structure

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.765810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.265519Z digest=sha256:cfd962e683d835d55e8b397b27b721586907ee9f6d2c6713e23aedbd3e7daef0

Observation 291b7612-36f3-4375-8092-3738fdadc648 · outbound

This paper cites Image generation from scene graphs.

Continuous Graph Flow Image generation from scene graphs

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.755652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.268646Z digest=sha256:2f4e267d6f2959b3e5c05c8dc33ad65253fd6c12aad3501564d18e6675f036e6

Observation eea2c6c3-a4aa-4037-9a64-6ea61c75a453 · outbound

This paper cites Layoutvae: Stochastic scene layout generation from a label set.

Continuous Graph Flow Layoutvae: Stochastic scene layout generation from a label set

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.745624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.271829Z digest=sha256:9766394c03859ee94babb0dbf1ec7be5d79b6873cc9e11f1f139f47155a6a828

Observation 3d1abcbb-781e-4264-9acd-b81cbb687b2b · outbound

This paper cites Auto-encoding variational bayes.

Continuous Graph Flow Auto-encoding variational bayes

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.734113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.275186Z digest=sha256:d3a2be339661fe5004dddde4c51a7936361c8d836605f717bbe091542f836f16

Observation 7ade2b73-d859-4a99-a3b4-46fbf3ecc1ee · outbound

This paper cites Glow: Generative flow with invertible 1x1 convolutions.

Continuous Graph Flow Glow: Generative flow with invertible 1x1 convolutions

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.722669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.278644Z digest=sha256:29e184dc15ee877b4cc61a02585a42414639fbd146939b5cf0a8c548d49ed626

Observation 47909bb3-8907-48fa-8597-da8fa65e31b8 · outbound

This paper cites Neural relational inference for interacting systems.

Continuous Graph Flow Neural relational inference for interacting systems

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.711565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.282112Z digest=sha256:641784b51e6e2cbb3a91df24252fbdac0e071e3312942bbeef935e0ae2d0825e

Observation b3b46289-e890-4780-b134-151463073d15 · outbound

This paper cites Variational graph auto-encoders.

Continuous Graph Flow Variational graph auto-encoders

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.701048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.285508Z digest=sha256:c5810fa15cfb8e5bbe28a7dd52ada1438cda50fe4bcce9fbf83534638714fc8f

Observation d3219457-b692-4cf2-9cd5-272548fa0d1f · outbound

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

Continuous Graph Flow Semi-supervised classification with graph convolutional networks

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.690359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.289125Z digest=sha256:d0ca914bbd48b4ba527593e90912a06d44e1b05921737e0167fcbd6d65a7c906

Observation 9aa4b4ce-62ad-4e44-8449-3ef626ca78d6 · outbound

This paper cites Visual genome: Connecting language and vision using crowdsourced dense image annotations.

Continuous Graph Flow Visual genome: Connecting language and vision using crowdsourced dense image annotations

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.679446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.292493Z digest=sha256:61ac662739706ed7cc04dc77e3b00b3147ae262cf8048eb8cde9f793e8818976

Observation 847be55a-6feb-45cd-a2c4-0b8aab7d1914 · outbound

This paper cites Learning multiple layers of features from tiny images.

Continuous Graph Flow Learning multiple layers of features from tiny images

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T14:51:52.295852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T14:51:52.295852Z digest=sha256:35bf8109231479eef6b26e3381f29b01fbede900ee36e97a345c439257477db3

Observation 167b9f4d-0a08-4fb9-9f24-8f676740ce04 · outbound

This paper cites Gradient-based learning applied to document recognition.

Continuous Graph Flow Gradient-based learning applied to document recognition

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.662213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.299221Z digest=sha256:f6d6c476ab42bcf8392c7b5bfa02cf331f6f15d080c7e1f09e72b9279be1539d

Observation 3b0ea9a7-14d5-47ce-b0a1-9a2f7bcc2555 · outbound

This paper cites Kronecker graphs: An approach to modeling networks.

Continuous Graph Flow Kronecker graphs: An approach to modeling networks

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.651362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.302675Z digest=sha256:702ca1fe97e9df1cb450cd3acc4836ffb98750e52e451f61f606a0deb63414bb

Observation 09a37844-0f8a-4f0e-ab37-9651f68b020e · outbound

This paper cites Situation recognition with graph neural networks.

Continuous Graph Flow Situation recognition with graph neural networks

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.641058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.306082Z digest=sha256:7efc381604fc183e8484a620303c2b37b3bb63d56c7131bcf9cc464d4f27c6cf

Observation 4c344087-6231-4d9c-8c72-4727e51af86a · outbound

This paper cites Learning deep generative models of graphs.

Continuous Graph Flow Learning deep generative models of graphs

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.630722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.309770Z digest=sha256:3cba0dc2758fd2039661591d165cb59bfc0afe70efcb6a6604eb5b9ce4ecaacc

Observation 30787a66-03ca-48dc-b48f-b5a487093330 · outbound

This paper cites Variational message passing with structured inference networks.

Continuous Graph Flow Variational message passing with structured inference networks

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.619906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.313754Z digest=sha256:4cbd013ac5ee7cbe2db58194ccda8d94695e2e12e75e604fdb9408e5a1f90c5a

Observation 45d1f87a-3e46-4b85-91fe-bfba09de33f8 · outbound

This paper cites Learning entity and relation embeddings for knowledge graph completion.

Continuous Graph Flow Learning entity and relation embeddings for knowledge graph completion

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.608906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.317663Z digest=sha256:c2b139db2fe1d6e4b966e37762d823cdc80b4da7c0831118db186ba1ea6839e4

Observation 1b60a6b3-0dfe-4366-9cbe-78c1637c1003 · outbound

This paper cites Graph normalizing flows.

Continuous Graph Flow Graph normalizing flows

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.598492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.321065Z digest=sha256:cc41334ff8fa64a0695ca3ea846e4b9e6777116d73f717ff8ccebfab18633f47

Observation 806957e6-f491-4c3e-a04f-1d8b11a97699 · outbound

This paper cites Deep learning face attributes in the wild.

Continuous Graph Flow Deep learning face attributes in the wild

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.588046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.324357Z digest=sha256:a94b115013a96d13a255f76d3c4527b42162f279fbb80828c1f1e8a9f430fe5d

Observation e210ff25-e026-4043-ac0e-5515b3a04bb4 · outbound

This paper cites Variational inference with normalizing flows.

Continuous Graph Flow Variational inference with normalizing flows

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.576951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.327828Z digest=sha256:806d25c40141e952deb5a9d9316b0c2c20b50b9683b50253daf6476a1e73b372

Observation b94de3fa-ea01-4c26-96c1-71dcf966b2aa · outbound

This paper cites A simple neural network module for relational reasoning.

Continuous Graph Flow A simple neural network module for relational reasoning

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.566374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.330843Z digest=sha256:310095ffd1906b7cd469f02513886cb6cd34bfa48db81475104b5da1044120b9

Observation 87fd00ec-45c0-4982-89be-ec2a9d6ff707 · outbound

This paper cites The graph neural network model.

Continuous Graph Flow The graph neural network model

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.555090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.334097Z digest=sha256:847e9bc5390f3ef1eb99caaa4f4f2d08d1670d48c334844c3228073237d96d3f

Observation ba4ad2f9-bb8c-4985-930c-17575cbc1fda · outbound

This paper cites Graphvae: Towards generation of small graphs using variational autoencoders.

Continuous Graph Flow Graphvae: Towards generation of small graphs using variational autoencoders

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.544033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.337486Z digest=sha256:90d75a4b311ea9fbab9d5f8e02ed790ed8ad397038c884a7efc3defa165bad1f

Observation cdda7d4a-e67e-49f0-93e7-bee7bc51dd0b · outbound

This paper cites Graphrnn: Generating realistic graphs with deep auto-regressive models.

Continuous Graph Flow Graphrnn: Generating realistic graphs with deep auto-regressive models

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.532151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.340828Z digest=sha256:91512019893544db7fc93515a4c42efb197786e75c2dd6b2d7b057ab65ae5c10

Observation 7d8605ff-cace-42b0-8da9-e89ced94b396 · outbound

This paper cites An end-to-end deep learning architecture for graph classification.

Continuous Graph Flow An end-to-end deep learning architecture for graph classification

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.521032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.344279Z digest=sha256:21a7ce7ef55b5fbce832fe68ed6703f2eedc65b643369f7757c6fccee74a0505

Observation 37691a69-29c4-4e92-8190-bbf0f1aea295 · outbound

This paper cites Image generation from layout.

Continuous Graph Flow Image generation from layout

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:51:52.505135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-14T14:51:52.347487Z digest=sha256:af0d5e69eeead3dc5a425c00298ce27dcb1716868a23509353f036e2a2bf5cc3

Observation 18c90c07-0d78-42d8-b2b4-401f5c551d77 · outbound

This paper cites write newline.

Continuous Graph Flow write newline

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-14T14:51:52.350884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T14:51:52.350884Z digest=sha256:aae48bd746b421e7b96911fff8bdb0476f246117fc7246462b69db352aa2ba3e

Observation e22b30e6-b7e9-4a7c-a66d-a1a0884f62ee · outbound

This paper cites @esa (Ref.

Continuous Graph Flow @esa (Ref

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-14T14:51:52.355693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T14:51:52.355693Z digest=sha256:e5eca24fd8fd8c6df75b2f8b51a0467660541dcf39ce7a5770a317488964e556

Observation 365d623f-953d-4235-a077-a36705b9da9c · outbound

This paper cites an unresolved cited work.

Continuous Graph Flow Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-14T14:51:52.359631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T14:51:52.359631Z digest=sha256:4e3ebdbe1e40abe167f26a2473327668ebc2ce4d1fe5658ed3c5fec7075d1c00

Observation 5a672fe9-e853-4c0e-9c6a-fc5b6356977d · outbound

This paper cites In this part, we describe implementation details of our model.

Continuous Graph Flow In this part, we describe implementation details of our model

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-14T14:51:52.392226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T14:51:52.392226Z digest=sha256:498ff20764ac9af2ada820ff9fb5c83c22345fc3412a372dc854291aa05bf3dc

Pith citing papers

Observation 71279c51-6c32-49ca-b1d1-7c89c9285b6a · inbound

Graph Neural Controlled Differential Equations For Collaborative Filtering cites this paper.

Graph Neural Controlled Differential Equations For Collaborative Filtering Continuous Graph Flow

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T15:33:05.928787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:33:05.928787Z digest=sha256:384374707b4dc5ae5fac91669c610499de22071fab6e8662415fc7bea650add5

Observation 167d59f6-04b3-4a5b-b5cf-8506aa330225 · inbound

INDEQS: Informed Neural controlled Differential EQuationS cites this paper.

INDEQS: Informed Neural controlled Differential EQuationS Continuous Graph Flow

Reference 114

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:39:16.958618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-26T21:04:38.378400Z digest=sha256:b4574345b01b0798ea6f3ac45c499cfc4501f84982f6ebf98d9d7dfea6a2412c