Paper Citation Record · LEDGER

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums

As of 17 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:1908.08497.

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

pith.paper-citation-record.v1
1908.08497 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:41:37.497402Z

measured 37 of 37 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:32:12.153687Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T13:32:12.776309Z

Reference resolution

36 of 36 outbound references displayed

verified exact3
verified fuzzy16
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d565c85e-1d19-4b9b-bb98-14df6d0329b6 · outbound

This paper cites Breast cancer community,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Breast cancer community,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:39.232241Z

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.

Observation 5c0e3d3e-2cc2-4980-918a-e7d0782dc425 · outbound

This paper cites American cancer society,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums American cancer society,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:39.196803Z

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.

Observation d1cc6b35-2e37-4663-9a2c-5a370cebd5ba · outbound

This paper cites ehealth forum,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums ehealth forum,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:39.158329Z

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.

Observation 110ffcb1-794a-4a11-a521-7e0ce17eba5e · outbound

This paper cites Characterizing the sublanguage of online breast cancer forums for medications, symptoms, and emotions,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Characterizing the sublanguage of online breast cancer forums for medications, symptoms, and emotions,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:39.108583Z

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.

Observation 9a8c7f29-7ade-434f-bb68-8c1f5a4787a1 · outbound

This paper cites Does sustained participation in an online health community affect sentiment?.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Does sustained participation in an online health community affect sentiment?

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:39.071361Z

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.

Observation 7f0c0864-e772-465b-989c-e481212af3d1 · outbound

This paper cites Longitudinal analysis of discussion topics in an online breast cancer community using convolu- tional neural networks,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Longitudinal analysis of discussion topics in an online breast cancer community using convolu- tional neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:39.027771Z

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.

Observation 445f635d-495d-43d8-8abe-de62e083efe8 · outbound

This paper cites Cancer stage prediction based on patient online discourse,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Cancer stage prediction based on patient online discourse,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.993263Z

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.

Observation 677e17c9-58ec-44d6-b991-107c62e5909e · outbound

This paper cites Hierarchi- cal incomplete multi-source feature learning for spatiotemporal event forecasting,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Hierarchi- cal incomplete multi-source feature learning for spatiotemporal event forecasting,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.969826Z

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.

Observation b5fc87ce-44df-403c-a43f-bb630666e4b5 · outbound

This paper cites Multi-instance domain adaptation for vaccine adverse event detection,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Multi-instance domain adaptation for vaccine adverse event detection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.927080Z

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.

Observation 0d0edc7e-62de-4539-acc8-58c5f81c16f1 · outbound

This paper cites Representation Learning over Dynamic Graphs.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Representation Learning over Dynamic Graphs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.167346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b385a7f0-acbf-46ae-a324-66ecb50b1c30 · outbound

This paper cites Dynamic network embedding by modeling triadic closure process.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Dynamic network embedding by modeling triadic closure process

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.182988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3ea90a6-e38c-40c5-bac7-3fb0366e31e1 · outbound

This paper cites dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.191635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6ce084a-172d-4dd0-bd29-f785882a36f3 · outbound

This paper cites Multiple structure- view learning for graph classiﬁcation,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Multiple structure- view learning for graph classiﬁcation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.865771Z

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.

Observation cdb0c4fc-1a2c-4acd-9551-f1c74e3bc5cc · outbound

This paper cites Scalable global alignment graph kernel using random features: From node embedding to graph embedding,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Scalable global alignment graph kernel using random features: From node embedding to graph embedding,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.804165Z

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.

Observation 0bfa7ae4-5815-451e-a69e-acba9ac360a7 · outbound

This paper cites SQL-to-Text Generation with Graph-to-Sequence Model.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums SQL-to-Text Generation with Graph-to-Sequence Model

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-14T11:41:38.313517Z

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.

Observation 194bec67-52b8-4a04-991d-050875e61850 · outbound

This paper cites Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-14T11:41:38.239324Z

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.

Observation ddc67729-5ddf-4c31-aefb-103bcce85fc5 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Neural Machine Translation by Jointly Learning to Align and Translate

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.249075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a893278-c78c-4cee-99ea-e75631f38e19 · outbound

This paper cites Effective Approaches to Attention-based Neural Machine Translation.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Effective Approaches to Attention-based Neural Machine Translation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.265282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87222dd1-585d-4369-a235-7069771fc1ac · outbound

This paper cites Hierarchical attention networks for document classiﬁcation,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Hierarchical attention networks for document classiﬁcation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.767728Z

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.

Observation e77f6a97-57a3-4757-8783-ada30de31a1c · outbound

This paper cites Graph Attention Networks.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Graph Attention Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.280823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d7ea76f-51b5-49ac-858f-2d0d610ffd34 · outbound

This paper cites Graph R-CNN for Scene Graph Generation.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Graph R-CNN for Scene Graph Generation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.287588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8baee1c-ad42-4c2c-a63e-04ca82f1abb4 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.298394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a636074-6de6-4ecf-b746-9dc73840438c · outbound

This paper cites Tree-to-Sequence Attentional Neural Machine Translation.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Tree-to-Sequence Attentional Neural Machine Translation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.307749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fdecab2-a77b-4d50-b48d-3b6b1cf08dc4 · outbound

This paper cites Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.316157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bef5c05-311c-405f-a757-26a7903474be · outbound

This paper cites Deep Graph Translation.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Deep Graph Translation

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-14T11:41:37.846533Z

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.

Observation 4b1257cf-fbe8-4608-aac0-0ee5edf62555 · outbound

This paper cites GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.343485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0484b7a7-8aa5-41c5-8a7f-912ede1eb232 · outbound

This paper cites Learning Deep Generative Models of Graphs.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Learning Deep Generative Models of Graphs

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.359735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99906085-6665-41fa-b58c-9f571cc8914f · outbound

This paper cites Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.381419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61f665c2-779c-42ee-b0d7-56f22ee0298b · outbound

This paper cites The fundamental advantages of temporal networks,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums The fundamental advantages of temporal networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.722080Z

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.

Observation 103a7f3f-c12e-4f6d-bbe5-faa0dfff8bf2 · outbound

This paper cites Sequence to sequence learning with neural networks,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Sequence to sequence learning with neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.675603Z

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.

Observation 380afc4e-1efe-40cb-b7f1-2356d4f06601 · outbound

This paper cites Long short-term memory,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Long short-term memory,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.425804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e7adee7-b769-443b-b82b-2df775e01c20 · outbound

This paper cites Neural machine translation (seq2seq) tutorial,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Neural machine translation (seq2seq) tutorial,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.594766Z

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.

Observation bc8ecc57-3458-4344-b7f8-ed9831953149 · outbound

This paper cites Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problems.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problems

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.451874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c30d36d-742d-4538-9bb1-c039af508425 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Bleu: a method for automatic evaluation of machine translation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:41:38.543011Z

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.

Observation 5d26beb8-7b1f-4814-8131-a58c7dbaa3e3 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries,.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Rouge: A package for automatic evaluation of summaries,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.488870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0bf41c9-91bb-4313-ae0b-0f6f61cd86b5 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums Adam: A Method for Stochastic Optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-14T11:41:37.497402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 4383eb5b-db6b-44c4-b7a4-2db5d76842e7 · inbound

Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation cites this paper.

Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-14T13:32:12.781675Z

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.