Pith. sign in

Paper Citation Record · LEDGER

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations

As of 12 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2508.20945.

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

pith.paper-citation-record.v1
2508.20945 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:46:29.045866Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

9 of 9 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 374f3901-4e1c-4a50-83d7-5058c738e3f0 · outbound

This paper cites Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models.

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T14:46:29.008727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:46:29.008727Z digest=sha256:658907f7db6de6239507d79966e9aaa25c0ac46ffe4ca1e40deddb7f02dec82d

Observation e0f672e5-0572-45db-9486-7c22d12bd950 · outbound

This paper cites IEEE Transactions on Knowledge and Data Engineering 35, 4 (2021), 4106–4123.

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations IEEE Transactions on Knowledge and Data Engineering 35, 4 (2021), 4106–4123

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:46:29.254843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T14:46:29.025339Z digest=sha256:213275b76f139ac7ef48aded76bb6f7e79e5f67be194edd3e4275194ed1eb2ca

Observation a5d5ba5e-60ec-49c5-9179-26e04d233a12 · outbound

This paper cites EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation.

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T14:46:29.033177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:46:29.033177Z digest=sha256:02f2ee856dd13abe42c87ac7769fd810f6f4aba6380d56cb1fb714aef90b17ad

Observation 23051869-ab27-4de4-aff4-8fedcb073d23 · outbound

This paper cites In Proceedings of the 41st International Conference on Machine Learning.

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations In Proceedings of the 41st International Conference on Machine Learning

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:46:29.193575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T14:46:29.045866Z digest=sha256:50595f90cd6b7ed9fb2728a0877745776ec98f34fd68728ac26a2ebda5457aa3

Observation fbad854a-728f-46ff-9492-de5fdb601c22 · outbound

This paper cites Session-based Recommendations with Recurrent Neural Networks.

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations Session-based Recommendations with Recurrent Neural Networks

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-05T14:46:28.986969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:46:28.986969Z digest=sha256:db0f2d2c44998a7a47d8b2d40b67434aa62da2c5256c8261257dec2a8ec8522c

Observation 559a01a4-ab77-4fd6-ba30-d5cc42b4f968 · outbound

This paper cites In 2018 IEEE international conference on data mining (ICDM).

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations In 2018 IEEE international conference on data mining (ICDM)

Reference 2018

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:46:29.308489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T14:46:28.995624Z digest=sha256:8630154f99ff498079729b77ba8a3d422ff52e490d57b66711755e3943dc6784

Observation dfbd6b8f-8ff3-49c0-8cbb-6b76b5ebc3c1 · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-05T14:46:29.015903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:46:29.015903Z digest=sha256:5444763315b55425f2057dcd9a638e9c38bd469ed37acdcf54a410f018938914

Observation 537ca49c-2647-4683-8ddb-b3153e7f403a · outbound

This paper cites In 2023 International Joint Con- ference on Neural Networks (IJCNN).

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations In 2023 International Joint Con- ference on Neural Networks (IJCNN)

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:46:29.224992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T14:46:29.040623Z digest=sha256:f647663a410f221179cbd2b74e8ab3fcb7fbbe90c784c2e24d27bb7e031763b4

Observation d85d21a2-fd0d-44f5-b512-c1e4de15508d · outbound

This paper cites User Modeling and User-Adapted Interaction 34, 5 (2024), 1777–1834.

Efficient Large-Scale Cross-Domain Sequential Recommendation with Dynamic State Representations User Modeling and User-Adapted Interaction 34, 5 (2024), 1777–1834

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T14:46:29.283161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T14:46:29.001559Z digest=sha256:9199789ba4a3f2c29dc6ef25beae19734668a4f7596242d696c26a102fc6c51a

Pith citing papers

No inbound Pith citation observations are available.