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Paper Citation Record · LEDGER

Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.09698.

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

pith.paper-citation-record.v1
2408.09698 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:09:47.582447Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T20:11:13.474512Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 950a0ed9-a19d-4613-a099-f3ec68477625 · inbound

Large Language Model as Universal Retriever in Industrial-Scale Recommender System cites this paper.

Large Language Model as Universal Retriever in Industrial-Scale Recommender System Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-09T10:09:47.582447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:09:47.582447Z digest=sha256:41d8eaddeace88a32891b76a0a70b0f89f4b840b58d7e67ea7c2e1591bb9df5d

Observation 71c59863-8ed1-4aa7-8500-d92c77b4a0f8 · inbound

Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science cites this paper.

Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T16:53:36.412297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:53:36.412297Z digest=sha256:4ff32b03710142b2f92742a6ae58f1a65607ddf9ee9864619aa7edfdf27d76db

Observation 7687bb78-8330-41a9-8075-e911ef12903d · inbound

Frozen LVLMs for Micro-Video Recommendation: A Systematic Study of Feature Extraction and Fusion cites this paper.

Frozen LVLMs for Micro-Video Recommendation: A Systematic Study of Feature Extraction and Fusion Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-16T20:11:13.476146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T20:09:45.442172Z digest=sha256:cac2a4ceadee4bbdc3d1a816e494dabe8c1ce81d660150801ad024f78014c3cd