Paper Citation Record · LEDGER

A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2302.04473.

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

pith.paper-citation-record.v1
2302.04473 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 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 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:25:46.974599Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:29:51.667993Z

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 a2fbd816-832a-4fd0-88f8-3969f8e25c14 · inbound

A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform cites this paper.

A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T17:24:39.183021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97d72210-1920-4dc1-8cb6-d5dda172bab6 · inbound

MDE: Modality Discrimination Enhancement for Multi-modal Recommendation cites this paper.

MDE: Modality Discrimination Enhancement for Multi-modal Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T19:25:46.974599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fb5cf82-f11b-49de-89d9-f1969f36f5c2 · inbound

VRAgent-R1: Boosting Video Recommendation with MLLM-based Agents via Reinforcement Learning cites this paper.

VRAgent-R1: Boosting Video Recommendation with MLLM-based Agents via Reinforcement Learning A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T20:29:41.844793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 574d6ab9-baad-4d7b-bca4-629b676809d7 · inbound

FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation cites this paper.

FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T19:48:35.108476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bfd2c56-31e7-4f79-9b10-2c78ef0083a9 · inbound

The Best is Yet to Come: Graph Convolution in the Testing Phase for Multimodal Recommendation cites this paper.

The Best is Yet to Come: Graph Convolution in the Testing Phase for Multimodal Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T14:36:54.273491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7442f80-5b27-44ad-b0d6-01a02216d4c3 · inbound

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions cites this paper.

A Scenario-Oriented Survey of Federated Recommender Systems: Techniques, Challenges, and Future Directions A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 132

Resolution: unresolved; no resolver link, observed 2026-08-05T15:41:00.774791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89e822c1-f8c7-4237-aba4-fc1304bcf388 · inbound

Modality Alignment with Multi-scale Bilateral Attention for Multimodal Recommendation cites this paper.

Modality Alignment with Multi-scale Bilateral Attention for Multimodal Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T19:44:04.810278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33d75075-289c-4205-9b8a-c6494bea55d0 · inbound

Hi-SAM: A Hierarchical Structure-Aware Multi-modal Framework for Large-Scale Recommendation cites this paper.

Hi-SAM: A Hierarchical Structure-Aware Multi-modal Framework for Large-Scale Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T00:06:29.303783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6bab82d-6292-435d-9a6c-92962f1d45ec · inbound

Binge Watch: Reproducible Multimodal Benchmarks Datasets for Large-Scale Movie Recommendation on MovieLens-10M and 20M cites this paper.

Binge Watch: Reproducible Multimodal Benchmarks Datasets for Large-Scale Movie Recommendation on MovieLens-10M and 20M A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T22:51:45.165831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0de0c26-9f5b-4587-8f99-6b7ae2796bca · inbound

TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning cites this paper.

TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:08:17.023726Z

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.

Observation 0fef4021-aee1-4ed0-9f01-e84124780921 · inbound

Joint Behavior-guided and Modality-coherence Conditional Graph Diffusion Denoising for Multi Modal Recommendation cites this paper.

Joint Behavior-guided and Modality-coherence Conditional Graph Diffusion Denoising for Multi Modal Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:43:02.855286Z

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.

Observation e5c0604a-712e-415f-a42a-2e09dd321d37 · inbound

FASH-iCNN: Making Editorial Fashion Identity Inspectable Through Multimodal CNN Probing cites this paper.

FASH-iCNN: Making Editorial Fashion Identity Inspectable Through Multimodal CNN Probing A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:46:25.450224Z

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.

Observation 0e6e8bb8-8f30-4bce-9e61-a488ffc985e4 · inbound

Modality-Aware Identity Construction and Counterfactual Structure Learning for ID-Free Multimodal Recommendation cites this paper.

Modality-Aware Identity Construction and Counterfactual Structure Learning for ID-Free Multimodal Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:42:54.769994Z

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.

Observation a5c292f4-4883-409a-b18d-4c962c88bb25 · inbound

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios cites this paper.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T12:29:51.670052Z

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.

Observation 1dc94239-592e-4f1d-b0b7-0661896cea88 · inbound

One Graph, Multiple Gains: Single High-Quality Item-Item Graph for Multimodal Recommendation cites this paper.

One Graph, Multiple Gains: Single High-Quality Item-Item Graph for Multimodal Recommendation A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-31T10:48:39.760303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df917876-9bd3-407e-b71c-5014b3cc4e1c · inbound

Is Personalized Modality Weighting Actually Personalized? A Controlled Audit of Per-User Weighting Claims in Multimodal Recommenders cites this paper.

Is Personalized Modality Weighting Actually Personalized? A Controlled Audit of Per-User Weighting Claims in Multimodal Recommenders A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-08T04:47:16.147189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.