Pith. sign in

Paper Citation Record · LEDGER

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios

As of 23 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2606.23291.

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

pith.paper-citation-record.v1
2606.23291 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T06:49:47.619411Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

36 of 36 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f093bb4a-e279-4df4-8173-11d73dc200d6 · outbound

This paper cites Proceedings of the 17th ACM International Conference on Web Search and Data Mining , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 17th ACM International Conference on Web Search and Data Mining , pages=

Reference 1

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:eb79052428581b8b73396b5923eae073b1025d0bf759f8d1553ceb57f8e52519

Observation 16722038-a660-4c06-ac95-4a57b03fcb66 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Advances in Neural Information Processing Systems , volume=

Reference 2

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:9c0b67733cf314993889ebade3524f4d866c546589f36e67ac7bb56a44cdb36a

Observation b626a738-cf71-4773-af7a-840f769ffdbd · outbound

This paper cites IEEE Transactions on Big Data , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios IEEE Transactions on Big Data , volume=

Reference 3

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:6a106a67384cc2d6a031b3054b3cf221d482a4e25a22a00ac5a285d4841a0746

Observation b372add0-1696-417a-8903-2f0697ceabd3 · outbound

This paper cites Proceedings of the 18th ACM Conference on Recommender Systems , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 18th ACM Conference on Recommender Systems , pages=

Reference 4

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:34c9797f4cfb2155cecfe15c24e77102c5073929270f371a355cfba4c2e3665a

Observation 5e9d8916-e66f-4f23-b065-7c07dc921ba8 · outbound

This paper cites IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios IEEE/ACM Transactions on Audio, Speech, and Language Processing , volume=

Reference 5

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:5abbdf4e62b22d2169c95530007cec72e4b0bd00a55f7e7a22974892d38ab9cb

Observation 84026604-0f9d-4850-a9c0-6d92307602d7 · outbound

This paper cites Balancing Accuracy and Novelty with Sub-Item Popularity.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Balancing Accuracy and Novelty with Sub-Item Popularity

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:29:51.679389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:8a54bed237cfcbc7b83d0c7e33d5bed84df1d24e2c142803d1e20e7a9dc2b567

Observation b579e0c6-db7d-4d80-86d3-4d0c231c78f4 · outbound

This paper cites Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages=

Reference 7

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:4e1a9f77c844a725e700a1d7a29652b18ca4e41b2e2d1d695f6c3d56546da364

Observation 696719df-34a8-486d-82e8-033ac06f4ea9 · outbound

This paper cites ACM Transactions on Recommender Systems , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios ACM Transactions on Recommender Systems , volume=

Reference 8

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:d8ad9d370866f5c86906afd83c4938c96cad72f24789b1308c67ed52d458baf5

Observation 0ae2349a-443f-4f26-b141-9c0c86b284a1 · outbound

This paper cites Proceedings of the 5th ACM International Conference on Multimedia in Asia Workshops , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 5th ACM International Conference on Multimedia in Asia Workshops , pages=

Reference 9

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:4ff6eaa3961b17221a2b1ed12c3518dfc4cb64425955c1fee7fcd345f197443b

Observation a89d8b71-32da-467a-97ae-b11cadb51c4e · outbound

This paper cites IEEE Assp Magazine , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios IEEE Assp Magazine , volume=

Reference 10

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:9b65b30f2adb2bd43a0b4cd551c9041bcc96d86538aaefa600736e578e8647fa

Observation 41d096b4-1079-488e-8966-a726c09ca74f · outbound

This paper cites IEEE transactions on pattern analysis and machine intelligence , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios IEEE transactions on pattern analysis and machine intelligence , volume=

Reference 11

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:a98c705d207b0dacc5dbd9969b5f012518241f396a350cdf544bdc9ac294923f

Observation 302694a5-6fc8-486f-a356-dc2edd5bf9ba · outbound

This paper cites Proceedings of the 30th ACM International Conference on Information & Knowledge Management , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 30th ACM International Conference on Information & Knowledge Management , pages=

Reference 12

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:053f83eb0f3f5f2357566f4794a110ca4c6064b3598645a3131493881ffb5564

Observation f1e3d7f7-b8a0-4fe7-8f70-5cbd996cc095 · outbound

This paper cites Proceedings of the 28th ACM international conference on information and knowledge management , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 28th ACM international conference on information and knowledge management , pages=

Reference 13

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:60aadfbb0324e37132c0a1f7040d8d55645e7925e3c0177fabc1f3ff33d06786

Observation 17f1af1b-561c-4763-8c74-f08f1805b417 · outbound

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

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Session-based Recommendations with Recurrent Neural Networks

Reference 14

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T12:29:51.675196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:82aa365e7ce3f8dae082ce9ab206243787b2c551c94d609aab214b3e1d8d5b4d

Observation 0891a19a-8658-440b-ba67-ce6b50fdec36 · outbound

This paper cites 2018 IEEE international conference on data mining (ICDM) , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios 2018 IEEE international conference on data mining (ICDM) , pages=

Reference 15

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:600c3258ca212c871ce5f8a50e501b37439961f9da500926a58a0a4bcada786a

Observation 3b5380ba-064c-42c7-92c5-1639d3545cfd · outbound

This paper cites BPR: Bayesian Personalized Ranking from Implicit Feedback.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios BPR: Bayesian Personalized Ranking from Implicit Feedback

Reference 16

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T12:29:51.666137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:e064896edd049b80e33aedafff27f804f8c431a6ddc7022874ea8ed26743504b

Observation 30e8d0ff-bfee-40d7-81b9-4dee4fb496a3 · outbound

This paper cites IEEE Transactions on Multimedia , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios IEEE Transactions on Multimedia , volume=

Reference 17

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:d3660b739276fd73a7d00b1f5903ebdb887f42c5ab0a91df0bda2874fcbf3bdb

Observation 470ac850-ff32-481c-a202-cc44ea02fa46 · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 18

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:791f7bce37697061efac5e97595e631a5481f279f242442425ef3619ceefdcf2

Observation 7fb3ad6b-8dfc-4249-a183-1a7f97e31fc9 · outbound

This paper cites BIT Numerical Mathematics , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios BIT Numerical Mathematics , volume=

Reference 19

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:ba277f64944c0ce236705ae00eb0f03ae88c0f73e6e630cf2a504632c0886d0a

Observation bb0a5b29-a6d9-4c05-bd3f-a0ce7a3dc671 · outbound

This paper cites Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Reference 20

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T12:29:51.672794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:2d4d6b04f31b8490173f06d9160b965a2acae81ad579b54ca134e762a001cf6d

Observation b47dc763-4968-477b-b315-466bd54a2b16 · outbound

This paper cites Proceedings of the 29th ACM international conference on multimedia , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 29th ACM international conference on multimedia , pages=

Reference 21

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:fea6e01928d0f812e3bba0d4d0f3e3d79b6db4236492d0a8abea53498b10336c

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

This paper cites A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions.

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:f329104f8921226063139427c278aef35aba57b3a0fe84696cb67745f84ac4a7

Observation fdf3dbd8-d3db-46bb-b0fa-482263471229 · outbound

This paper cites Communications of the ACM , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Communications of the ACM , volume=

Reference 23

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:f610c09f5f7027245c4fd6bd76a1567ad84886cf4af10a0e7e1c45793ea79fb8

Observation ae633722-0156-4dea-99ce-c9075ada643b · outbound

This paper cites The adaptive web: methods and strategies of web personalization , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios The adaptive web: methods and strategies of web personalization , pages=

Reference 24

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:4f7e705d0c8f4a43ea456fc57a2e82b6672379338eb01eae1bc70a5cd27412b6

Observation 696a31c5-793a-4bca-aca1-7927d409a523 · outbound

This paper cites modality-based recommender models revisited , author=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios modality-based recommender models revisited , author=

Reference 25

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:2d536d6f766f905fd4ee8230993e889fd176daef56068d9664b39de233603d90

Observation 50d0bb01-e274-4838-a349-15f6ef0f6a41 · outbound

This paper cites Expert Systems with Applications , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Expert Systems with Applications , volume=

Reference 26

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:f19c04ecc2d620e55b8b5a14636a581e532cf6b0d04038134f1b3c4482e54d02

Observation 4c6fc631-27f6-4447-8a35-1e5048b6f45a · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Advances in Neural Information Processing Systems , volume=

Reference 27

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:7da72cadd3369b032a160c1dd4f9f7ae9f600af88eca58ce47123b75501ff31e

Observation 1921c554-1e1d-4306-acd1-0698d2983014 · outbound

This paper cites Proceedings of the web conference 2020 , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the web conference 2020 , pages=

Reference 28

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:fc55b2c24df2fec720c074303870b9e130b2d2403add5dd967da071c62a42509

Observation cd1a13e1-73bb-49a1-9dbf-c0edce225998 · outbound

This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages=

Reference 29

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:4b34619b02bfa5ff48e6231c77ed5bf10863619f730f7156975e71d2f4831792

Observation 8ad2efac-efc5-4524-9052-aa44f428e1b1 · outbound

This paper cites Proceedings of the 22nd ACM international conference on Information & Knowledge Management , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 22nd ACM international conference on Information & Knowledge Management , pages=

Reference 30

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:8b6b67935967bdadd47b63788a4cc5e91272db38241112cfb575f1c15db3e9b4

Observation da499c94-f6d5-48fa-9210-a145b4902b51 · outbound

This paper cites Proceedings of the 31st ACM international conference on multimedia , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 31st ACM international conference on multimedia , pages=

Reference 31

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:9452011d14eaf742d3213b62fa3f8c1e747ee94c185fcd0cededc60478d5123d

Observation 40569e7d-18ea-429d-8be5-793d0e1781c2 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Advances in Neural Information Processing Systems , volume=

Reference 32

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:fe80b1c6dc829d82132ef3013d9ae095ad2a3b021f08c2b55d3f4f492a49c33a

Observation 19458fc6-eed9-43b1-badc-4c5883a0bb0c · outbound

This paper cites International Conference on Learning Representations (ICLR) , year=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios International Conference on Learning Representations (ICLR) , year=

Reference 33

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:dae2100b4469fc5fb816082e571e8fc3b6c477c17d269b074f79b4cd6a20d8e8

Observation 3510ecbf-3a05-43bf-995e-a41167a04ddc · outbound

This paper cites fm-2k, and DBbook with multimodal data , author=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios fm-2k, and DBbook with multimodal data , author=

Reference 34

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:9fdd4a9fd475bf302afc87d9e3ed317924e255de55f8b52658abb40e6137965b

Observation 60860bc6-d6b6-4a7e-8a21-9e80fb4e6f4b · outbound

This paper cites , author=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios , author=

Reference 35

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:6fc565dec64557ebf0373ada40004407f9281bc066c0aca04b7eff068439edf3

Observation 3cc3a7ca-bff6-40e8-a0f2-07fcaa5ea8a6 · outbound

This paper cites Proceedings of the 26th international conference on world wide web , pages=.

URecJPQ: Memory-efficient Multimodal Recommendation Models through RecJPQ in Large-Scale Scenarios Proceedings of the 26th international conference on world wide web , pages=

Reference 36

Resolution
unresolved
no resolver link, observed 2026-06-26T06:49:47.619411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-26T06:49:47.619411Z digest=sha256:898473e40baa7fc9848550591a7eef243713701b9475352b4e89d473a405ad70

Pith citing papers

No inbound Pith citation observations are available.