{"as_of":"2026-08-07T16:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:63cf2def559f39a5e2c654598e23fced9d3eb23af95977270d8aa1d9c56ded78","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:47:49.249401Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.09998/citation-record","integrity":"/paper/2507.09998/integrity","json":"/paper/2507.09998/citation-record.json","paper":"/paper/2507.09998"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:55.187996Z","title":"Learning fine-grained user interests for micro-video recommendation,","venue":null,"work_id":"4a2c0bf1-a7bd-4753-9e6e-b51e4b0105ea","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.683010Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:2b2c713fa35bd70dc0fa1c6bfea0993181fd09953767a2f8b53c8912a009a963","observation_id":"42dacae1-389c-4fa1-a431-ed01c82c5d05","resolution":{"observed_at":"2026-08-06T17:47:55.322640Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:54.956685Z","title":"An industrial framework for personalized serendipitous recommen- dation in e-commerce,","venue":null,"work_id":"230f8c75-2b76-4875-8cbb-fb43604ebbd4","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.689465Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:4f54de75f779f5c732720bb0109c8f9d7bbe75ee41dbb68686e41f486c5f71d8","observation_id":"6cc1dfce-91d5-45d1-ba9d-4766dd8d3b64","resolution":{"observed_at":"2026-08-06T17:47:55.092034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:54.731016Z","title":"Neural graph collaborative filtering,","venue":null,"work_id":"b205f4e7-b0c4-4843-a431-c02d04e25f9c","year":2019},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.695974Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:092c843104c19e179c181a87b14a6a378f73e2d1014c85285dce0cd287d828ed","observation_id":"fac95266-718f-4b8e-abf1-868f6970d29c","resolution":{"observed_at":"2026-08-06T17:47:54.844662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:54.526930Z","title":"LightGCN: Simplifying and powering graph convolution network for recommendation,","venue":null,"work_id":"c8e05ca3-ce2f-494e-b4ec-749d1240410e","year":2020},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.704959Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:d68c0539d3a70ae28a202d1b60e04b2d2fb1983e63a6341ad0a3731e82cf30e7","observation_id":"1a3a6fc1-be75-4d61-a246-441f194bb5b9","resolution":{"observed_at":"2026-08-06T17:47:54.645091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:54.246826Z","title":"Inter-and intra- domain potential user preferences for cross-domain recommendation,","venue":null,"work_id":"1a4a4e68-4ca8-4c57-81cd-0cf97c8605e3","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.714753Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:e22d2f85cf879d509b8aa02d9ab6e6d3ec5a79e18c2e98af768b28aaf65c264a","observation_id":"dd80382a-b04c-4531-a7ac-36cca7f37161","resolution":{"observed_at":"2026-08-06T17:47:54.382751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:54.034262Z","title":"Multimodal graph contrastive learning for multimedia-based recommendation,","venue":null,"work_id":"b32b7bd8-26c7-4058-9511-3bb3a7d01c1a","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.725927Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:06d64772b38f5b60e4ca9e97cab2dd7a95e661a7f7bfa177df91099f082a85c5","observation_id":"8114bd0c-bb49-48c1-a7de-6af1924f6ae2","resolution":{"observed_at":"2026-08-06T17:47:54.117614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:53.842298Z","title":"Space: Self- supervised dual preference enhancing network for multimodal recommen- dation,","venue":null,"work_id":"18ea9bcb-a447-4f3e-a5c1-8b4820873a2b","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.734918Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:9d54d7dd347922085f1defe3ab98484bc857f1c8f3aa2ab05428a9a3fd46bff6","observation_id":"f40af280-1a57-4bfb-89bb-d18931ae5cc9","resolution":{"observed_at":"2026-08-06T17:47:53.915013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:53.689837Z","title":"A survey on recommender systems using graph neural network,","venue":null,"work_id":"5be42fbf-9858-47a7-bdce-e0fc89b17c4d","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.742121Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:355e31f8d964c1da2ebdbe37fa67b11808d9f0ba0d90b8c6f6fd738491da2584","observation_id":"cb99c0e8-0b22-4a74-9eac-bd4b46e4a264","resolution":{"observed_at":"2026-08-06T17:47:53.753108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:53.578029Z","title":"EditKG: Editing knowledge graph for recommendation,","venue":null,"work_id":"f6ed96b4-d6b6-45f8-84e0-d2f5dbd75e3d","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.749369Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:4c01832d1814531ed56db66dfff320a67d1e8f5a352436ec580e023639581bbf","observation_id":"f1ea0cf2-5c1b-4886-b277-3f525eb4574a","resolution":{"observed_at":"2026-08-06T17:47:53.668743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:53.399450Z","title":"Relation pruning and discriminative sampling over knowledge graph for long-tail recommendation,","venue":null,"work_id":"ae8e1141-a43a-4519-84b0-29e9c4e0bf9e","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.757725Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:565cd59c765278892caae8d67983d4d50c633027afe9708e84f5661df15cda34","observation_id":"96ea0876-610a-4681-b438-6e7c4c62b1a2","resolution":{"observed_at":"2026-08-06T17:47:53.479020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:53.218579Z","title":"Knowledge distillation dealing with sample-wise long-tail problem,","venue":null,"work_id":"e5500484-d483-40ce-9c93-fda695db75e5","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.768861Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:1f76e82da36a46cceb4686240c8db2a58c244d15dd0114792456dd8c278e5583","observation_id":"d05acc7a-a807-4398-9e75-754e69a217ec","resolution":{"observed_at":"2026-08-06T17:47:53.317577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:53.002564Z","title":"Do we really need to drop items with missing modalities in multimodal recom- mendation?","venue":null,"work_id":"c8b8ea62-0960-4d2e-a827-ca83fb24da36","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.777765Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:cce8049e376b7df2fc9388ef40dc921a94d372349a14c9c26f64cdec721b92a6","observation_id":"64c13129-40bd-4cc1-b37e-a0c528e5db87","resolution":{"observed_at":"2026-08-06T17:47:53.102224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:52.804199Z","title":"Improving multi-modal recommender systems by denoising and aligning multi-modal content and user feedback,","venue":null,"work_id":"240c56e9-38d5-47ab-8215-4de24303d537","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.789551Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:ae161e7bd2ba7a8505ea0414ee98b000408a63f9b932890bb588575237f5a3e3","observation_id":"d0f3ce8f-3cd2-4d97-a9ca-2dbaf2c5be3d","resolution":{"observed_at":"2026-08-06T17:47:52.902153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:52.638241Z","title":"Multimodal recommender systems: A survey,","venue":null,"work_id":"63392e26-2415-461f-b4b7-776bcc664d52","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.799979Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:f8a50a023dfdaf568125a32970af3c72972f8966a213940e88798703ddd4934c","observation_id":"198d152c-2697-463e-8f19-6d67546bfcc8","resolution":{"observed_at":"2026-08-06T17:47:52.708745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:52.508531Z","title":"Multi-modal knowledge graphs for recommender systems,","venue":null,"work_id":"57f6346c-9867-4ae4-987c-b5ce868f3806","year":2020},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.809751Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:bf969d382995060ea03c3f7c045f6ea7ade451e43e137ed9cc80b271442cf99b","observation_id":"6c950ab1-2dbe-4dff-aa82-f43fc4ad20c6","resolution":{"observed_at":"2026-08-06T17:47:52.564512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:52.344970Z","title":"Automatic hypergraph generation for enhancing recommendation with sparse optimization,","venue":null,"work_id":"195446b8-c784-4d8b-884b-dbd59b2bd1c7","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.818647Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:4fc33a3f02a0c01069b03a6a5671fbcd80a0a63dd106ec73023ec7151414258b","observation_id":"d2ad7712-ceee-4d23-aaf5-8b2f410e23b0","resolution":{"observed_at":"2026-08-06T17:47:52.420729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:52.204388Z","title":"KGAT: Knowledge graph attention network for recommendation,","venue":null,"work_id":"b7e8183e-702b-449d-957f-f4ca17d6fcdf","year":2019},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.837108Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:2a8fca34f80c400dd7e0af6b0c14c1b1105268c9f64e658f467678f2eaa6d084","observation_id":"bb513037-7c31-41d7-8a82-4193e620ea9a","resolution":{"observed_at":"2026-08-06T17:47:52.280861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:52.032593Z","title":"UltraGCN: Ultra simplification of graph convolutional networks for recommendation,","venue":null,"work_id":"61a64a3b-2127-4279-8e1b-e27cdb909d88","year":2021},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.877488Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:74b207ce7f5c8152a0f0c47130f10a237a7600699928959ab19acf3944720998","observation_id":"4d2c1355-c54c-47c8-bcf1-1b0f34d266de","resolution":{"observed_at":"2026-08-06T17:47:52.126982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:51.860342Z","title":"A tale of two graphs: Freezing and denoising graph structures for multimodal recommendation,","venue":null,"work_id":"3a3e0293-4398-46c9-bcc8-9e58e15dab60","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.901312Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:6fde2aef0807fa5e02aee2c28a0ce3bf387a4fa178faddb231ee070ec1add7fb","observation_id":"69ccd679-2d9c-4241-bca3-f5fcaeef9e21","resolution":{"observed_at":"2026-08-06T17:47:51.932791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:51.723047Z","title":"Attention-guided multi-step fusion: A hierarchical fusion network for multimodal recommendation,","venue":null,"work_id":"9ad0d391-9c99-41a8-b505-ce5fea2033d8","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:47.950236Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:7345959b4f8a08fe0dfaf0d7e84b20319d1971ec32bff6d3cf2930256dd48005","observation_id":"22c5b045-24f6-443f-a14a-fe7ef416b16e","resolution":{"observed_at":"2026-08-06T17:47:51.799165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:51.570750Z","title":"Mining latent structures for multimedia recommendation,","venue":null,"work_id":"fb43f181-5587-4656-a948-bed8bef8306e","year":2021},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.008712Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:1db6e63f874c1f34c80e5c6a69cd631a0f456b006575f34a01d47605198cd4f0","observation_id":"8a8cbacd-ff16-46cd-9ca5-54e3d7cd87d2","resolution":{"observed_at":"2026-08-06T17:47:51.653430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:51.418439Z","title":"Who to align with: Feedback-oriented multi-modal alignment in recommendation systems,","venue":null,"work_id":"e0e11a6e-b43d-419b-818e-0faab07d7ddd","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.039207Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:ff820a82c18f797b1f24d2aca8c59a0f3721d284d1eb0f254392e795f84a38f0","observation_id":"aea283c2-9a93-4ea0-a367-76a71e89ef23","resolution":{"observed_at":"2026-08-06T17:47:51.494100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:51.273031Z","title":"Kb4rec: A data set for linking knowledge bases with recommender systems,","venue":null,"work_id":"943594e8-72e1-4505-85ca-3cb75a45d1e1","year":2019},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.096118Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:274747fdb1f49d0aaaea3ba57aa2c2e2adc8245066e3b1bc6c8a9c0da959b2f2","observation_id":"a067de52-b1ca-42ef-bb3e-4de4bbb8a0b3","resolution":{"observed_at":"2026-08-06T17:47:51.336832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.10084","last_updated":"2019-08-27T08:50:17Z","snapshot_observed_at":"2026-07-06T08:17:05.681370Z","submitted_at":"2019-08-27T08:50:17Z","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.10084","snapshot_observed_at":"2026-08-06T17:47:48.137902Z","title":"Sentence-bert: Sentence embeddings using siamese bert- networks,","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.137902Z"},"links":{"cited_paper":"/paper/1908.10084","citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:7ce4638ecadaba432d7af8e04123ab1087fdc55c9db81e3df8a54afc2e470661","observation_id":"b408f557-a278-48c7-84be-ef50681e343d","resolution":{"observed_at":"2026-08-06T17:47:48.137902Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:48.162773Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.162773Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:f9b0445fc23739ae5fe2815b680c1cbf253964b182a879a56b0dae84f417cd0c","observation_id":"850ebb5d-eae8-4bc6-a0b8-22cc3d6d4945","resolution":{"observed_at":"2026-08-06T17:47:48.162773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:51.088653Z","title":"Learning hybrid behavior patterns for multimedia recommendation,","venue":null,"work_id":"679e76f0-2dd9-41f2-8daa-1b9f4ac65810","year":2022},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.224819Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:69cde04d8d41c330f584416b3d8aae2305222804959c7b5715e5b5413e958c63","observation_id":"bf825c72-1eaf-448f-94f7-92c7396fc7ee","resolution":{"observed_at":"2026-08-06T17:47:51.168917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1205.2618","last_updated":"2012-05-09T18:25:09Z","snapshot_observed_at":"2026-07-06T02:47:58.266745Z","submitted_at":"2012-05-09T18:25:09Z","title":"BPR: Bayesian Personalized Ranking from Implicit Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1205.2618","snapshot_observed_at":"2026-08-06T17:47:48.351897Z","title":"BPR: Bayesian personalized ranking from implicit feedback,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.351897Z"},"links":{"cited_paper":"/paper/1205.2618","citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:f620a550b980b904504eb4c930e719c72e762b34cb8d18f79e7c2dda9eeb76c8","observation_id":"945fa696-e71c-40ec-8942-3cd976ecf870","resolution":{"observed_at":"2026-08-06T17:47:48.351897Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:50.886388Z","title":"Bootstrap latent representations for multi-modal recommendation,","venue":null,"work_id":"183c4f61-5e71-40f1-b7de-881e98d053c1","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.437893Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:30b1fb47d627be653042f3aa5c4c3eee67329ccc6e9da4460297875d4f6c5e37","observation_id":"d751d514-8e09-4bff-ab18-986e4fdc7e57","resolution":{"observed_at":"2026-08-06T17:47:50.982381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:50.713347Z","title":"DiffMM: Multi- modal diffusion model for recommendation,","venue":null,"work_id":"c7bbcfa4-5019-4c60-864d-f3daa53440bc","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.530829Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:d60d6e47e8cd190b7470a766779e685568e691c1936b003cf9aa303c36afdd9c","observation_id":"c5cc2bde-f91b-473d-a575-e1ca127057fe","resolution":{"observed_at":"2026-08-06T17:47:50.779422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:50.563544Z","title":"Knowledge graph contrastive learning for recommendation,","venue":null,"work_id":"202c88a7-a94b-4991-ada9-846f236c8940","year":2022},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.615703Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:d786a9dc22d21302340ec9ef6a6c9657c92c328a3813e30771c676585be3849e","observation_id":"3a474cb4-a331-4ecc-8d8a-ce8604909256","resolution":{"observed_at":"2026-08-06T17:47:50.627374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:50.336514Z","title":"Learning intents behind interactions with knowledge graph for recommendation,","venue":null,"work_id":"67536fc7-520c-4f91-8dac-c01f6f9afc34","year":2021},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.767960Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:480043e7012c6d031f07492b3dc29fd38bc431c237b422fa3b0f85255f4d4bed","observation_id":"9588ce71-4091-4bb1-bade-2cdaea4c6143","resolution":{"observed_at":"2026-08-06T17:47:50.454796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:50.038782Z","title":"Knowledge- adaptive contrastive learning for recommendation,","venue":null,"work_id":"485f335f-2f12-4a2e-8556-045590e1afb5","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:48.905645Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:a1be287969b6b80efd12b4480a52b3328a79741e21e579bedb37b4659227c6f7","observation_id":"2dd19907-2bfb-4950-88b8-1597491c46a5","resolution":{"observed_at":"2026-08-06T17:47:50.132688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:49.801612Z","title":"Knowledge graph self-supervised rationalization for recommendation,","venue":null,"work_id":"a9758d66-85b4-4d60-a1df-74ab6cad0bfc","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:49.037279Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:721c732f9c8a8d77c2be0c92393396bbffdba8a6f2d995544609ca3b61bd1656","observation_id":"e5510993-990f-4315-822c-828c2235ab53","resolution":{"observed_at":"2026-08-06T17:47:49.893274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:49.645438Z","title":"Knowledge-refined denoising network for robust recommendation,","venue":null,"work_id":"d439b352-e298-44d4-b18c-fd3dc5266342","year":2023},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:49.145140Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:b1bbc769bb3baaab50c122ba5db266156e5d5951f61bff71255b33eea780708c","observation_id":"45bbd46c-4b79-4849-8810-d31ec9d456c9","resolution":{"observed_at":"2026-08-06T17:47:49.732209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:47:49.418030Z","title":"DiffKG: Knowledge graph diffusion model for recommendation,","venue":null,"work_id":"ba521a84-5b03-42b5-ad43-4b42961e3f0a","year":2024},"citing_paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:49.249401Z"},"links":{"citing_paper":"/paper/2507.09998"},"observation_digest":"sha256:36801504cbd08c4dee95d1741b27521a1205d47096aff35a29c6f364141a273e","observation_id":"9459a0ed-3b63-4965-bece-da569324e89d","resolution":{"observed_at":"2026-08-06T17:47:49.546098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.09998","last_updated":"2025-07-14T07:32:16Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-06T17:39:50.617155Z","submitted_at":"2025-07-14T07:32:16Z","title":"SLIF-MR: Self-loop Iterative Fusion of Heterogeneous Auxiliary Information for Multimodal Recommendation"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":32},"total_outbound_references":35},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.09998."}