{"as_of":"2026-08-08T13:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fad090088502001918076fde1991d9b1839d874429ff2e40fdd622c46b02e41f","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T02:23:46.071601Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2607.25471/citation-record","integrity":"/paper/2607.25471/integrity","json":"/paper/2607.25471/citation-record.json","paper":"/paper/2607.25471"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:23:45.883228Z","title":"Enhancing cross-domain recommendations: Leveraging personality-based transfer learning with probabilistic matrix factorization.Expert Systems with Applications, 263:125667, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.883228Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:f53a13afcf90bb2c37259b11d5106d02d5f868180ecad2797ff653fea9e6058b","observation_id":"a1782017-69bd-43e0-b915-409b8f0c2632","resolution":{"observed_at":"2026-08-01T02:23:45.883228Z","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":"2026-08-01T02:23:45.888977Z","title":"Item2vec: neural item embeddings for collaborative filtering","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.888977Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:c3da91b672c871f720bca80cae81e35fb4cfda345e8540d19058e3b608a0e5af","observation_id":"e3db0dd1-2472-4e19-9356-200d92ae0a48","resolution":{"observed_at":"2026-08-01T02:23:45.888977Z","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":"2026-08-01T02:23:45.893587Z","title":"Towards universal cross-domain recommendation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.893587Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:badf9746b54c461b86f5a49fe158bc8982698fc3a1b522d7e90e11613585de5a","observation_id":"4979da0c-ddb3-404a-a0e1-7458c0551d93","resolution":{"observed_at":"2026-08-01T02:23:45.893587Z","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":"2026-08-01T02:23:45.898809Z","title":"Cross-domain recommen- dation to cold-start users via variational information bottleneck","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.898809Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:2e198b23a42096b9e83cddb427019aabfda8e901f5f81c90554f0f9ad5e4a58f","observation_id":"9e73ad55-b84f-4dff-80d0-4be0853a0584","resolution":{"observed_at":"2026-08-01T02:23:45.898809Z","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":"2026-08-01T02:23:45.903523Z","title":"Wide & deep learning for recommender systems","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.903523Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:248771da32ac472894fd69109a8c113c06feb16d2f825d9f14fc1545dc30d165","observation_id":"5d5121e7-d74f-40af-93f0-a7d045675367","resolution":{"observed_at":"2026-08-01T02:23:45.903523Z","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":"2026-08-01T02:23:45.908263Z","title":"Rakcr: Reviews sentiment-aware based knowledge graph convolutional networks for personalized recommendation.Expert Systems with Applications, 248:123403, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.908263Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:62e9f5cc28950448dacb5f849c9a62911768eac93bc9985029ed29f758757352","observation_id":"598de99f-ca6c-46a9-823c-e43bc68497d7","resolution":{"observed_at":"2026-08-01T02:23:45.908263Z","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":"2026-08-01T02:23:45.913374Z","title":"Homogeneous and heterogeneous relational graph for visible-infrared person re-identification","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.913374Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:66088ee08a6d4470a6c76172b2bce3a1812dd651d1d603a274ea97deefb98a04","observation_id":"3cef9cd4-3bda-4c18-a555-e8f8427c9714","resolution":{"observed_at":"2026-08-01T02:23:45.913374Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.14524","last_updated":"2023-04-04T03:51:27Z","snapshot_observed_at":"2026-08-06T15:51:39.801143Z","submitted_at":"2023-03-25T17:37:43Z","title":"Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.14524","snapshot_observed_at":"2026-08-01T02:23:45.919888Z","title":"Chat-rec: Towards interactive and explainable llms-augmented recommender system","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.919888Z"},"links":{"cited_paper":"/paper/2303.14524","citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:b8dc42486aa10f90a9249525939e74b9713aded7b93b61729c0efee2c89ea120","observation_id":"b1391a6d-f239-4d56-ab90-9a28ef42305a","resolution":{"observed_at":"2026-08-01T02:23:45.919888Z","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":"2026-08-01T02:23:45.925862Z","title":"Recommendation as language processing (rlp): A unified pretrain, personalized prompt & predict paradigm (p5)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.925862Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:1d69bc8e7400361bbf9d0b94eb451c97e3ba2b1add7bef8d87544a8abb3f2cff","observation_id":"8c42a784-b4f3-448c-b137-1ae9faa5e527","resolution":{"observed_at":"2026-08-01T02:23:45.925862Z","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":"2026-08-01T02:23:45.932114Z","title":"node2vec: Scalable feature learning for networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.932114Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:b6830cbc4bf5e1f73f9fcfa87837edd570e1ca148b0a995457105ac86c734e08","observation_id":"5a8a3291-c8a8-4214-be13-3cedabdef99a","resolution":{"observed_at":"2026-08-01T02:23:45.932114Z","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":"2026-08-01T02:23:45.937255Z","title":"Lightgcn: Simplifying and powering graph convolution network for recommendation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.937255Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:33dbf0dd6e3b27d4415d94c5e18de10db69b013006ac64bf97cab43cd0d6ce1b","observation_id":"e7831530-5be0-40dd-8c76-b94bd8ac30f5","resolution":{"observed_at":"2026-08-01T02:23:45.937255Z","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":"2026-08-01T02:23:45.941985Z","title":"Neural collaborative filtering","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.941985Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:5e9d0f03dac0069a044583ac6aff043907198ce97793631849c238fbe7bee768","observation_id":"081a32fc-f06a-421e-a107-0518e7e39f66","resolution":{"observed_at":"2026-08-01T02:23:45.941985Z","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":"2026-08-01T02:23:45.947167Z","title":"Towards universal sequence representation learning for recommender systems","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.947167Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:be276cda37c67e435c57937422d9d882c2cae34d007f0c104a209a0794d49bd1","observation_id":"ceb1554c-5b70-4e3e-a692-72507c0ebb9f","resolution":{"observed_at":"2026-08-01T02:23:45.947167Z","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":"2026-08-01T02:23:45.951719Z","title":"Tag-aware attentional graph neural networks for personalized tag recommendation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.951719Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:05aac57e53f46cc41e49ab21059c9a162e84ae1a288e95760aa4147284f757ed","observation_id":"cda08473-1759-44da-882d-25951719be9c","resolution":{"observed_at":"2026-08-01T02:23:45.951719Z","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":"2026-08-01T02:23:45.956473Z","title":"Matrix factorization techniques for recom- mender systems.Computer, 42(8):30–37, 2009","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.956473Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:7de2efa744c5634592f8e16fb8253229afffe456edc3847edab6d74c35cddded","observation_id":"2ed76a65-77af-49da-91f8-cbce362a9c1c","resolution":{"observed_at":"2026-08-01T02:23:45.956473Z","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":"2026-08-01T02:23:45.961019Z","title":"Text is all you need: Learning language representations for sequential recommendation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.961019Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:de0073855cbbc9d9af80d2f5e02eb3d935f83d2c367fb5d7da98dd2d58f18669","observation_id":"e21ab1ee-7556-4abb-bdc7-ee5807decbc5","resolution":{"observed_at":"2026-08-01T02:23:45.961019Z","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":"2026-08-01T02:23:45.965283Z","title":"Mixed attention network for cross-domain sequential recom- mendation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.965283Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:1cdbdab0e4a8cca22370c8ea8e74f421756acc00f55712ba71476183461a60b1","observation_id":"8c1501a7-bb3d-459a-aa09-8b083db0ca8c","resolution":{"observed_at":"2026-08-01T02:23:45.965283Z","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":"2026-08-01T02:23:45.969707Z","title":"How can recommender systems benefit from large language models: A survey.ACM Transactions on Information Systems, 43(2):1–47, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.969707Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:c62f254768f52c511b350f6226973b57b02ff7ee44dc228a1c0a4d77cde2770a","observation_id":"65603ac1-8179-4518-b599-3c23fe5c92f6","resolution":{"observed_at":"2026-08-01T02:23:45.969707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.10149","last_updated":"2023-10-27T09:11:50Z","snapshot_observed_at":"2026-07-06T15:17:48.587665Z","submitted_at":"2023-04-20T08:16:07Z","title":"Is ChatGPT a Good Recommender? A Preliminary Study","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.10149","snapshot_observed_at":"2026-08-01T02:23:45.974038Z","title":"Is chatgpt a good recommender? a preliminary study.arXiv preprint arXiv:2304.10149, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.974038Z"},"links":{"cited_paper":"/paper/2304.10149","citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:35997f0d244ead1f4bb56b51c79890eed26936b59b154b519965dfd19817ddca","observation_id":"6d7e58c3-02a8-4bb9-8cae-316cf8804a07","resolution":{"observed_at":"2026-08-01T02:23:45.974038Z","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":"2026-08-01T02:23:45.979004Z","title":"Pre-train, prompt, and recommendation: A comprehensive survey of language modeling paradigm adaptations in recommender systems","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.979004Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:778996047231ace9f79e4360cd03cd5bfdec8ba88ec352f427c190165636a59d","observation_id":"9db913bf-d987-464e-b247-7385448fc250","resolution":{"observed_at":"2026-08-01T02:23:45.979004Z","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":"2026-08-01T02:23:45.983340Z","title":"Poi recommendation for random groups based on cooperative graph neural networks.Information Processing & Management, 61(3):103676, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.983340Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:ea984a76844968d1e40a29fc4b6a9638c3260573831f6455aae2f959a6581866","observation_id":"a9898e27-21dd-4621-ade2-7b3ef0cce3f5","resolution":{"observed_at":"2026-08-01T02:23:45.983340Z","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":"2026-08-01T02:23:45.987888Z","title":"Sequential recom- mendation with metric models based on frequent sequences.Data Mining and Knowledge Discovery, 35:1087–1133, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.987888Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:1b3e26e6964cf97d3514b05dbbf3807d32b3971507c0839dd9ea00905ba3870b","observation_id":"a41ed6a9-4a35-4b22-8929-441de136498b","resolution":{"observed_at":"2026-08-01T02:23:45.987888Z","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":"2026-08-01T02:23:45.992214Z","title":"Exploring false hard negative sample in cross-domain recommendation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.992214Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:fdbeafe233609b471e8a2f39766363b1e6341f365bbe4c3dcbcf6533f70bbde3","observation_id":"7f4e4fa2-663b-4514-b5d3-e343474ad524","resolution":{"observed_at":"2026-08-01T02:23:45.992214Z","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":"2026-08-01T02:23:45.997317Z","title":"From theory to practice: The evolution and comparative analysis of homogeneous vs","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:45.997317Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:ac44fafe53530b224acf959d157520f5d52bedb0c7333bab3a85cc61154ec2d3","observation_id":"2ac33fcb-ab52-4d1f-b74b-ca46b72cf0b7","resolution":{"observed_at":"2026-08-01T02:23:45.997317Z","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":"2026-08-01T02:23:46.002374Z","title":"Improving the accuracy of collaborative filtering recommendations using clustering and associa- tion rules mining on implicit data.Computers in Human Behavior, 67:113–128, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.002374Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:a461fb2a07ed7b01f67dabf83a176352861d3e518b9b77696226e1e82823e7af","observation_id":"ea424200-663f-4db8-86e8-530b5e9d577e","resolution":{"observed_at":"2026-08-01T02:23:46.002374Z","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":"2026-08-01T02:23:46.008153Z","title":"Deepwalk: Online learning of social repre- sentations","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.008153Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:6c869527338e82fe1e7667db3280b6149e2a133923ad1041cf8d6934d348b556","observation_id":"dc18f7f6-8e1c-49c4-b355-d8b5b1cfbb0d","resolution":{"observed_at":"2026-08-01T02:23:46.008153Z","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":"2026-08-01T02:23:46.012910Z","title":"Representation learning with large language models for recommendation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.012910Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:3be2fbab707724dd873e60c2ce64b53d2058845245f2f3ddac382a08aa9bcc23","observation_id":"7d60dee7-ee58-4b96-ab80-d136f863692b","resolution":{"observed_at":"2026-08-01T02:23:46.012910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.09741","last_updated":"2023-05-30T15:22:50Z","snapshot_observed_at":"2026-08-04T08:37:37.119739Z","submitted_at":"2022-12-19T18:57:05Z","title":"One Embedder, Any Task: Instruction-Finetuned Text Embeddings","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.09741","snapshot_observed_at":"2026-08-01T02:23:46.019790Z","title":"One embedder, any task: Instruction-finetuned text embeddings.arXiv preprint arXiv:2212.09741, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.019790Z"},"links":{"cited_paper":"/paper/2212.09741","citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:0c0c4b5f0f6ebe287a7cb00f384966b61f664523c3abafdb1274077b1421362e","observation_id":"0f9e1693-c7b3-451d-bf0c-b1f733313019","resolution":{"observed_at":"2026-08-01T02:23:46.019790Z","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":"2026-08-01T02:23:46.026484Z","title":"Cross-domain recommendation with user personality.Knowledge-Based Systems, 213:106664, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.026484Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:58dbac267cf3e2c0a6b443e6ba3e86760caf859af89f02cd0363310ae13e9f56","observation_id":"3123de9c-9ecb-43bd-9128-3aa41156f80f","resolution":{"observed_at":"2026-08-01T02:23:46.026484Z","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":"2026-08-01T02:23:46.034581Z","title":"Knowledge-aware graph neural networks with label attention mechanism for recommendation","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.034581Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:a280ec630531df51031138a3b9031d7bbabd4884fafd9457e132bc9bca319fac","observation_id":"66339fe3-f9ab-4b55-9197-7c4a2abc5634","resolution":{"observed_at":"2026-08-01T02:23:46.034581Z","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":"2026-08-01T02:23:46.040194Z","title":"Neural graph collabo- rative filtering","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.040194Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:12da6cb321d7aad8ad722f03f6d6f16b522fc23a535554bfe72647158f707e04","observation_id":"b3d1b233-79c5-425b-b347-be9a7c837014","resolution":{"observed_at":"2026-08-01T02:23:46.040194Z","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":"2026-08-01T02:23:46.044693Z","title":"Het- erogeneous graph attention network","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.044693Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:a5968029575c01cd08717c526e2e3f6a9f3da105b8d28335a255c0967b41a84c","observation_id":"afa960a8-77e1-42e9-b9fb-f5b625b85039","resolution":{"observed_at":"2026-08-01T02:23:46.044693Z","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":"2026-08-01T02:23:46.049022Z","title":"A survey on large language models for recommendation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.049022Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:2337370af529fab76836047a4c26c083663e5f7110e6157fb39364829ed0eeba","observation_id":"f7a4c240-9c01-4e77-9881-4e9acc2206db","resolution":{"observed_at":"2026-08-01T02:23:46.049022Z","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":"2026-08-01T02:23:46.053084Z","title":"Neural node matching for multi-target cross domain recommendation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.053084Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:e32a3ec202874b1130833f7d3a1cae7433a04058b79e79595ee1149e5355251e","observation_id":"3e5582e6-abba-4d79-b5a5-caf52b8d73b6","resolution":{"observed_at":"2026-08-01T02:23:46.053084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.04825","last_updated":"2020-01-07T23:02:07Z","snapshot_observed_at":"2026-08-06T19:09:15.467813Z","submitted_at":"2020-01-07T23:02:07Z","title":"Enabling the Analysis of Personality Aspects in Recommender Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.04825","snapshot_observed_at":"2026-08-01T02:23:46.057260Z","title":"Enabling the analysis of personality aspects in recommender systems.arXiv preprint arXiv:2001.04825, 2020","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.057260Z"},"links":{"cited_paper":"/paper/2001.04825","citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:cdf9eea1df0eef3f2069dff7a47370f0c763381286a53067de7fc7611ce1b233","observation_id":"c162e667-57be-4ac4-935f-67b1f66c2d9c","resolution":{"observed_at":"2026-08-01T02:23:46.057260Z","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":"2026-08-01T02:23:46.061918Z","title":"Recommender systems in the era of large language models (llms).IEEE Transactions on Knowledge and Data Engineering, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.061918Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:4a6c5d4e86311406b486ab6e24ff2da3880f752d46da881f0c688448205f7148","observation_id":"d14b13bc-c7ba-45d5-b090-c4f4e7d74d4e","resolution":{"observed_at":"2026-08-01T02:23:46.061918Z","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":"2026-08-01T02:23:46.066001Z","title":"Limitations","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.066001Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:e0147fe862aa86baee9b153de120083a7b1b0cbc03110c1696ece5fac981980c","observation_id":"e86f4821-7eb3-4a03-bb0c-dc6fbf1e8871","resolution":{"observed_at":"2026-08-01T02:23:46.066001Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-01T02:23:46.071601Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-01T02:23:46.071601Z"},"links":{"citing_paper":"/paper/2607.25471"},"observation_digest":"sha256:2c999d7bb9124b34fd3e03018b4906bd43792d39dea395a93918c284ca4865b5","observation_id":"cb891aea-5638-46cd-9823-c7c206db353c","resolution":{"observed_at":"2026-08-01T02:23:46.071601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.25471","last_updated":"2026-07-28T09:03:38Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-06T15:52:27.640233Z","submitted_at":"2026-07-28T09:03:38Z","title":"TRWH: A Text-Driven Random Walk Heterogeneous GNN for Semantic-Aware Sparse Recommendation"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":37,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":38},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.25471."}