{"as_of":"2026-08-18T23:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e9646ea60f5f15714622f92f954a0357d9a27bc2e09be52360acccd690d60fbb","coverage":[{"denominator":58,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":58,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T17:46:03.288427Z","state":"measured"},{"denominator":58,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":58,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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/2507.20566/citation-record","integrity":"/paper/2507.20566/integrity","json":"/paper/2507.20566/citation-record.json","paper":"/paper/2507.20566"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:46:04.493623Z","title":"Knowledge graph embedding: A survey of approaches and applications","venue":null,"work_id":"4fc78ea5-80bc-4c32-b1a6-43f59eb53b0a","year":2017},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.008302Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:9d34c58ff03878d9f4bf5928d042e3560775dcb41235c5a7d8c34517cb0328fe","observation_id":"8e7d204d-199d-4fcf-9d30-04a50329e989","resolution":{"observed_at":"2026-08-15T17:46:04.499282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:46:03.014204Z","title":"Knowledge graph embedding for link prediction: A comparative analysis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.014204Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:f9baac56f77728b985c7711f87ec4d1c1bc81c1593b6298ff9eec8bf885a13ce","observation_id":"bd224036-95ce-40f9-b0b4-c093496264c4","resolution":{"observed_at":"2026-08-15T17:46:03.014204Z","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":"2026-08-15T17:46:04.338053Z","title":"Knowledge vault: A web-scale approach to proba- bilistic knowledge fusion","venue":null,"work_id":"736dcb35-80f7-4c74-9928-cabe77f4b8e8","year":2014},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.020020Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:6897b9bf72ba3757e5623851787222b655784a22da0e5b8aa7f1908cd5a62e79","observation_id":"bd32a8bf-c28b-4fb1-a8d1-5a267ac62222","resolution":{"observed_at":"2026-08-15T17:46:04.343610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.320063Z","title":"Open question answering with weakly supervised embedding models","venue":null,"work_id":"29484e86-fc47-4946-8728-68e7e98bdad1","year":2014},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.025104Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:c23d97e1a619a82f2241da329e10df46bc26deac4d1cb26708a784a8a2e47c55","observation_id":"84c83b3c-4a77-4bd7-973d-64c90e7ae3f0","resolution":{"observed_at":"2026-08-15T17:46:04.325245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.302912Z","title":"Semantic parsing via paraphrasing","venue":null,"work_id":"143c252c-567f-41ee-a4c9-7b4b35acaa02","year":2014},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.030166Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:56abe1b230b1dbd35824d031b63bdc826582f0f074c903851eaa857574e92e11","observation_id":"e7eec08d-8188-4da8-a65c-734e1822b82d","resolution":{"observed_at":"2026-08-15T17:46:04.307891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07624","last_updated":"2025-04-10T10:17:08Z","snapshot_observed_at":"2026-08-18T19:00:03.631446Z","submitted_at":"2025-04-10T10:17:08Z","title":"ConceptFormer: Towards Efficient Use of Knowledge-Graph Embeddings in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.07624","snapshot_observed_at":"2026-08-15T17:46:03.034998Z","title":"Conceptformer: Towards efficient use of knowledge-graph embeddings in large language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.034998Z"},"links":{"cited_paper":"/paper/2504.07624","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:3613c69ce56369778835e844de5e2e2b8de381c77d1250fa57b5b359acaafbf4","observation_id":"dfdebf82-6cfc-4902-b7a9-89f52e74104d","resolution":{"observed_at":"2026-08-15T17:46:03.034998Z","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":"2026-08-15T17:46:03.040660Z","title":"A survey of graph unlearning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.040660Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:3d88ddab236166297d08fcf0adc6d5829ba8b70e5a565ef28d693aecbf3a39a3","observation_id":"cabc75ad-b8e0-46b4-9da3-4b4b85fcf9fa","resolution":{"observed_at":"2026-08-15T17:46:03.040660Z","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":"2026-08-15T17:46:04.285995Z","title":"Suchanek, Gjergji Kasneci, and Gerhard Weikum","venue":null,"work_id":"62e67d4e-b092-4dcc-938c-7f90bad28f70","year":2007},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.045277Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:7e1d10d01d23e09b5f65389ee49df4e67f84370d2392607e836a7388dcd327f5","observation_id":"a6f8ed24-9d78-40ab-b8bf-08566956fb9f","resolution":{"observed_at":"2026-08-15T17:46:04.291418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.269267Z","title":"Suchanek, Klaus Berberich, and Gerhard Weikum","venue":null,"work_id":"93a18c2d-629e-4b16-9643-c6e3030d9517","year":2013},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.049905Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:c563afe76535d1f5d88c671e522eb28d6e289604be7dbc60764e383baf8cd25a","observation_id":"246977a5-1262-4750-a0cf-b40aa3aa9e83","resolution":{"observed_at":"2026-08-15T17:46:04.274825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.252363Z","title":"Editing language model-based knowledge graph embeddings","venue":null,"work_id":"2728fba3-6a8e-4153-9cc8-bd7b0c5e39c7","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.054417Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:4ab705899d045d6d150318a093851ca9b7c808ec9dc4f21176bba3eb62eb8714","observation_id":"9812a117-d226-4492-aafa-58e4ca654b16","resolution":{"observed_at":"2026-08-15T17:46:04.257504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:46:03.059031Z","title":"Machine unlearning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.059031Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:6d1742788c67640b9c88328e8dffeaa57a7ff10be0517043c514a16dabc892e1","observation_id":"95da83ac-d9bd-47b6-aec9-b279595d159e","resolution":{"observed_at":"2026-08-15T17:46:03.059031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02238","last_updated":"2023-10-04T05:20:19Z","snapshot_observed_at":"2026-08-18T10:13:38.925008Z","submitted_at":"2023-10-03T17:48:14Z","title":"Who's Harry Potter? Approximate Unlearning in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02238","snapshot_observed_at":"2026-08-15T17:46:03.063524Z","title":"Who’s harry potter? approximate unlearning in llms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.063524Z"},"links":{"cited_paper":"/paper/2310.02238","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:3d541bf89068a6772b8217325ccb083f9ed4065ddbdc3656e78fad0da10de301","observation_id":"922f1057-a8ca-4bbf-8074-0704797ba11e","resolution":{"observed_at":"2026-08-15T17:46:03.063524Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07406","last_updated":"2026-04-20T05:27:15Z","snapshot_observed_at":"2026-07-06T18:13:16.171803Z","submitted_at":"2024-05-13T00:58:34Z","title":"Machine Unlearning: A Comprehensive Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07406","snapshot_observed_at":"2026-08-15T17:46:03.068888Z","title":"Machine unlearning: A comprehensive survey.arXiv preprint arXiv:2405.07406, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.068888Z"},"links":{"cited_paper":"/paper/2405.07406","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:7b64fda4a0a21a120139a3cc33179b3d1b0255983daea35d88a897202fa3b1d3","observation_id":"6cd893f2-6722-4173-86be-059287072899","resolution":{"observed_at":"2026-08-15T17:46:03.068888Z","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":"2026-08-15T17:46:04.225114Z","title":"Eternal sunshine of the spotless net: Selective forgetting in deep networks","venue":null,"work_id":"edd29ea0-37e1-4a7e-9497-7b166f71e51f","year":2020},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.073896Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:616ec8ac0d3cb6284a4515e4a0ab6d7cf2a37b502333d69553b3a3aa7362c545","observation_id":"8b5a3409-88af-41ca-a2cd-0b3e2c6e90aa","resolution":{"observed_at":"2026-08-15T17:46:04.230180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.208512Z","title":"Unrolling sgd: Understanding factors influencing machine unlearning","venue":null,"work_id":"f2908c6d-1d3b-45ba-a185-c31c0e34bec3","year":2022},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.078783Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:9553f84436d0e38dd7d6521f82fce33217253487aceed6fe08d6f0c20bdd44bb","observation_id":"17f6685d-54bb-4fef-84df-46dedcf91b66","resolution":{"observed_at":"2026-08-15T17:46:04.213561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.192603Z","title":"Arcane: An efficient architecture for exact machine unlearning","venue":null,"work_id":"0d2ff26d-927b-4afb-86cd-be50a248d075","year":2022},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.083619Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:92e273ef786d24d218e396ed0d1743a2a24d3836df508fa3ed29c5c9c1b62ede","observation_id":"c01e2d04-0c3e-43c0-8b84-83efc5006270","resolution":{"observed_at":"2026-08-15T17:46:04.197867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.176184Z","title":"Puma: Performance unchanged model augmentation for training data removal","venue":null,"work_id":"2cdae163-d0fa-470f-b0f8-d49297a3cdb4","year":2022},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.088205Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:b4c3dde3c093823d1b561c105406c7c656256d03517abe88635c7e837ff42b9a","observation_id":"f5855e5f-ba69-45b5-b4cc-bc5436864790","resolution":{"observed_at":"2026-08-15T17:46:04.181369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:46:03.092737Z","title":"Convolutional 2d knowledge graph embeddings","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.092737Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:cf461dd6a31de2601c9191b91c7cb88832b487acc9ee5093d3ae0230ad462b8b","observation_id":"2de6720c-25e8-4ba3-9c53-137db621ef43","resolution":{"observed_at":"2026-08-15T17:46:03.092737Z","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":"2026-08-15T17:46:04.149481Z","title":"Representing text for joint embedding of text and knowledge bases","venue":null,"work_id":"1d74c249-10c5-42b7-859a-8bdbdd7d14ba","year":2015},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.097210Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:169c670f75db177b2e33813567201bef6da67f244c4159370ac7346329c34575","observation_id":"ca4ed0da-7551-4b0f-a39f-4fc74581571b","resolution":{"observed_at":"2026-08-15T17:46:04.154954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.132948Z","title":"Codex: A comprehensive knowledge graph completion bench- mark","venue":null,"work_id":"5b74dd94-3ca2-4ecc-8bb9-9d00da2330c7","year":2020},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.101840Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:fba7b88daf31337df45edc6e7cca6d591f3d6802c4aa58ca81b15827c47771d9","observation_id":"5c80dffc-211e-4142-a85a-92014167aa18","resolution":{"observed_at":"2026-08-15T17:46:04.138012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.117174Z","title":"Yago3: A knowledge base from multilingual wikipedias","venue":null,"work_id":"a5395a45-798d-43d3-a9bb-9ca6606c4524","year":2013},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.106605Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:9217bf05954a8dbed011adf1240f9a6688fc5e67a6eac108a066d7d91a0b0dfd","observation_id":"f898fa40-6f9d-405f-9e4f-db7db9862059","resolution":{"observed_at":"2026-08-15T17:46:04.122046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.02299","last_updated":"2024-09-17T11:55:58Z","snapshot_observed_at":"2026-08-18T20:41:01.318983Z","submitted_at":"2022-09-06T08:51:53Z","title":"A Survey of Machine Unlearning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.02299","snapshot_observed_at":"2026-08-15T17:46:03.111419Z","title":"A survey of machine unlearning.arXiv preprint arXiv:2209.02299, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.111419Z"},"links":{"cited_paper":"/paper/2209.02299","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:1ce9c3f248b4471c988c9e81018c369f974a24a8bc6b01e9d95b3b320b4b43d7","observation_id":"031fc26f-6e8b-4429-ab15-36caca0bd9de","resolution":{"observed_at":"2026-08-15T17:46:03.111419Z","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":"2026-08-15T17:46:04.099799Z","title":"Fast machine unlearning without retraining through selective synaptic dampening","venue":null,"work_id":"7dba05ec-b858-4e6c-a73e-6af0b5de8d90","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.116343Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:4d56b09d2b53f09e08b4aecd0cf851f2f5820fc56054d7a1e670121ad54f40ba","observation_id":"50973a96-e45f-4f61-b956-2e92054678c4","resolution":{"observed_at":"2026-08-15T17:46:04.105610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.082390Z","title":"Learning to unlearn: Instance-wise unlearning for pre-trained classifiers","venue":null,"work_id":"ec33a247-0fff-4dac-bbea-e49c13de8b1e","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.120984Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:c7dc1aea51c7f5e7416bf9b165a058d7540b9cf779cf4975e3ec9c500365444d","observation_id":"3c7f4a18-0b63-4ab5-836f-ce43dfa8e376","resolution":{"observed_at":"2026-08-15T17:46:04.087431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.065795Z","title":"Knowledge graph unlearning with schema","venue":null,"work_id":"66fa227c-3f10-43c1-902a-a42b18a0cb3a","year":2025},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.125623Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:9170285af34e646f3785969c8f5d60867515a85c748f9de89aa782bfc4b2eae9","observation_id":"35d27586-e3bb-42c1-a0b6-09879104553f","resolution":{"observed_at":"2026-08-15T17:46:04.070978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.00881","last_updated":"2024-12-01T16:43:04Z","snapshot_observed_at":"2026-08-18T03:00:48.420608Z","submitted_at":"2024-12-01T16:43:04Z","title":"Learn to Unlearn: Meta-Learning-Based Knowledge Graph Embedding Unlearning","version":1},"cited_work":{"arxiv_id":"2412.00881","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.00881","snapshot_observed_at":"2026-08-15T17:46:03.443524Z","title":"Learn to Unlearn: Meta-Learning-Based Knowledge Graph Embedding Unlearning","venue":"cs.AI","work_id":"b3b74f93-6b0a-4550-9092-aa0250c3444e","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.130402Z"},"links":{"cited_paper":"/paper/2412.00881","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:91b9e608d6e91ebb6ac48a23d8d35afbea1bcc0bba762c674920dbd4e1795026","observation_id":"b30d0d74-ea09-4fc0-b1fd-26f1620bc35d","resolution":{"observed_at":"2026-08-15T17:46:03.450666Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.048626Z","title":"Translating embeddings for modeling multi-relational data","venue":null,"work_id":"09653fff-33c5-4394-afd0-6bc4db1429e3","year":2013},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.135286Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:d6cfb9a69e77e40f234d58804b0d7d412f8db204cb2ec3fe5788e677c490354e","observation_id":"38c63b89-347f-49b0-b0ce-54f872838a85","resolution":{"observed_at":"2026-08-15T17:46:04.053888Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.030796Z","title":"Complex embeddings for simple link prediction","venue":null,"work_id":"7121cb1b-c3ba-42dd-96ac-b6803b0082ac","year":2016},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.140070Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:ce863f56558c7b22d8f71cbb6a727db561addf4e1327464bedb5d34ffcd738a7","observation_id":"b6a7b0c7-a655-481e-8460-351ec05d004d","resolution":{"observed_at":"2026-08-15T17:46:04.036368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:04.012122Z","title":"Rotate: Knowledge graph embed- ding by relational rotation in complex space","venue":null,"work_id":"1249799a-9bfa-43a5-b62c-f8d4e3d9466e","year":2019},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.144649Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:d3283529e5f4b028c35603687507bf949271d9084377173f886ac33f60ef30a5","observation_id":"bfe9ba5c-27ae-44da-9f7c-6fd79d39c0d8","resolution":{"observed_at":"2026-08-15T17:46:04.019165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05862","last_updated":"2022-04-12T15:02:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-12T15:02:38Z","title":"Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05862","snapshot_observed_at":"2026-08-15T17:46:03.149299Z","title":"Training a helpful and harmless assistant with reinforcement learning from human feedback","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.149299Z"},"links":{"cited_paper":"/paper/2204.05862","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:8948104ed7eb8dfd4b373249fda3cd046487b42baafb01e07433f9b2b7ce34d1","observation_id":"38bd37e4-3173-4922-8231-f0685fd881ea","resolution":{"observed_at":"2026-08-15T17:46:03.149299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14734","last_updated":"2024-11-01T20:05:19Z","snapshot_observed_at":"2026-08-16T13:50:07.192537Z","submitted_at":"2024-05-23T16:01:46Z","title":"SimPO: Simple Preference Optimization with a Reference-Free Reward","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14734","snapshot_observed_at":"2026-08-15T17:46:03.154242Z","title":"Simpo: Simple preference optimization with a reference-free reward","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.154242Z"},"links":{"cited_paper":"/paper/2405.14734","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:24482d80dd1fc437efcb6486957e782e5997c873b502a50cea956c34453ea3e3","observation_id":"155970b4-1ee4-40bf-8aac-aaf1bc4814e9","resolution":{"observed_at":"2026-08-15T17:46:03.154242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-08-15T20:26:32.102285Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-15T17:46:03.159200Z","title":"Proximal policy optimization algorithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.159200Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:b34abe1545d740057cc48c7eea08758ed8cfd7d544f6ab1148763a1d9f2c9934","observation_id":"285d0600-0f01-4c45-bb43-1fabbb97ef60","resolution":{"observed_at":"2026-08-15T17:46:03.159200Z","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":"2026-08-15T17:46:03.163985Z","title":"Direct preference optimization: Your language model is secretly a reward model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.163985Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:a01dc2f6bed138780554b2b82f3c5762503c86f43745dfe1daaa581a2fdb638b","observation_id":"9130e643-116d-4cf2-817b-658b4781f403","resolution":{"observed_at":"2026-08-15T17:46:03.163985Z","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":"2026-08-15T17:46:03.168874Z","title":"A general theoretical paradigm to understand learning from human preferences","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.168874Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:7e941330b9c561d428cb8024d55497e29b77855f352108f292de598f4acdf8bb","observation_id":"701880af-48dd-43b3-bfb7-a26cbacfb3f2","resolution":{"observed_at":"2026-08-15T17:46:03.168874Z","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":"2026-08-15T17:46:03.970478Z","title":"Learning multi-granularity and adaptive representation for knowledge graph reasoning","venue":null,"work_id":"4df30f5b-a219-45a3-ae48-2c16298d6522","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.173831Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:bf9f0d2a029735e4d97b1f8c1516167b42da3b41576c73e2294edb3a6dc9d297","observation_id":"51240e16-7c0d-4456-b31e-becdc7c2b5e0","resolution":{"observed_at":"2026-08-15T17:46:03.975807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.953212Z","title":"A comprehensive survey of forgetting in deep learning beyond continual learning, 2023","venue":null,"work_id":"024f5813-c1b0-4460-a44a-8615f7229ab5","year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.178963Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:b905041af2f833fbdb01f04c57a018af2e80bca018754b41c46254fb1938f280","observation_id":"2369fe6c-32fc-4c80-9cee-852d656535aa","resolution":{"observed_at":"2026-08-15T17:46:03.958736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.937224Z","title":"Dualde: Dually distilling knowledge graph embedding for faster and cheaper reasoning","venue":null,"work_id":"3c855c78-f94c-40c3-98bd-9c5d03d72371","year":2022},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.183842Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:3cdb02b87531b346d050cd04e92130b8ad05246202e2cc5ff890e448b8f37595","observation_id":"08a2ac38-92e8-4d52-a9c4-2a8a860b4589","resolution":{"observed_at":"2026-08-15T17:46:03.942204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.920447Z","title":"Towards continual knowledge graph embedding via incremental distillation","venue":null,"work_id":"7cb24034-92f9-4cda-865c-0afc86230c32","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.188505Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:7063ac64077362e119b4f160044dc7fe4a7db2e9f9332396deb4b80860e30a6f","observation_id":"ec9e8fd7-c932-403e-b143-3b788a1ad23f","resolution":{"observed_at":"2026-08-15T17:46:03.925710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:46:03.193104Z","title":"Knowledge graph embedding by translating on hyperplanes","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.193104Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:c2858b7727ba6ac339fa6d5128005e804c7d32d1afb68ea0edaad68ec7e2c378","observation_id":"f8950011-c913-44ab-ae28-e52da5f63e32","resolution":{"observed_at":"2026-08-15T17:46:03.193104Z","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":"2026-08-15T17:46:03.893816Z","title":"Simple embedding for link prediction in knowledge graphs","venue":null,"work_id":"196a1e7b-c638-436f-9032-f3f65be4ca00","year":2018},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.197913Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:577c713c02eea40257b53048c5e8952c5c2db79914d8bca8f6a4774cd20ce9e6","observation_id":"616a7fa0-8cb0-41e3-a4b1-f5ccc03f9582","resolution":{"observed_at":"2026-08-15T17:46:03.899246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.877788Z","title":"Boundary unlearning: Rapid forgetting of deep networks via shifting the decision boundary","venue":null,"work_id":"8fe849fb-3a5a-4c9b-82e4-af4508149f00","year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.204057Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:315cdfba8d1b6b3d359c476dc26e2ffb90742942d3865b8a63b1cc13be347850","observation_id":"083b9dbf-27e6-43a8-8dc8-7cacb673c2ef","resolution":{"observed_at":"2026-08-15T17:46:03.882922Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10683","last_updated":"2024-02-16T19:47:36Z","snapshot_observed_at":"2026-08-18T12:31:49.489444Z","submitted_at":"2023-10-14T00:32:55Z","title":"Large Language Model Unlearning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10683","snapshot_observed_at":"2026-08-15T17:46:03.209091Z","title":"Large language model unlearning.arXiv preprint arXiv:2310.10683, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.209091Z"},"links":{"cited_paper":"/paper/2310.10683","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:76615d26eadf1091fa63767074aab168c5ea18d870d7713d248ac2b2e60abe26","observation_id":"670c206d-e773-49f6-b771-b0dbf3c2727f","resolution":{"observed_at":"2026-08-15T17:46:03.209091Z","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":"2026-08-15T17:46:03.214501Z","title":"Visualizing data using t-sne","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.214501Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:5380524fbd680bdf93543ce6979d351c7691c47c3c9796f4d6b454374b54fb41","observation_id":"1c075a57-cf9e-4014-af65-06652f5beedc","resolution":{"observed_at":"2026-08-15T17:46:03.214501Z","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":"2026-08-15T17:46:03.851592Z","title":"Learning entity and relation embeddings for knowledge graph completion","venue":null,"work_id":"1646f2ca-ce6a-4a08-86f7-491d82ad3920","year":2015},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.220300Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:9305e3550a81b5f39c41f29d34b91a96684deb434a3de89dd5649a97e700e2ca","observation_id":"388cabb4-5737-4d8d-a4b4-4821988b3557","resolution":{"observed_at":"2026-08-15T17:46:03.856789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.836373Z","title":"Mulde: Multi-teacher knowledge distillation for low-dimensional knowledge graph embeddings","venue":null,"work_id":"e2db195a-aea0-418f-8b9e-722f3cd70bd0","year":2021},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.225024Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:05b9f6bd414e58bef15a5f8938aee3a9f17b9205aabc53e0b2922e371d738610","observation_id":"060056b6-963c-4e65-8778-2840ac6d47f3","resolution":{"observed_at":"2026-08-15T17:46:03.841303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.819879Z","title":"Iterde: an iterative knowledge distillation framework for knowledge graph embeddings","venue":null,"work_id":"a5cd18cc-c9b0-42be-a098-0f7c68b0e34b","year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.229841Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:70b63f592d48369fbe3df3f3c611db8413a770727051d7d66337f7ddd36270b5","observation_id":"45d9e39e-37db-44d0-8134-d888843647cd","resolution":{"observed_at":"2026-08-15T17:46:03.825156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.802760Z","title":"Entity-agnostic representation learning for parameter-efficient knowledge graph embedding","venue":null,"work_id":"87beacd4-d196-4aec-b8a7-6c79581c1ec8","year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.234685Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:5313218deeeb833786f90d17766d448dc1a214687c6266fe1c85f2fa69a012f3","observation_id":"baec2328-d46c-4de5-99b2-bb98e5f8c48e","resolution":{"observed_at":"2026-08-15T17:46:03.807781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T17:46:03.239350Z","title":"Continual learning of knowledge graph embeddings","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.239350Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:f87107162451008b422cbf1da0f9f3235ec7f3270bdd89d906169f06430cedc2","observation_id":"87db6853-e18c-4027-8dfb-4ad517430ec0","resolution":{"observed_at":"2026-08-15T17:46:03.239350Z","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":"2026-08-15T17:46:03.773875Z","title":"Lifelong embedding learning and transfer for growing knowledge graphs","venue":null,"work_id":"0b881532-6f3e-45fa-b370-77f923feb93e","year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.243831Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:274ce212ffe3136951d8366edb9542077e3563eaac3fa26f729233ba915a265a","observation_id":"6c4fa322-ef9a-4bea-86fb-999cd04c2c73","resolution":{"observed_at":"2026-08-15T17:46:03.779882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16173","last_updated":"2024-06-08T06:50:47Z","snapshot_observed_at":"2026-08-18T18:34:20.862529Z","submitted_at":"2023-09-28T05:09:14Z","title":"Distill to Delete: Unlearning in Graph Networks with Knowledge Distillation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16173","snapshot_observed_at":"2026-08-15T17:46:03.248707Z","title":"Distill to delete: unlearning in graph networks with knowledge distillation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.248707Z"},"links":{"cited_paper":"/paper/2309.16173","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:dab47a38c1e767dc610c07e10cd71bf645b65b1191ba2d865543c77fea630a03","observation_id":"ffdfeb4a-984c-4582-b499-6be11c03bd53","resolution":{"observed_at":"2026-08-15T17:46:03.248707Z","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":"2026-08-15T17:46:03.756734Z","title":"Unlearning graph classifiers with limited data resources","venue":null,"work_id":"c0fb3b70-66bf-45fd-af43-e91e941c618d","year":2023},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.253718Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:0e398633f33cd583439973bfce0d4d0fc6e8b8dff85befac1121af92bc7bb453","observation_id":"0b3d9f32-205e-47a3-88e6-d2663d4477d9","resolution":{"observed_at":"2026-08-15T17:46:03.761866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.739196Z","title":"Graph unlearning with efficient partial retraining","venue":null,"work_id":"03ec622a-d77f-43e5-b6fc-726866206c1c","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.258726Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:c5f5101525d368b943097b5ff784a0ce7041bdbfe0c37b55c343f565698c5064","observation_id":"070856c4-6af5-417b-8712-2b9ad8851a4c","resolution":{"observed_at":"2026-08-15T17:46:03.744402Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.723053Z","title":"Distill to delete: Unlearning in graph networks with knowledge distillation, 2024","venue":null,"work_id":"53a0c93b-8df8-4fc3-ad2f-1401603853f3","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.263293Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:0258ca6f75ec2c11f0b28119ef1e66714dbfc2e73b70186f84882996f361f69e","observation_id":"b3d3c2f2-cbfc-4a98-baf0-0783535cf940","resolution":{"observed_at":"2026-08-15T17:46:03.728266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.18629","last_updated":"2024-06-26T17:43:06Z","snapshot_observed_at":"2026-08-06T00:24:52.274888Z","submitted_at":"2024-06-26T17:43:06Z","title":"Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.18629","snapshot_observed_at":"2026-08-15T17:46:03.267995Z","title":"Step- dpo: Step-wise preference optimization for long-chain reasoning of llms","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.267995Z"},"links":{"cited_paper":"/paper/2406.18629","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:633fa30e77308e87513ba5dbd906b8ac2df4003f85e406fed360d8a4934cef9d","observation_id":"17cbbd3f-3e34-4169-a709-8d750ec9ca1e","resolution":{"observed_at":"2026-08-15T17:46:03.267995Z","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":"2026-08-15T17:46:03.707174Z","title":"Token- level direct preference optimization","venue":null,"work_id":"5ca4e991-9fcc-40c3-925e-23fca4e02496","year":2024},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.273492Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:1d1042549224f345ef6d614710f02840c70385762df519e28a69fad36301c054","observation_id":"0a33df94-ac2c-4228-b521-3ee487be3b10","resolution":{"observed_at":"2026-08-15T17:46:03.712162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.02846","last_updated":"2025-03-04T18:20:24Z","snapshot_observed_at":"2026-08-16T12:53:07.170236Z","submitted_at":"2025-03-04T18:20:24Z","title":"Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.02846","snapshot_observed_at":"2026-08-15T17:46:03.278320Z","title":"Mask-dpo: Generalizable fine-grained factuality alignment of llms","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.278320Z"},"links":{"cited_paper":"/paper/2503.02846","citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:2bf59663dd9e8ec5bd48a5ebe089a0c521e4aed0ebe1b5529c2aca5a1302799e","observation_id":"fa29b757-b097-48e4-b372-2411cf347e4f","resolution":{"observed_at":"2026-08-15T17:46:03.278320Z","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":"2026-08-15T17:46:03.691144Z","title":"Pytorch: An imperative style, high-performance deep learning library","venue":null,"work_id":"1648ca36-ac7d-4634-aa56-fb4870b5aa07","year":2019},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.283342Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:43260d74517e8319086692553a62eb75bb29bf076eefc58e408716de265c7eb4","observation_id":"b20ece33-1060-44c1-82ad-60e45d15b2c4","resolution":{"observed_at":"2026-08-15T17:46:03.696469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-15T17:46:03.674794Z","title":null,"venue":null,"work_id":"37c599c1-6453-4877-84c4-4339adfaae90","year":null},"citing_paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-15T17:46:03.288427Z"},"links":{"citing_paper":"/paper/2507.20566"},"observation_digest":"sha256:5c02fcc380ada4818f64a7b6ec1984bef3f0c4c93e332c15d0d6889cc19ad50a","observation_id":"1c31a404-e54a-44c3-a667-9515b28933f8","resolution":{"observed_at":"2026-08-15T17:46:03.680338Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.20566","last_updated":"2025-07-28T07:03:04Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-17T20:50:06.404331Z","submitted_at":"2025-07-28T07:03:04Z","title":"Unlearning of Knowledge Graph Embedding via Preference Optimization"},"reference_resolution":{"displayed":58,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":1,"verified_fuzzy":36},"total_outbound_references":58},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2507.20566."}