{"as_of":"2026-08-20T04:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5a641a95517ad235334cb3fd6a895ac5a07102f8e193d60ae94c4a3730e854aa","coverage":[{"denominator":11,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T21:22:49.700021Z","state":"measured"},{"denominator":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2505.10003/citation-record","integrity":"/paper/2505.10003/integrity","json":"/paper/2505.10003/citation-record.json","paper":"/paper/2505.10003"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T21:22:49.916963Z","title":"Big AI models for 6G wireless networks: Opportunities, challenges, and research directions,","venue":null,"work_id":"950b1a41-82c3-4fdf-bed6-5545335e4f32","year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.642833Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:7e5163e3eb94892a8a54331b21905b17be54629a2b61dfc78b08872e4bf34ce0","observation_id":"e594b9ce-04b0-4e7d-949e-1fbf3d6c766d","resolution":{"observed_at":"2026-08-15T21:22:49.922595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T21:22:49.900756Z","title":"Large generative AI models for telecom: The next big thing?,","venue":null,"work_id":"2ed245fe-2fc5-4651-961d-6f9882d80aab","year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.649121Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:b70e792373397bb597d843496fd1ea19808c406a501d55985e1bddd256abb2db","observation_id":"a04c128c-c413-4d8f-b664-08b375b5d99c","resolution":{"observed_at":"2026-08-15T21:22:49.905766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T21:22:49.882350Z","title":"Large multi-modal models (LMMs) as universal foundation models for AI-native wireless systems,","venue":null,"work_id":"424664a9-6d8f-49b2-baa1-c7fd93995f6d","year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.654758Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:78515ed92bdca80059404bea0701333c4507ec888181cb5440cb80b93d219e20","observation_id":"7f74ea11-1f9f-444d-bd84-4d28ae85393f","resolution":{"observed_at":"2026-08-15T21:22:49.888797Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T21:22:49.862672Z","title":"MAPLM: A real-world large-scale vision-language bench- mark for map and traffic scene understanding,","venue":null,"work_id":"d382241e-f917-40ae-b2be-1886d2eb0243","year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.660298Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:0cb92cdcb70a6b0c7e556a1963b50901d6eb6b8680593fb2328e666bc70aa1f0","observation_id":"43308b90-ed6c-41d8-8cee-1fe914535405","resolution":{"observed_at":"2026-08-15T21:22:49.867995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12821","last_updated":"2025-02-09T08:17:34Z","snapshot_observed_at":"2026-08-16T13:50:57.036405Z","submitted_at":"2024-05-21T14:26:36Z","title":"Talk2Radar: Bridging Natural Language with 4D mmWave Radar for 3D Referring Expression Comprehension","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12821","snapshot_observed_at":"2026-08-15T21:22:49.666020Z","title":"Talk2Radar: Bridging natural language with 4D mmWave radar for 3D referring expression comprehension,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.666020Z"},"links":{"cited_paper":"/paper/2405.12821","citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:d35c616d511531ff6016efa3147f55b7304ee3edb8976f705eca9b28d6e0d165","observation_id":"bcb319a3-e3dc-43f2-b8cf-3cfa75118db0","resolution":{"observed_at":"2026-08-15T21:22:49.666020Z","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":"2026-08-15T21:22:49.845813Z","title":"NetLLM: Adapting large language models for networking,","venue":null,"work_id":"acea404b-01c8-4b38-b87c-8ad376b8e572","year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.672790Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:84713994b534f5372bb73396591d4b505b82c5749fe6a7f97fca1835021cb5be","observation_id":"d00750c3-9df4-46bf-adca-f91d072e7e5a","resolution":{"observed_at":"2026-08-15T21:22:49.851014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T21:22:49.828683Z","title":"6G-oriented CSI-based multi-modal pre-training and down- stream task adaptation paradigm,","venue":null,"work_id":"a6984d83-a416-467f-827e-c13f7ac3ea2f","year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.678995Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:54f29274b073ece5b5e521fe7c867695c120b0f6369194db78a9893a35b6ab80","observation_id":"52b7a99d-3271-44f1-b3d3-d8ca8ead5411","resolution":{"observed_at":"2026-08-15T21:22:49.833832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T21:22:49.812113Z","title":"Addressing the curse of scenario and task generalization in AI-6G: A multi-modal paradigm,","venue":null,"work_id":"e532dee7-5c7e-428e-8dfd-ebdf7e0496d5","year":2025},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.684136Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:ca9641f94a683f578729bef21938ee2085ae52e945656e75d61d3c19792423cd","observation_id":"cc7348db-5208-4efa-a4d2-20e8ef05f03f","resolution":{"observed_at":"2026-08-15T21:22:49.817373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.02159","last_updated":"2022-12-05T10:59:05Z","snapshot_observed_at":"2026-08-20T00:46:26.994628Z","submitted_at":"2022-12-05T10:59:05Z","title":"WAIR-D: Wireless AI Research Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.02159","snapshot_observed_at":"2026-08-15T21:22:49.689392Z","title":"W AIR-D: Wireless AI research dataset,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.689392Z"},"links":{"cited_paper":"/paper/2212.02159","citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:14527a5e35d0ad6c51fc187afa9abca38fdb307bbd6cdf12b5fefbae36094ae2","observation_id":"56af6f6d-4abc-4ffb-a2ce-1b0a6ac127b5","resolution":{"observed_at":"2026-08-15T21:22:49.689392Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.06435","last_updated":"2019-02-18T07:44:08Z","snapshot_observed_at":"2026-08-14T17:15:06.275058Z","submitted_at":"2019-02-18T07:44:08Z","title":"DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.06435","snapshot_observed_at":"2026-08-15T21:22:49.694467Z","title":"DeepMIMO: A generic deep learning dataset for mil- limeter wave and massive MIMO applications,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.694467Z"},"links":{"cited_paper":"/paper/1902.06435","citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:0b650afadbf9d543e0dc95ae4b6862d84c6490eb05c814478fce91b0eb70303c","observation_id":"82f08911-1663-4bf3-bd84-f60dea0dae1f","resolution":{"observed_at":"2026-08-15T21:22:49.694467Z","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":"2026-08-15T21:22:49.793928Z","title":"LLM agents as 6G orchestrator: A paradigm for task- oriented physical-layer automation,","venue":null,"work_id":"c84148ad-c790-4e0f-8f58-5e55e47c7924","year":2024},"citing_paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T21:22:49.700021Z"},"links":{"citing_paper":"/paper/2505.10003"},"observation_digest":"sha256:2dff3e7cc415276fa5dc92c35a072529424c73d985d80bc51230ad2ab69a3751","observation_id":"ffef116b-db39-49a3-a29c-60f7be234be9","resolution":{"observed_at":"2026-08-15T21:22:49.800785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.10003","last_updated":"2025-05-15T06:32:59Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T21:16:58.156964Z","submitted_at":"2025-05-15T06:32:59Z","title":"AI2MMUM: AI-AI Oriented Multi-Modal Universal Model Leveraging Telecom Domain Large Model"},"reference_resolution":{"displayed":11,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":8},"total_outbound_references":11},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2505.10003."}