{"as_of":"2026-08-12T20:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:aa41f9643e60befda745d6c9de51a9bafc9e84bbd573f4d8c01613ec75222027","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T16:23:57.260385Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T01:56:01.451833Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T10:46:32.446279Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"cited_work":{"arxiv_id":"2412.10107","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.10107","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"NetOrchLLM: Mastering wireless network orchestration with large language models","venue":null,"work_id":"81ed06e0-a57c-422a-8d5c-97cf63b0cdd2","year":2024},"citing_paper":{"arxiv_id":"2605.03215","last_updated":"2026-05-04T23:10:34Z","snapshot_observed_at":"2026-08-11T16:08:59.624374Z","submitted_at":"2026-05-04T23:10:34Z","title":"Enwar 3.0: An Agentic Multi-Modal LLM Orchestrator for Situation-Aware Beamforming, Blockage Prediction, and Handover Management","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T01:56:01.451833Z"},"links":{"cited_paper":"/paper/2412.10107","citing_paper":"/paper/2605.03215"},"observation_digest":"sha256:541b1e8298e540e34257771dbc46a0df63d1dc6d8cecfb06a7c023e9e0574195","observation_id":"7d7b3484-8ef0-4900-96e7-96c78f5024b1","resolution":{"observed_at":"2026-05-12T10:46:32.451643Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.10107/citation-record","integrity":"/paper/2412.10107/integrity","json":"/paper/2412.10107/citation-record.json","paper":"/paper/2412.10107"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:23:57.435974Z","title":"Leveraging large language models for intelligent control of 6G integrated TN-NTN with iot service,","venue":null,"work_id":"242f1fc1-d81d-4c3a-bfd4-de86ba5b4f2d","year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.205746Z"},"links":{"citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:cceb0234a97579d1a293ac45f257894336398af2c25bb67075ca96ec8abd4485","observation_id":"9b9fcd3e-6518-4978-809e-5095291030bd","resolution":{"observed_at":"2026-08-11T16:23:57.439967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:23:57.424389Z","title":"At the dawn of generative ai era: A tutorial- cum-survey on new frontiers in 6g wireless intelligence,","venue":null,"work_id":"d915edc8-0006-43dd-8167-1e7e79aaf632","year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.210454Z"},"links":{"citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:62f2b94b40d81f0485617f6e2f66b6ffecc50880cd6efbee1fb3db80ac2250cc","observation_id":"28a6d54d-e999-45b0-9ef5-dd9153336f4a","resolution":{"observed_at":"2026-08-11T16:23:57.428701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02757","last_updated":"2023-07-06T03:41:15Z","snapshot_observed_at":"2026-08-10T03:18:53.492591Z","submitted_at":"2023-07-06T03:41:15Z","title":"Wireless Multi-Agent Generative AI: From Connected Intelligence to Collective Intelligence","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02757","snapshot_observed_at":"2026-08-11T16:23:57.214264Z","title":"Wireless multi-agent generative ai: From connected intelligence to collective intelligence,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.214264Z"},"links":{"cited_paper":"/paper/2307.02757","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:e8e03e8ae048f74681bd3333e3e55c18649b1018ab9e3307a972677cde5518b6","observation_id":"7a6edaa4-9e06-4255-a0c8-d778fe56f4ba","resolution":{"observed_at":"2026-08-11T16:23:57.214264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01748","last_updated":"2024-02-07T17:55:11Z","snapshot_observed_at":"2026-08-11T19:22:27.267163Z","submitted_at":"2024-01-30T00:21:41Z","title":"Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01748","snapshot_observed_at":"2026-08-11T16:23:57.218728Z","title":"Large multi-modal models (LMMs) as universal foundation models for AI-native wireless systems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.218728Z"},"links":{"cited_paper":"/paper/2402.01748","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:924794b996848ea18fc0ba381250e26fa2b716379acbdaf39fba7f256257d8f4","observation_id":"0b685523-35ef-43e1-96c5-dd958452c8c9","resolution":{"observed_at":"2026-08-11T16:23:57.218728Z","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":"2026-08-11T16:23:57.413751Z","title":"Large language models empowered autonomous edge AI for connected intelligence,","venue":null,"work_id":"f6b251b4-9b1c-4066-b0ff-b557b6e5e4fe","year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.222715Z"},"links":{"citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:98111b99c1b32d0bd96e76d9c750028134e4861d9875a64b7ccee84c464f07e2","observation_id":"c3d901a1-d74b-43f9-9379-17c54a4b0816","resolution":{"observed_at":"2026-08-11T16:23:57.417390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:23:57.402744Z","title":"Large generative ai models for telecom: The next big thing?","venue":null,"work_id":"7f7b297a-3391-4ea7-8056-fffb139ec3f5","year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.226809Z"},"links":{"citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:c8f44ac8375521c63f1c16774d323ef9434409dd0cba1ae283f051ca9d7e5f89","observation_id":"07ac89ae-e008-48f6-ad7a-5bb352a10a7b","resolution":{"observed_at":"2026-08-11T16:23:57.406526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T16:23:57.230434Z","title":"Large language model enhanced multi-agent systems for 6g communications,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.230434Z"},"links":{"citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:b76b6ba137ffb50142611bcae771b94390ab9aeebf8bb4eb2284f6c15f2088da","observation_id":"177fe275-001c-4b33-b18e-134d8dd48840","resolution":{"observed_at":"2026-08-11T16:23:57.230434Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.17053","last_updated":"2024-06-15T07:01:54Z","snapshot_observed_at":"2026-07-06T18:20:27.214667Z","submitted_at":"2024-05-27T11:18:25Z","title":"WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.17053","snapshot_observed_at":"2026-08-11T16:23:57.233876Z","title":"WirelessLLM: Empowering large language models towards wireless intelligence,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.233876Z"},"links":{"cited_paper":"/paper/2405.17053","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:31defb75a73017b33e0794fe4b8db7c1f09f97a28f3783220a2b01ce391a7318","observation_id":"750111b0-15ac-4606-a4de-c49518dff2b7","resolution":{"observed_at":"2026-08-11T16:23:57.233876Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.05842","last_updated":"2023-11-10T02:59:16Z","snapshot_observed_at":"2026-08-07T06:39:44.750209Z","submitted_at":"2023-11-10T02:59:16Z","title":"AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.05842","snapshot_observed_at":"2026-08-11T16:23:57.237586Z","title":"AI-native interconnect framework for integration of large language model technologies in 6G systems,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.237586Z"},"links":{"cited_paper":"/paper/2311.05842","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:3896d7397afb81b785df5780cd6f507aa9c79def06c1ccf8fbb7458335cda137","observation_id":"d5f61671-4d6a-47c0-96d2-49639fb4de9f","resolution":{"observed_at":"2026-08-11T16:23:57.237586Z","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":"2026-08-11T16:23:57.385016Z","title":"When large language model agents meet 6G networks: Perception, grounding, and alignment,","venue":null,"work_id":"e62a7de9-f62a-414b-ae6c-3a53e1807376","year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.241485Z"},"links":{"citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:f44d519f366fd16390b23949f3ae1d8c59577289974ed54ec811614c6339e782","observation_id":"14876fa7-5a94-4a0d-a94d-c8ca0f1e6753","resolution":{"observed_at":"2026-08-11T16:23:57.388912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07053","last_updated":"2024-06-11T08:35:23Z","snapshot_observed_at":"2026-08-12T01:06:57.892194Z","submitted_at":"2024-06-11T08:35:23Z","title":"TelecomRAG: Taming Telecom Standards with Retrieval Augmented Generation and LLMs","version":1},"cited_work":{"arxiv_id":"2406.07053","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.07053","snapshot_observed_at":"2026-08-11T16:23:57.321895Z","title":"TelecomRAG: Taming Telecom Standards with Retrieval Augmented Generation and LLMs","venue":"cs.NI","work_id":"fe1aa22f-f8e6-4af2-a6ce-122243824d99","year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.244987Z"},"links":{"cited_paper":"/paper/2406.07053","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:9a1a18ada0bfe22e84d1becb0d2e5e7fc86dad4b21ac2d10a718c61c2118ff71","observation_id":"194d3b9f-7c66-436a-a944-5b46e66ada9b","resolution":{"observed_at":"2026-08-11T16:23:57.328371Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.15051","last_updated":"2023-10-23T15:55:15Z","snapshot_observed_at":"2026-08-10T21:34:04.507390Z","submitted_at":"2023-10-23T15:55:15Z","title":"TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.15051","snapshot_observed_at":"2026-08-11T16:23:57.248704Z","title":"TeleQnA: A benchmark dataset to assess large language models telecommunications knowledge,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.248704Z"},"links":{"cited_paper":"/paper/2310.15051","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:38205843ebd159818dd40e3629871dca344fd0990d3b45f0bd4f47cde03f6940","observation_id":"a9bb9c53-8f35-441f-8eaf-b4100da52f1b","resolution":{"observed_at":"2026-08-11T16:23:57.248704Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.09424","last_updated":"2024-07-12T16:51:02Z","snapshot_observed_at":"2026-08-10T07:54:07.506601Z","submitted_at":"2024-07-12T16:51:02Z","title":"TelecomGPT: A Framework to Build Telecom-Specfic Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.09424","snapshot_observed_at":"2026-08-11T16:23:57.252585Z","title":"TelecomGPT: A framework to build telecom-specfic large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.252585Z"},"links":{"cited_paper":"/paper/2407.09424","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:08fcd24b6e745d0b4e570ab96c37d983247ada005cbec40ceb5de2f513521eb4","observation_id":"2c9343b7-60fa-4b0d-888d-4215fd520031","resolution":{"observed_at":"2026-08-11T16:23:57.252585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18104","last_updated":"2024-10-08T16:26:18Z","snapshot_observed_at":"2026-08-11T03:49:42.348198Z","submitted_at":"2024-10-08T16:26:18Z","title":"ENWAR: A RAG-empowered Multi-Modal LLM Framework for Wireless Environment Perception","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18104","snapshot_observed_at":"2026-08-11T16:23:57.256635Z","title":"ENW AR: A RAG-empowered multi-modal LLM framework for wireless environment perception,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.256635Z"},"links":{"cited_paper":"/paper/2410.18104","citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:80e5648c531fdc8ec1f8593948ee0a41b4032db26ac08e20598422bd61bb8c5d","observation_id":"856471b7-bf0d-4fe8-8435-8faca56255a0","resolution":{"observed_at":"2026-08-11T16:23:57.256635Z","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":"2026-08-11T16:23:57.373981Z","title":"Deep learning power allocation in massive mimo,","venue":null,"work_id":"0b810c9f-d84d-4ccf-9638-eec125726fe2","year":2018},"citing_paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T16:23:57.260385Z"},"links":{"citing_paper":"/paper/2412.10107"},"observation_digest":"sha256:1c40239c0af0b3da590b527ed590ee13ca61498be36bd335ecf4e5f492701011","observation_id":"8d6ebc19-6f2a-49a6-8c0c-40afd049db46","resolution":{"observed_at":"2026-08-11T16:23:57.378155Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.10107","last_updated":"2024-12-13T12:48:15Z","latest_version":1,"primary_category":"cs.NI","snapshot_observed_at":"2026-08-12T10:35:50.759042Z","submitted_at":"2024-12-13T12:48:15Z","title":"NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":1,"verified_fuzzy":6},"total_outbound_references":15},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2412.10107."}