{"as_of":"2026-08-14T16:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4ddbe0acb1b1655c09dbb42d91458b8972be8f1757d93edc5069a5c99c1171dc","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":14,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T17:25:31.472001Z","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":"2026-07-04T17:30:00.128559Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-11T17:25:31.472001Z","title":"Large language model (LLM)-enabled in-context learning for wireless network optimization: A case study of power control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.09041","last_updated":"2025-06-20T10:28:15Z","snapshot_observed_at":"2026-08-12T20:39:15.426812Z","submitted_at":"2024-12-12T08:07:26Z","title":"Towards Wireless Native Big AI Model: The Mission and Approach Differ From Large Language Model","version":3},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-11T17:25:31.472001Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2412.09041"},"observation_digest":"sha256:3d9d375568cfce580fda3583033462daad616b3b0dd94bbc76d39dd27ca0d7da","observation_id":"b55f9d2c-3dd7-496b-b521-e9eeb8f1a4ff","resolution":{"observed_at":"2026-08-11T17:25:31.472001Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-11T14:15:31.978340Z","title":"Large language model (llm)-enabled in-context learning for wireless network optimization: A case study of power control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19823","last_updated":"2024-12-16T20:01:36Z","snapshot_observed_at":"2026-08-11T14:09:47.493311Z","submitted_at":"2024-12-16T20:01:36Z","title":"A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions","version":1},"reference_index":150,"source":"pdf_text","source_observed_at":"2026-08-11T14:15:31.978340Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2412.19823"},"observation_digest":"sha256:89ea2fd49b3d9095dae5dafed936245d888baca7bea645955cc7764346954837","observation_id":"556ad245-7c71-477d-b078-549ff7f9503a","resolution":{"observed_at":"2026-08-11T14:15:31.978340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-10T23:44:56.292397Z","title":"Large language model-enabled in-context learning for wireless net- work optimization: A case study of power control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19996","last_updated":"2024-12-28T03:42:05Z","snapshot_observed_at":"2026-08-10T23:38:44.189564Z","submitted_at":"2024-12-28T03:42:05Z","title":"Embodied AI-empowered Low Altitude Economy: Integrated Sensing, Communications, Computation, and Control (ISC3)","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T23:44:56.292397Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2412.19996"},"observation_digest":"sha256:808655d45bea7f4a77af262a3aa38ac3ffccbb0f8c4d3e0c6a9e6fbc6b636dd8","observation_id":"16374c30-7c65-42a2-b293-4253dcd8d5b8","resolution":{"observed_at":"2026-08-10T23:44:56.292397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-07T15:29:46.612991Z","title":"Large language model (llm)-enabled in-context learning for wireless network optimization: A case study of power control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14906","last_updated":"2025-05-20T21:00:08Z","snapshot_observed_at":"2026-08-13T06:37:18.369524Z","submitted_at":"2025-05-20T21:00:08Z","title":"Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:29:46.612991Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2505.14906"},"observation_digest":"sha256:1bc1954393648883abc346ddcb6fcbf920b8dd287670c4231975067b44106008","observation_id":"40adf2d7-2ad4-402d-88e1-6de17877f60f","resolution":{"observed_at":"2026-08-07T15:29:46.612991Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-07T10:43:37.484882Z","title":"Large language model (LLM)-enabled in-context learning for wireless network optimization: A case study of power control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.04594","last_updated":"2025-06-05T03:19:57Z","snapshot_observed_at":"2026-08-13T10:39:25.002280Z","submitted_at":"2025-06-05T03:19:57Z","title":"Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T10:43:37.484882Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2506.04594"},"observation_digest":"sha256:39111fa57c8297dfa4c28f2f10f9851a5f48d7016abb234bc061c2327cec1b2a","observation_id":"1098ad89-1738-4e71-bcba-631009c460c7","resolution":{"observed_at":"2026-08-07T10:43:37.484882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-07T05:59:21.160295Z","title":"Large language model (llm)-enabled in-context learning for wireless network optimization: A case study of power control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06519","last_updated":"2025-06-06T20:33:29Z","snapshot_observed_at":"2026-08-13T14:56:58.914372Z","submitted_at":"2025-06-06T20:33:29Z","title":"Hierarchical Debate-Based Large Language Model (LLM) for Complex Task Planning of 6G Network Management","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T05:59:21.160295Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2506.06519"},"observation_digest":"sha256:0575ed585524ad0d4b25beb7134a5b13a9a0157f3b6aa59ad868658c192b6bc2","observation_id":"f503e695-48a6-4b31-aa49-cb0846fc3530","resolution":{"observed_at":"2026-08-07T05:59:21.160295Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-07T05:57:45.797496Z","title":"Large language model (llm)-enabled in-context learning for wireless network optimization: A case study of power control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06532","last_updated":"2025-06-06T20:59:52Z","snapshot_observed_at":"2026-08-12T21:44:37.497137Z","submitted_at":"2025-06-06T20:59:52Z","title":"Hierarchical and Collaborative LLM-Based Control for Multi-UAV Motion and Communication in Integrated Terrestrial and Non-Terrestrial Networks","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T05:57:45.797496Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2506.06532"},"observation_digest":"sha256:db93c7ef781816ee8b774267c4c47bf825e94a4697934895d8bdfe7868f9d714","observation_id":"166a5ffc-b121-4f23-b5fa-2831aab06aab","resolution":{"observed_at":"2026-08-07T05:57:45.797496Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-07T05:33:54.967574Z","title":"Large Language Model (LLM)-Enabled In- Context Learning for Wireless Network Optimization: A Case Study of Power Control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07647","last_updated":"2025-06-09T11:12:02Z","snapshot_observed_at":"2026-08-14T08:58:39.832217Z","submitted_at":"2025-06-09T11:12:02Z","title":"Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T05:33:54.967574Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2506.07647"},"observation_digest":"sha256:71f7dc49ae217e5afc099e8fe639300be47c5b715b604d142eba8439bfcb8221","observation_id":"a1cc5ea0-c104-4ff4-9977-01e3d78af907","resolution":{"observed_at":"2026-08-07T05:33:54.967574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-04T20:55:41.961677Z","title":"Large language model (llm)-enabled in-context learning for wireless network optimization: A case study of power control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08269","last_updated":"2026-07-17T08:53:46Z","snapshot_observed_at":"2026-08-08T15:31:01.848037Z","submitted_at":"2025-09-10T04:05:54Z","title":"A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving","version":6},"reference_index":227,"source":"pdf_text","source_observed_at":"2026-08-04T20:55:41.961677Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2509.08269"},"observation_digest":"sha256:572498e26624a3149cfccac43e8fac2ff27dfd86de7aaa27a40ac0be257eeba4","observation_id":"8cfc1850-8abb-4aef-a04a-9638105ae615","resolution":{"observed_at":"2026-08-04T20:55:41.961677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-04T16:33:30.246479Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.12795","last_updated":"2026-06-01T08:46:33Z","snapshot_observed_at":"2026-08-13T00:13:00.487752Z","submitted_at":"2025-09-16T08:14:15Z","title":"When Large Language Models Meet UAV Projects: An Empirical Study from Developers' Perspective","version":3},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-04T16:33:30.246479Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2509.12795"},"observation_digest":"sha256:a4bce3d82bf6657fe73cba0ff148f39cca66204d18bb33b5258339b8d198c86e","observation_id":"3013f5d1-f4f0-4cfa-988a-3772fe79410e","resolution":{"observed_at":"2026-08-04T16:33:30.246479Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-04T11:20:12.346207Z","title":"Large language model (llm)-enabled in-context learning for wireless network optimization: A case study of power control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-12T18:53:38.802785Z","submitted_at":"2025-10-07T09:04:56Z","title":"AIC-VDS: Attention-Based In-Context Learning for Joint Velocity Control and Data Collection Scheduling in Multi-UAV-Assisted Pipeline Monitoring","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.346207Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:7a0e6768f59d9228cd02cf2c2ca8f1d1061dbcf97bb2e45459cfaa9f4dfb78c9","observation_id":"3e76d248-d16c-4d5a-add0-8e9e7b8b4c15","resolution":{"observed_at":"2026-08-04T11:20:12.346207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":"2408.00214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-07-04T17:30:00.128559Z","title":"Large language model (LLM)-enabled in-context learning for wireless network optimization: A case study of power control","venue":null,"work_id":"8f97bc07-8e35-46b2-8dac-3ec134681381","year":2024},"citing_paper":{"arxiv_id":"2605.04436","last_updated":"2026-05-06T02:59:18Z","snapshot_observed_at":"2026-08-03T07:57:06.274322Z","submitted_at":"2026-05-06T02:59:18Z","title":"Joint Optimization of Trajectory Control, Resource Allocation, and Task Offloading for Multi-UAV-Assisted IoV","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-08T17:26:13.034726Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2605.04436"},"observation_digest":"sha256:96d4341257f8a043567c2b950e6f818b57f7cfa4208aedcbff5484d93f9be2b4","observation_id":"c5aa311b-2e77-4694-9ef5-6ee9db09cdd1","resolution":{"observed_at":"2026-05-11T17:36:05.289956Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":"2408.00214","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-07-04T17:30:00.128559Z","title":"Large language model (LLM)-enabled in-context learning for wireless network optimization: A case study of power control","venue":null,"work_id":"8f97bc07-8e35-46b2-8dac-3ec134681381","year":2024},"citing_paper":{"arxiv_id":"2606.24416","last_updated":"2026-07-24T13:19:58Z","snapshot_observed_at":"2026-08-13T23:50:32.067998Z","submitted_at":"2026-06-23T10:53:12Z","title":"Agentic AI for Bilevel Long-Term Optimization of Policy-Driven Physical Layer Systems","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-25T23:41:53.531425Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2606.24416"},"observation_digest":"sha256:9f0c892ee6b51f949f4c95a561fbec2e7b53cbf7b29d21d7672eb9021fa132c8","observation_id":"0851e050-6ac6-4883-ab6a-1d87845ebfc6","resolution":{"observed_at":"2026-07-04T17:30:00.130231Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00214","snapshot_observed_at":"2026-08-02T10:24:52.740347Z","title":"Large language model (LLM)-enabled in-context learning for wireless network optimization: A case study of power control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.24416","last_updated":"2026-07-24T13:19:58Z","snapshot_observed_at":"2026-08-13T23:50:32.067998Z","submitted_at":"2026-06-23T10:53:12Z","title":"Agentic AI for Bilevel Long-Term Optimization of Policy-Driven Physical Layer Systems","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T10:24:52.740347Z"},"links":{"cited_paper":"/paper/2408.00214","citing_paper":"/paper/2606.24416"},"observation_digest":"sha256:775b66cdc245d6fbc3cc81d83d0fd972c980cdf20f531991e7ca3132dddb4e89","observation_id":"bc5d5e6e-f92e-4638-bab5-615c63cfe051","resolution":{"observed_at":"2026-08-02T10:24:52.740347Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2408.00214/citation-record","integrity":"/paper/2408.00214/integrity","json":"/paper/2408.00214/citation-record.json","paper":"/paper/2408.00214"},"outbound":[],"paper":{"arxiv_id":"2408.00214","last_updated":"2025-06-16T01:41:18Z","latest_version":2,"primary_category":"eess.SY","snapshot_observed_at":"2026-08-14T15:55:45.235583Z","submitted_at":"2024-08-01T00:53:02Z","title":"Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2408.00214."}