{"as_of":"2026-08-08T09:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:372b4557a9c53dafb85db6e32673037a01e75ad4b9f29b835ce1baa147b53dfe","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T11:20:14.730085Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2510.05698/citation-record","integrity":"/paper/2510.05698/integrity","json":"/paper/2510.05698/citation-record.json","paper":"/paper/2510.05698"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T11:20:11.534436Z","title":"Multi uav based traffic control in smart cities,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":1,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:11.534436Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:1fdab9b8c8c9de72231e8be25a23172e53da32afa77e0de796cfc61d2aa8052c","observation_id":"3d8c436c-3639-4213-b2e7-ea55b0124dc3","resolution":{"observed_at":"2026-08-04T11:20:11.534436Z","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":"2026-08-04T11:20:11.669726Z","title":"Unmanned aerial vehicles for package delivery and network coverage,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":2,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:11.669726Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:3197c6af63b9206dab24a3fce1ef6b201eb8e191254f30087158383ae818c8fd","observation_id":"bca18782-8289-4b3a-89f3-8336d726f513","resolution":{"observed_at":"2026-08-04T11:20:11.669726Z","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":"2026-08-04T11:20:11.900555Z","title":"Topographic data acquisition in tsunami-prone coastal area using unmanned aerial vehicle (uav),","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":4,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:11.900555Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:b01f85abdbc68821306f5af320eb55f79d102170c3989955aa22b2a09b8f651f","observation_id":"2d008ad2-1db3-4ba7-a440-339ca854523b","resolution":{"observed_at":"2026-08-04T11:20:11.900555Z","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":"2026-08-04T11:20:11.970753Z","title":"(2025) Tsunamis – health impacts and who response","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":5,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:11.970753Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:7fa734475958f3c6b031656bbd89771e2c62f86307c9b1c8d34ac607233d08be","observation_id":"bf52af8e-58ac-42eb-ae8a-cb0c87dfed11","resolution":{"observed_at":"2026-08-04T11:20:11.970753Z","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":"2026-08-04T11:20:12.106256Z","title":"Generalising rescue operations in disaster scenarios using drones: A lifelong reinforcement learning approach,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":6,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.106256Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:a658784eb1cc679939d4e495dfb0a1147ba343ac20296b5b22c5009db22c4456","observation_id":"e727cf84-f14c-448d-91ff-bab3f5bf20bd","resolution":{"observed_at":"2026-08-04T11:20:12.106256Z","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":"2026-08-04T11:20:12.146635Z","title":"Deep reinforcement learning: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":7,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.146635Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:7819479435a17d08fd7727f9cf95ca94a8cb59d579e8df074da98bebf679c40c","observation_id":"f242011f-9782-4dcc-bc5c-7e7195595a4d","resolution":{"observed_at":"2026-08-04T11:20:12.146635Z","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":"2026-08-04T11:20:12.206301Z","title":"Data-driven flight control of internet-of-drones for sensor data aggregation using multi-agent deep reinforcement learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":8,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.206301Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:4749f543f128e0c478a105ac146ba82a5e286f8a82805347885fdb428a38908b","observation_id":"420473ed-eda5-4054-b77e-be21e20e023b","resolution":{"observed_at":"2026-08-04T11:20:12.206301Z","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":"2026-08-04T11:20:12.278053Z","title":"A review on large language models: Architectures, applications, taxonomies, open issues and challenges,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":9,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.278053Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:2edbd4e14347dbe048cd731cdae9e7934e08eee932893532939ca7c6d36c6e0f","observation_id":"68298157-839f-4190-86f8-1d043a25fe56","resolution":{"observed_at":"2026-08-04T11:20:12.278053Z","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":"2026-07-06T18:55:19.894571Z","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":"2026-08-06T23:28:17.938338Z","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":"sha256:01a55b29980f8833b55848b2463dd7ec78bd5ecf8edaa907f7134e02afee065d","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":"2312.09953","last_updated":"2023-12-15T17:04:03Z","snapshot_observed_at":"2026-08-07T21:23:19.336129Z","submitted_at":"2023-12-15T17:04:03Z","title":"Deep Reinforcement Learning for Joint Cruise Control and Intelligent Data Acquisition in UAVs-Assisted Sensor Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.09953","snapshot_observed_at":"2026-08-04T11:20:12.420861Z","title":"Deep reinforcement learning for joint cruise control and in- telligent data acquisition in uavs-assisted sensor networks,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":11,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.420861Z"},"links":{"cited_paper":"/paper/2312.09953","citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:505d9495b6c741a4727f9af31efa387b06f9173b443b57274255f1276f572535","observation_id":"7924d6e3-2e49-4a26-86a6-243d0442b736","resolution":{"observed_at":"2026-08-04T11:20:12.420861Z","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":"2026-08-04T11:20:12.506744Z","title":"Online velocity control and data capture of drones for the internet of things: An onboard deep reinforcement learning approach,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":12,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.506744Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:b1b937349cdf8f72738535d88d6f9c47a14065b47cd7f85eb5855b3d8486cfbf","observation_id":"4d1b64e6-4ba9-4bf6-922d-effaad1c989f","resolution":{"observed_at":"2026-08-04T11:20:12.506744Z","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":"2026-08-04T11:20:12.618752Z","title":"The mystery of in- context learning: A comprehensive survey on interpretation and analysis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":13,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.618752Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:6f1f7f411c38e1a3e73cb1401f38d901b1284d54dc95dc2cb000b512ff3a9e16","observation_id":"bb04f6fe-468e-4313-b135-ec15410a75da","resolution":{"observed_at":"2026-08-04T11:20:12.618752Z","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":"2026-08-04T11:20:12.731696Z","title":"Llm-based edge intelligence: A comprehensive sur- vey on architectures, applications, security and trustworthiness,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":14,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.731696Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:fb3f6e14041d4555f9089023fdddea7e6a6bf4943e093d0d06fa83c53e2d7f8c","observation_id":"913f137b-fa64-4518-98ae-51a6719f9c73","resolution":{"observed_at":"2026-08-04T11:20:12.731696Z","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":"2026-08-04T11:20:12.873448Z","title":"Aero-llm: A distributed framework for secure uav communication and intelligent decision-making,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":15,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.873448Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:1f9753064fd852035ee1b1c16c35998f023513eecfcfee7eddf6777699874944","observation_id":"04d2846c-d011-434d-b2c3-db36abfd7c63","resolution":{"observed_at":"2026-08-04T11:20:12.873448Z","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":"2026-08-04T11:20:12.988070Z","title":"Llm-enabled in-context learning for data collection scheduling in uav-assisted sensor networks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":16,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:12.988070Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:cf19ad12191fc0fc8ebc7c1ef1076e24ec1d6bf95d05625c78c512a55fafb128","observation_id":"45d0cfc9-7743-4e64-b982-67941f7d520c","resolution":{"observed_at":"2026-08-04T11:20:12.988070Z","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":"2026-08-04T11:20:13.115477Z","title":"From prompts to protection: Large language model-enabled in-context learning for smart public safety uav,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":17,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.115477Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:aae63764e0e56d8c9d4889aea86aa1c3d794d0b43fe4d39c73c343323db48929","observation_id":"181f41e2-29bb-483e-bd66-70e84b86e156","resolution":{"observed_at":"2026-08-04T11:20:13.115477Z","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":"2026-08-04T11:20:13.228040Z","title":"Frsicl: Llm-enabled in-context learning flight resource allocation for fresh data collection in uav-assisted wildfire monitoring,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":18,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.228040Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:411a0e64de2fad39d56e71e273610ed5dbb17fd496415961fe3b6c826a44e1e9","observation_id":"a5eb51ab-f721-4443-a45a-88a76bfb495b","resolution":{"observed_at":"2026-08-04T11:20:13.228040Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04136","last_updated":"2024-12-27T20:02:48Z","snapshot_observed_at":"2026-07-06T19:46:19.931894Z","submitted_at":"2024-10-27T00:51:16Z","title":"Large Language Models for Wireless Networks: An Overview from the Prompt Engineering Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04136","snapshot_observed_at":"2026-08-04T11:20:13.374410Z","title":"Large language models (llms) for wireless networks: An overview from the prompt engineering perspective,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":19,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.374410Z"},"links":{"cited_paper":"/paper/2411.04136","citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:2273eced67a61e372553689cc8678d355b420fbe5f888f3bab757f3206b563f6","observation_id":"c81f254c-271e-4fa6-b5c2-4c5ec8e1909e","resolution":{"observed_at":"2026-08-04T11:20:13.374410Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.00234","last_updated":"2024-10-05T11:47:02Z","snapshot_observed_at":"2026-07-06T14:36:25.690733Z","submitted_at":"2022-12-31T15:57:09Z","title":"A Survey on In-context Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00234","snapshot_observed_at":"2026-08-04T11:20:13.514102Z","title":"A survey on in-context learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":20,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.514102Z"},"links":{"cited_paper":"/paper/2301.00234","citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:f842a9e18ea4487b0e2ba24cc3561d36291a5ab4d51177695154a8be1b6f7778","observation_id":"a7d499e4-6d97-4929-b0cd-102d085017cc","resolution":{"observed_at":"2026-08-04T11:20:13.514102Z","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":"2026-08-04T11:20:13.576955Z","title":"Large language models in wireless application design: In-context learning-enhanced au- tomatic network intrusion detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":21,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.576955Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:5b35ae113e9403e21545d0bc86305c3dc4ed9167cf60df836bfa7963c27d8c92","observation_id":"168228a7-20c5-4614-bc4e-e8f28be1141a","resolution":{"observed_at":"2026-08-04T11:20:13.576955Z","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":"2026-08-04T11:20:13.654476Z","title":"Leveraging large language models for wireless symbol detection via in-context learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":22,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.654476Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:a3c0655a2d1f0d8533caa1e0163ea47b017f58086e557d1a07669590534db2f8","observation_id":"eb3a6646-8112-4cb6-8165-26f123b12776","resolution":{"observed_at":"2026-08-04T11:20:13.654476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16739","last_updated":"2025-06-04T07:22:47Z","snapshot_observed_at":"2026-08-03T22:38:00.596602Z","submitted_at":"2023-09-28T06:22:59Z","title":"Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16739","snapshot_observed_at":"2026-08-04T11:20:13.727839Z","title":"Pushing large language models to the 6g edge: Vision, challenges, and opportunities,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":23,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.727839Z"},"links":{"cited_paper":"/paper/2309.16739","citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:cabb28a0631186d5db2e99c54d1dc1d81203b36515896a2fa5d6172f74564309","observation_id":"71e6e476-a898-4c80-ab82-1e8dfb7aa7e9","resolution":{"observed_at":"2026-08-04T11:20:13.727839Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18062","last_updated":"2024-02-28T05:46:23Z","snapshot_observed_at":"2026-08-05T03:14:03.003063Z","submitted_at":"2024-02-28T05:46:23Z","title":"Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18062","snapshot_observed_at":"2026-08-04T11:20:13.778254Z","title":"Generative ai for unmanned vehicle swarms: Challenges, applications and opportunities,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":24,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.778254Z"},"links":{"cited_paper":"/paper/2402.18062","citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:ad52ebcdeeb4ba1a2abbad5b1699b6393cbe554c248e9dabb9f801f34f3fcc35","observation_id":"07778636-ce17-44d9-ae43-3c9843c38bd9","resolution":{"observed_at":"2026-08-04T11:20:13.778254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02341","last_updated":"2025-03-25T15:55:33Z","snapshot_observed_at":"2026-08-01T22:19:58.635790Z","submitted_at":"2025-01-04T17:32:12Z","title":"UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobility","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02341","snapshot_observed_at":"2026-08-04T11:20:13.859247Z","title":"Uavs meet llms: Overviews and perspectives toward agentic low-altitude mobility,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":25,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.859247Z"},"links":{"cited_paper":"/paper/2501.02341","citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:bad44f7a129899a66b7ab463d6a32ea262ef64dbab234465a94da369d276383e","observation_id":"0d546668-839f-4bcc-8f84-0efca3f49b79","resolution":{"observed_at":"2026-08-04T11:20:13.859247Z","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":"2026-08-04T11:20:13.932646Z","title":"Large language models for uavs: Current state and pathways to the future,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":26,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:13.932646Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:64da7abe2eda2c0053980a1e4347995aae60e78ed5786fa485bcaa15ed49b79c","observation_id":"7819e20a-2d8e-4a4e-8562-438e8bf3d910","resolution":{"observed_at":"2026-08-04T11:20:13.932646Z","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":"2026-08-04T11:20:14.030115Z","title":"Net-gpt: A llm-empowered man-in-the-middle chatbot for unmanned aerial vehicle,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":27,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:14.030115Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:7bd89027af12f704143bdc0f4bd033956bd5a6d983abbcdc90a1bbe86c8ff8c2","observation_id":"7199f101-0b8c-4001-a627-a443a9add35c","resolution":{"observed_at":"2026-08-04T11:20:14.030115Z","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":"2026-08-04T11:20:14.087916Z","title":"Enhancing autonomous system security and resilience with generative ai: A compre- hensive survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":28,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:14.087916Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:6b44161fc5c8e46ea0583bad5b7c4785ee40ed2c9587f7a0c8d6ec074200c605","observation_id":"ef68ea87-0041-43ae-9463-ab3bfda9e3ff","resolution":{"observed_at":"2026-08-04T11:20:14.087916Z","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":"2026-08-04T11:20:14.189252Z","title":"Large model based agents: State-of-the-art, cooperation paradigms, security and privacy, and future trends,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":29,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:14.189252Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:971144277c6be40efa1d28181f30b8033e4378a152245b4eee8b4f5c1dc27cf6","observation_id":"93316c48-d4fc-4b7d-90a4-941ec1218cf0","resolution":{"observed_at":"2026-08-04T11:20:14.189252Z","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":"2026-08-04T11:20:14.341346Z","title":"Optimal lap altitude for maximum coverage,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":30,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:14.341346Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:70dfbf048bc6c14addcff1b64e2bbf6575e179581d1a435c3c182bda4c999057","observation_id":"6a05e326-953e-4272-9ed4-223f4f273784","resolution":{"observed_at":"2026-08-04T11:20:14.341346Z","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":"2026-08-04T11:20:14.502691Z","title":"Joint communication scheduling and velocity control in multi-uav-assisted sensor networks: A deep reinforcement learning approach,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":31,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:14.502691Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:7d02fd9741c92e3645fb5efb6085ef983a68480c7bf3da5b56c82f5a93076b7a","observation_id":"ff5a0256-9875-4078-a8c7-5ef2b141c312","resolution":{"observed_at":"2026-08-04T11:20:14.502691Z","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":"2026-08-04T11:20:14.614203Z","title":"On-board deep q-network for uav-assisted online power transfer and data collection,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":32,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:14.614203Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:bfddbc9abb4ad33b410fc500ad91c4beaa67408ca390b965843aaa49cc9eecf4","observation_id":"97b0675a-a008-4b6d-b21e-73deef69c740","resolution":{"observed_at":"2026-08-04T11:20:14.614203Z","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":"2026-08-04T11:20:14.730085Z","title":"Joint flight cruise control and data collection in uav-aided internet of things: An onboard deep reinforcement learning approach,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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":33,"source":"pdf_text","source_observed_at":"2026-08-04T11:20:14.730085Z"},"links":{"citing_paper":"/paper/2510.05698"},"observation_digest":"sha256:9ee6142ceffbea04d7467c17cc668897e4608c856209307843f7aa72c8fc331e","observation_id":"2ffbfc5e-b57c-4da2-adfa-7eb5eb84965e","resolution":{"observed_at":"2026-08-04T11:20:14.730085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2510.05698","last_updated":"2026-08-03T14:54:31Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-06T23:28:17.938338Z","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"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":32,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":32},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2510.05698."}