{"as_of":"2026-08-13T12:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6797c242dd2d17e9060d32fdc181d4b286eaca6ce8dcf9e64b301e174d02e6bd","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T17:25:31.523265Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-11T16:23:57.321895Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.07053","last_updated":"2024-06-11T08:35:23Z","snapshot_observed_at":"2026-08-12T23:45:47.066031Z","submitted_at":"2024-06-11T08:35:23Z","title":"TelecomRAG: Taming Telecom Standards with Retrieval Augmented Generation and LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07053","snapshot_observed_at":"2026-08-11T17:25:31.523265Z","title":"TelecomRAG: Taming telecom standards with retrieval augmented generation and LLMs","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":38,"source":"arxiv_source","source_observed_at":"2026-08-11T17:25:31.523265Z"},"links":{"cited_paper":"/paper/2406.07053","citing_paper":"/paper/2412.09041"},"observation_digest":"sha256:87a7b2dcbe100f2d40171f848c2e7272287b80bb15c3727d7bf72e32c074a231","observation_id":"880d92b7-b813-48d2-b204-156f73af02d8","resolution":{"observed_at":"2026-08-11T17:25:31.523265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07053","last_updated":"2024-06-11T08:35:23Z","snapshot_observed_at":"2026-08-12T23:45:47.066031Z","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:a4df11760706b63dcb621594ccfeeae9b6698491425ec44bc5eb47142aa30336","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 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2406.07053/citation-record","integrity":"/paper/2406.07053/integrity","json":"/paper/2406.07053/citation-record.json","paper":"/paper/2406.07053"},"outbound":[],"paper":{"arxiv_id":"2406.07053","last_updated":"2024-06-11T08:35:23Z","latest_version":1,"primary_category":"cs.NI","snapshot_observed_at":"2026-08-12T23:45:47.066031Z","submitted_at":"2024-06-11T08:35:23Z","title":"TelecomRAG: Taming Telecom Standards with Retrieval Augmented Generation and LLMs"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.07053."}