{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DMOMJPBXUHXD45SPIBTQCOXBUT","short_pith_number":"pith:DMOMJPBX","canonical_record":{"source":{"id":"2604.17362","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-04-19T10:17:47Z","cross_cats_sorted":[],"title_canon_sha256":"d184c5a87a075852cc8f656a50e3d233f8e1e5b98be612383295f1961e2de56f","abstract_canon_sha256":"d64188588e677d18834ce8c11c79eb07194b3ac3d791350b21558ffb2e636f6a"},"schema_version":"1.0"},"canonical_sha256":"1b1cc4bc37a1ee3e764f4067013ae1a4e9b7dc0a6efa7605c6c94b6642697ed2","source":{"kind":"arxiv","id":"2604.17362","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.17362","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"arxiv_version","alias_value":"2604.17362v3","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.17362","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"pith_short_12","alias_value":"DMOMJPBXUHXD","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"pith_short_16","alias_value":"DMOMJPBXUHXD45SP","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"pith_short_8","alias_value":"DMOMJPBX","created_at":"2026-06-23T02:12:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DMOMJPBXUHXD45SPIBTQCOXBUT","target":"record","payload":{"canonical_record":{"source":{"id":"2604.17362","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-04-19T10:17:47Z","cross_cats_sorted":[],"title_canon_sha256":"d184c5a87a075852cc8f656a50e3d233f8e1e5b98be612383295f1961e2de56f","abstract_canon_sha256":"d64188588e677d18834ce8c11c79eb07194b3ac3d791350b21558ffb2e636f6a"},"schema_version":"1.0"},"canonical_sha256":"1b1cc4bc37a1ee3e764f4067013ae1a4e9b7dc0a6efa7605c6c94b6642697ed2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T02:12:49.191999Z","signature_b64":"b4WkHjSmY6Qy7iWpmM5GgQ7rSgLAtAZEnXrVcbeTbT8sXanhg1NFkzh9+GP+/BTZgpXHDygSkPrLQ6B7HemuCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1b1cc4bc37a1ee3e764f4067013ae1a4e9b7dc0a6efa7605c6c94b6642697ed2","last_reissued_at":"2026-06-23T02:12:49.191504Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T02:12:49.191504Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.17362","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-23T02:12:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uO05zQRLg/OLh0v2Q3YfzdecNGUGEt8tE7NAYPbSyMIN+9KKbhLMp3gquT9MBlqYVBEz5CFUQmUugWVlcNnVDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:19:28.900934Z"},"content_sha256":"000a3b2b4252dfb80d36a790b4eced4898c909ef72de89318283db03bf6a15e3","schema_version":"1.0","event_id":"sha256:000a3b2b4252dfb80d36a790b4eced4898c909ef72de89318283db03bf6a15e3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DMOMJPBXUHXD45SPIBTQCOXBUT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"FARM uses a masked autoencoder and diffusion decoder on a new high-resolution low-altitude dataset to estimate aerial radio maps with improved generalization.","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Guobin Shen, Jiahui Liang, Liuqing Yang, Shijian Gao, Wenlihan Lu, Yifeng Yuan","submitted_at":"2026-04-19T10:17:47Z","abstract_excerpt":"Precise aerial radio environment characterization is vital for low-altitude airspace planning. However, existing datasets and construction methods lack the high-resolution granularity required for complex aerial spaces, particularly failing to capture spatial variations across both horizontal and vertical dimensions. To address these gaps, this paper introduces FARM, a pioneering foundation model for unified aerial radio map (ARM) construction. FARM is supported by our newly curated, high-granularity full-domain ARM dataset, which features multi-band and multi-antenna configurations, effective"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"FARM significantly outperforms state-of-the-art benchmarks and exhibits superior generalization capabilities across unseen scenarios.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the newly curated high-resolution dataset is representative of real low-altitude environments and that the masked autoencoder plus diffusion decoder can achieve unified estimation and generalization without any environmental priors.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"FARM is a foundation model combining masked autoencoders and diffusion decoders to estimate high-resolution aerial radio maps from a new multi-band low-altitude dataset, claiming superior accuracy and generalization over prior methods.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"FARM uses a masked autoencoder and diffusion decoder on a new high-resolution low-altitude dataset to estimate aerial radio maps with improved generalization.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"500cb40c75d08739d65f2342b9e5bd6ba96a95a47ed755f8bef1005eda8698ba"},"source":{"id":"2604.17362","kind":"arxiv","version":3},"verdict":{"id":"fd1f70b8-1be5-45d3-9b35-6c77cd8754a3","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-10T06:14:00.592159Z","strongest_claim":"FARM significantly outperforms state-of-the-art benchmarks and exhibits superior generalization capabilities across unseen scenarios.","one_line_summary":"FARM is a foundation model combining masked autoencoders and diffusion decoders to estimate high-resolution aerial radio maps from a new multi-band low-altitude dataset, claiming superior accuracy and generalization over prior methods.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the newly curated high-resolution dataset is representative of real low-altitude environments and that the masked autoencoder plus diffusion decoder can achieve unified estimation and generalization without any environmental priors.","pith_extraction_headline":"FARM uses a masked autoencoder and diffusion decoder on a new high-resolution low-altitude dataset to estimate aerial radio maps with improved generalization."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.17362/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":"fd1f70b8-1be5-45d3-9b35-6c77cd8754a3"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-23T02:12:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M2VqjtZgbJCv2OWqE0ch/4TOgfZ9pNdSZUtOx+WWMSrZc9W3Cr5pk3KKTdEmKFEJZ9pfFewldJqUGpGxoGcMCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:19:28.901597Z"},"content_sha256":"32a6e71a466d3e9004a38a5960c84d6e517054f3b96df514cdad79b98cb80d28","schema_version":"1.0","event_id":"sha256:32a6e71a466d3e9004a38a5960c84d6e517054f3b96df514cdad79b98cb80d28"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DMOMJPBXUHXD45SPIBTQCOXBUT/bundle.json","state_url":"https://pith.science/pith/DMOMJPBXUHXD45SPIBTQCOXBUT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DMOMJPBXUHXD45SPIBTQCOXBUT/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T23:19:28Z","links":{"resolver":"https://pith.science/pith/DMOMJPBXUHXD45SPIBTQCOXBUT","bundle":"https://pith.science/pith/DMOMJPBXUHXD45SPIBTQCOXBUT/bundle.json","state":"https://pith.science/pith/DMOMJPBXUHXD45SPIBTQCOXBUT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DMOMJPBXUHXD45SPIBTQCOXBUT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DMOMJPBXUHXD45SPIBTQCOXBUT","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"d64188588e677d18834ce8c11c79eb07194b3ac3d791350b21558ffb2e636f6a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-04-19T10:17:47Z","title_canon_sha256":"d184c5a87a075852cc8f656a50e3d233f8e1e5b98be612383295f1961e2de56f"},"schema_version":"1.0","source":{"id":"2604.17362","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.17362","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"arxiv_version","alias_value":"2604.17362v3","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.17362","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"pith_short_12","alias_value":"DMOMJPBXUHXD","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"pith_short_16","alias_value":"DMOMJPBXUHXD45SP","created_at":"2026-06-23T02:12:49Z"},{"alias_kind":"pith_short_8","alias_value":"DMOMJPBX","created_at":"2026-06-23T02:12:49Z"}],"graph_snapshots":[{"event_id":"sha256:32a6e71a466d3e9004a38a5960c84d6e517054f3b96df514cdad79b98cb80d28","target":"graph","created_at":"2026-06-23T02:12:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"FARM significantly outperforms state-of-the-art benchmarks and exhibits superior generalization capabilities across unseen scenarios."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That the newly curated high-resolution dataset is representative of real low-altitude environments and that the masked autoencoder plus diffusion decoder can achieve unified estimation and generalization without any environmental priors."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"FARM is a foundation model combining masked autoencoders and diffusion decoders to estimate high-resolution aerial radio maps from a new multi-band low-altitude dataset, claiming superior accuracy and generalization over prior methods."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"FARM uses a masked autoencoder and diffusion decoder on a new high-resolution low-altitude dataset to estimate aerial radio maps with improved generalization."}],"snapshot_sha256":"500cb40c75d08739d65f2342b9e5bd6ba96a95a47ed755f8bef1005eda8698ba"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2604.17362/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Precise aerial radio environment characterization is vital for low-altitude airspace planning. However, existing datasets and construction methods lack the high-resolution granularity required for complex aerial spaces, particularly failing to capture spatial variations across both horizontal and vertical dimensions. To address these gaps, this paper introduces FARM, a pioneering foundation model for unified aerial radio map (ARM) construction. FARM is supported by our newly curated, high-granularity full-domain ARM dataset, which features multi-band and multi-antenna configurations, effective","authors_text":"Guobin Shen, Jiahui Liang, Liuqing Yang, Shijian Gao, Wenlihan Lu, Yifeng Yuan","cross_cats":[],"headline":"FARM uses a masked autoencoder and diffusion decoder on a new high-resolution low-altitude dataset to estimate aerial radio maps with improved generalization.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-04-19T10:17:47Z","title":"FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.17362","kind":"arxiv","version":3},"verdict":{"created_at":"2026-05-10T06:14:00.592159Z","id":"fd1f70b8-1be5-45d3-9b35-6c77cd8754a3","model_set":{"reader":"grok-4.3"},"one_line_summary":"FARM is a foundation model combining masked autoencoders and diffusion decoders to estimate high-resolution aerial radio maps from a new multi-band low-altitude dataset, claiming superior accuracy and generalization over prior methods.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"FARM uses a masked autoencoder and diffusion decoder on a new high-resolution low-altitude dataset to estimate aerial radio maps with improved generalization.","strongest_claim":"FARM significantly outperforms state-of-the-art benchmarks and exhibits superior generalization capabilities across unseen scenarios.","weakest_assumption":"That the newly curated high-resolution dataset is representative of real low-altitude environments and that the masked autoencoder plus diffusion decoder can achieve unified estimation and generalization without any environmental priors."}},"verdict_id":"fd1f70b8-1be5-45d3-9b35-6c77cd8754a3"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:000a3b2b4252dfb80d36a790b4eced4898c909ef72de89318283db03bf6a15e3","target":"record","created_at":"2026-06-23T02:12:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"d64188588e677d18834ce8c11c79eb07194b3ac3d791350b21558ffb2e636f6a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-04-19T10:17:47Z","title_canon_sha256":"d184c5a87a075852cc8f656a50e3d233f8e1e5b98be612383295f1961e2de56f"},"schema_version":"1.0","source":{"id":"2604.17362","kind":"arxiv","version":3}},"canonical_sha256":"1b1cc4bc37a1ee3e764f4067013ae1a4e9b7dc0a6efa7605c6c94b6642697ed2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1b1cc4bc37a1ee3e764f4067013ae1a4e9b7dc0a6efa7605c6c94b6642697ed2","first_computed_at":"2026-06-23T02:12:49.191504Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T02:12:49.191504Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"b4WkHjSmY6Qy7iWpmM5GgQ7rSgLAtAZEnXrVcbeTbT8sXanhg1NFkzh9+GP+/BTZgpXHDygSkPrLQ6B7HemuCg==","signature_status":"signed_v1","signed_at":"2026-06-23T02:12:49.191999Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.17362","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:000a3b2b4252dfb80d36a790b4eced4898c909ef72de89318283db03bf6a15e3","sha256:32a6e71a466d3e9004a38a5960c84d6e517054f3b96df514cdad79b98cb80d28"],"state_sha256":"25be7ee0b761b8d6ec2f96b47ce327434a78cac5fe752f21ea9935774e0f2b26"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YgEtKONJMgCqvUtA6sAIMjQPTNWoqV+DIGylURCDCdAU9A992UhQA8KXbUAD75fE8Gsdo/Sbh4LfvG1qP7sMCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T23:19:28.907170Z","bundle_sha256":"b3ebfa5297abd37c0b255ed953b6d8692199893ddad0839855d258a7e069d4fe"}}