{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WDUS67EECQHSIROZH55T5XQGMX","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":"baef2f22beacab64e3e53be9ec6ffe7b78dd423bb67185802d42c3c1ed49d0b8","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2026-06-30T23:06:04Z","title_canon_sha256":"e4eae49a46035a06ee4d1d5e75ca6d54fad99eaeda70e6189c2943d39d37908e"},"schema_version":"1.0","source":{"id":"2607.00255","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00255","created_at":"2026-07-02T00:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00255v1","created_at":"2026-07-02T00:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00255","created_at":"2026-07-02T00:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"WDUS67EECQHS","created_at":"2026-07-02T00:18:41Z"},{"alias_kind":"pith_short_16","alias_value":"WDUS67EECQHSIROZ","created_at":"2026-07-02T00:18:41Z"},{"alias_kind":"pith_short_8","alias_value":"WDUS67EE","created_at":"2026-07-02T00:18:41Z"}],"graph_snapshots":[{"event_id":"sha256:952a4cca4cecc05f9137b38956936de83bb3decae0c1d3d0bee34374dbeb460f","target":"graph","created_at":"2026-07-02T00:18:41Z","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":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2607.00255/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Unmanned Aerial Vehicles (UAVs) have become key enabling platforms for low-altitude economic networks, yet achieving efficient and adaptive optimization under resource-constrained and dynamic environments remains challenging. This paper investigates language models for UAV-enabled Wireless Power Transfer (WPT) systems. First, a lightweight Small Language Model (SLM)-based solution is developed using a pre-trained BERT backbone, enhanced UAV embeddings and contextual features, a geometry-aware path decoder, and ensemble inference to achieve low complexity, low latency, and high energy efficienc","authors_text":"Abbas Jamalipour, Feibo Jiang, Kezhi Wang, Lei Mao, Li Dong, Xianbin Wang","cross_cats":["math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2026-06-30T23:06:04Z","title":"SLM, LLM or Agentic AI? Toward Intelligent UAV-Enabled WPT Systems in Low-Altitude Economy Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00255","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d402a8377d60205765a65a19c0a01cbe82de71110a24600629ddec075cadc3aa","target":"record","created_at":"2026-07-02T00:18:41Z","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":"baef2f22beacab64e3e53be9ec6ffe7b78dd423bb67185802d42c3c1ed49d0b8","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2026-06-30T23:06:04Z","title_canon_sha256":"e4eae49a46035a06ee4d1d5e75ca6d54fad99eaeda70e6189c2943d39d37908e"},"schema_version":"1.0","source":{"id":"2607.00255","kind":"arxiv","version":1}},"canonical_sha256":"b0e92f7c84140f2445d93f7b3ede0665f806fb254aeb937c14a6d31960bb74fd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0e92f7c84140f2445d93f7b3ede0665f806fb254aeb937c14a6d31960bb74fd","first_computed_at":"2026-07-02T00:18:41.273205Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-02T00:18:41.273205Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VKaTQsPRX3kK3Lg/LBFZCcXikwOC80qgp4lQRiT7G02or62r8F3u5kSVgjp1YK14mW8yA5KfYYvETUfk5qMiDw==","signature_status":"signed_v1","signed_at":"2026-07-02T00:18:41.273685Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.00255","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d402a8377d60205765a65a19c0a01cbe82de71110a24600629ddec075cadc3aa","sha256:952a4cca4cecc05f9137b38956936de83bb3decae0c1d3d0bee34374dbeb460f"],"state_sha256":"72b499b311f462ed960757e7090b7516633c4a559031955cf192716dc1b9aeee"}