{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:EPUE7CIFLDO3RIY66NYMUXQXPT","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":"2dd5fd30684e45650534195041df40dc1e2b54e286bea84b4bbfbd2f43ba132b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-18T05:55:29Z","title_canon_sha256":"a3184619164e80df0644a89cda7390380de435e2e544b71495a52beca242d108"},"schema_version":"1.0","source":{"id":"2606.19821","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.19821","created_at":"2026-06-19T16:12:36Z"},{"alias_kind":"arxiv_version","alias_value":"2606.19821v1","created_at":"2026-06-19T16:12:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.19821","created_at":"2026-06-19T16:12:36Z"},{"alias_kind":"pith_short_12","alias_value":"EPUE7CIFLDO3","created_at":"2026-06-19T16:12:36Z"},{"alias_kind":"pith_short_16","alias_value":"EPUE7CIFLDO3RIY6","created_at":"2026-06-19T16:12:36Z"},{"alias_kind":"pith_short_8","alias_value":"EPUE7CIF","created_at":"2026-06-19T16:12:36Z"}],"graph_snapshots":[{"event_id":"sha256:a4c3d66a74ade39d37da9e57bb1f7e77760f7e82257eaa2bd82f354dc172b666","target":"graph","created_at":"2026-06-19T16:12:36Z","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/2606.19821/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Key Performance Measurement (KPM) forecasting is essential for proactive network management of 5G and next-generation telecom networks. However, existing machine learning (ML) approaches face significant limitations in scalability and explainability, restricting their effectiveness in real-world deployments. We propose TelcoAgent, a foundation model-based framework that enables accurate, scalable, and explainable forecasting of multiple KPMs across diverse network cells without the need for site-specific training. Specifically, the framework comprises three key components: (i) an automated thr","authors_text":"Dara Ron, Een Kee Hong, Geon Kim, Pranshav Gajjar, Sukhdeep Singh, Suyog Moogi, Vijay K. Shah, V V N K Someswara Rao Koduri","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-18T05:55:29Z","title":"TelcoAgent: A Scalable 5G Multi-KPM Forecasting With 3GPP-Grounded Explainability"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.19821","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":"sha256:013e24de090fb0fe2d1067528d6aae1f02c4ca8ed55eb2c0a3fc35678e13f5d8","target":"record","created_at":"2026-06-19T16:12:36Z","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":"2dd5fd30684e45650534195041df40dc1e2b54e286bea84b4bbfbd2f43ba132b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-18T05:55:29Z","title_canon_sha256":"a3184619164e80df0644a89cda7390380de435e2e544b71495a52beca242d108"},"schema_version":"1.0","source":{"id":"2606.19821","kind":"arxiv","version":1}},"canonical_sha256":"23e84f890558ddb8a31ef370ca5e177cf26723652d46f0c5b52e16b84f4851d0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"23e84f890558ddb8a31ef370ca5e177cf26723652d46f0c5b52e16b84f4851d0","first_computed_at":"2026-06-19T16:12:36.208774Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:12:36.208774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"v3wAEVxqvPwGTkP8+1QNt0k2A+PZ3RNc9vLuO/0JyyCXnWfhe683hYt/u0lP0rbLbaK4y3MXLZhrPNHlmF5zCw==","signature_status":"signed_v1","signed_at":"2026-06-19T16:12:36.209121Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.19821","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:013e24de090fb0fe2d1067528d6aae1f02c4ca8ed55eb2c0a3fc35678e13f5d8","sha256:a4c3d66a74ade39d37da9e57bb1f7e77760f7e82257eaa2bd82f354dc172b666"],"state_sha256":"7658a20681205f728f0e94320873f22ff596d0a9af3d7364d67117dc0c2ed539"}