{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:5TIDCSJSI2HZN6NGJOJGZLIG4J","short_pith_number":"pith:5TIDCSJS","schema_version":"1.0","canonical_sha256":"ecd0314932468f96f9a64b926cad06e2570a27c988080021500ebc977649c8b9","source":{"kind":"arxiv","id":"2508.07778","version":1},"attestation_state":"computed","paper":{"title":"An Experimental Reservoir-Augmented Foundation Model: 6G O-RAN Case Study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Amir Ashtari Gargari, Farhad Rezazadeh, Hatim Chergui, Jiongyu Dai, Lingjia Liu, Raymond Zhao","submitted_at":"2025-08-11T09:05:09Z","abstract_excerpt":"Next-generation open radio access networks (O-RAN) continuously stream tens of key performance indicators (KPIs) together with raw in-phase/quadrature (IQ) samples, yielding ultra-high-dimensional, non-stationary time series that overwhelm conventional transformer architectures. We introduce a reservoir-augmented masked autoencoding transformer (RA-MAT). This time series foundation model employs echo state network (ESN) computing with masked autoencoding to satisfy the stringent latency, energy efficiency, and scalability requirements of 6G O-RAN testing. A fixed, randomly initialized ESN rapi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2508.07778","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-08-11T09:05:09Z","cross_cats_sorted":[],"title_canon_sha256":"ffa843e2bdd6a37977cd1e1de7f2a4e60ae7b5e56307d274fac2b3e6af76e057","abstract_canon_sha256":"1a5d9375ad32069f79a297b7b1eede1b36d715a8fff30659a34a51544cce2106"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:51:52.185425Z","signature_b64":"u3twRT9YU8a1I4oWjHmTYxDkyUwqa5l7pJ6jMFO9STxsnpHUw/k0feOOGw7n8gYDN6Og1U+87nCxqUbTlLr0BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ecd0314932468f96f9a64b926cad06e2570a27c988080021500ebc977649c8b9","last_reissued_at":"2026-07-05T11:51:52.184930Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:51:52.184930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Experimental Reservoir-Augmented Foundation Model: 6G O-RAN Case Study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Amir Ashtari Gargari, Farhad Rezazadeh, Hatim Chergui, Jiongyu Dai, Lingjia Liu, Raymond Zhao","submitted_at":"2025-08-11T09:05:09Z","abstract_excerpt":"Next-generation open radio access networks (O-RAN) continuously stream tens of key performance indicators (KPIs) together with raw in-phase/quadrature (IQ) samples, yielding ultra-high-dimensional, non-stationary time series that overwhelm conventional transformer architectures. We introduce a reservoir-augmented masked autoencoding transformer (RA-MAT). This time series foundation model employs echo state network (ESN) computing with masked autoencoding to satisfy the stringent latency, energy efficiency, and scalability requirements of 6G O-RAN testing. A fixed, randomly initialized ESN rapi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.07778","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2508.07778/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2508.07778","created_at":"2026-07-05T11:51:52.185000+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.07778v1","created_at":"2026-07-05T11:51:52.185000+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.07778","created_at":"2026-07-05T11:51:52.185000+00:00"},{"alias_kind":"pith_short_12","alias_value":"5TIDCSJSI2HZ","created_at":"2026-07-05T11:51:52.185000+00:00"},{"alias_kind":"pith_short_16","alias_value":"5TIDCSJSI2HZN6NG","created_at":"2026-07-05T11:51:52.185000+00:00"},{"alias_kind":"pith_short_8","alias_value":"5TIDCSJS","created_at":"2026-07-05T11:51:52.185000+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J","json":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J.json","graph_json":"https://pith.science/api/pith-number/5TIDCSJSI2HZN6NGJOJGZLIG4J/graph.json","events_json":"https://pith.science/api/pith-number/5TIDCSJSI2HZN6NGJOJGZLIG4J/events.json","paper":"https://pith.science/paper/5TIDCSJS"},"agent_actions":{"view_html":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J","download_json":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J.json","view_paper":"https://pith.science/paper/5TIDCSJS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.07778&json=true","fetch_graph":"https://pith.science/api/pith-number/5TIDCSJSI2HZN6NGJOJGZLIG4J/graph.json","fetch_events":"https://pith.science/api/pith-number/5TIDCSJSI2HZN6NGJOJGZLIG4J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J/action/storage_attestation","attest_author":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J/action/author_attestation","sign_citation":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J/action/citation_signature","submit_replication":"https://pith.science/pith/5TIDCSJSI2HZN6NGJOJGZLIG4J/action/replication_record"}},"created_at":"2026-07-05T11:51:52.185000+00:00","updated_at":"2026-07-05T11:51:52.185000+00:00"}