{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:A2HCQT4HOTEXLCMHHXGBJZYMKC","short_pith_number":"pith:A2HCQT4H","schema_version":"1.0","canonical_sha256":"068e284f8774c97589873dcc14e70c50b220695f163706bb21ae2c521659b0ed","source":{"kind":"arxiv","id":"2410.09099","version":2},"attestation_state":"computed","paper":{"title":"Adaptive Active Inference Agents for Heterogeneous and Lifelong Federated Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.DC"],"primary_cat":"cs.LG","authors_text":"Alireza Furutanpey, Anastasiya Danilenka, Anna Lackinger, Boris Sedlak, Marcin Paprzycki, Maria Ganzha, Schahram Dustdar, Victor Casamayor Pujol","submitted_at":"2024-10-09T10:43:29Z","abstract_excerpt":"Handling heterogeneity and unpredictability are two core problems in pervasive computing. The challenge is to seamlessly integrate devices with varying computational resources in a dynamic environment to form a cohesive system that can fulfill the needs of all participants. Existing work on adaptive systems typically focuses on optimizing individual variables or low-level Service Level Objectives (SLOs), such as constraining the usage of specific resources. While low-level control mechanisms permit fine-grained control over a system, they introduce considerable complexity, particularly in dyna"},"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":"2410.09099","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-09T10:43:29Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"5e3003b25a101da1259e57e66667c491fa07728418bb4acdedd3a6dde61543d3","abstract_canon_sha256":"a54cf1719ce6386367eab5b7c86d93eb1fb22c9e92015060869a7a945e7ddd74"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:27:17.262897Z","signature_b64":"QJ+eOi5VbryZNpaOqEitRSyXJaWlTPG9crbI9AzHYRaUoN8O5+CRWlUOpvqPPuLTyFdceuyeIohJzqfATxZyDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"068e284f8774c97589873dcc14e70c50b220695f163706bb21ae2c521659b0ed","last_reissued_at":"2026-07-05T10:27:17.262390Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:27:17.262390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adaptive Active Inference Agents for Heterogeneous and Lifelong Federated Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.DC"],"primary_cat":"cs.LG","authors_text":"Alireza Furutanpey, Anastasiya Danilenka, Anna Lackinger, Boris Sedlak, Marcin Paprzycki, Maria Ganzha, Schahram Dustdar, Victor Casamayor Pujol","submitted_at":"2024-10-09T10:43:29Z","abstract_excerpt":"Handling heterogeneity and unpredictability are two core problems in pervasive computing. The challenge is to seamlessly integrate devices with varying computational resources in a dynamic environment to form a cohesive system that can fulfill the needs of all participants. Existing work on adaptive systems typically focuses on optimizing individual variables or low-level Service Level Objectives (SLOs), such as constraining the usage of specific resources. While low-level control mechanisms permit fine-grained control over a system, they introduce considerable complexity, particularly in dyna"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.09099","kind":"arxiv","version":2},"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/2410.09099/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":"2410.09099","created_at":"2026-07-05T10:27:17.262451+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.09099v2","created_at":"2026-07-05T10:27:17.262451+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.09099","created_at":"2026-07-05T10:27:17.262451+00:00"},{"alias_kind":"pith_short_12","alias_value":"A2HCQT4HOTEX","created_at":"2026-07-05T10:27:17.262451+00:00"},{"alias_kind":"pith_short_16","alias_value":"A2HCQT4HOTEXLCMH","created_at":"2026-07-05T10:27:17.262451+00:00"},{"alias_kind":"pith_short_8","alias_value":"A2HCQT4H","created_at":"2026-07-05T10:27:17.262451+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/A2HCQT4HOTEXLCMHHXGBJZYMKC","json":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC.json","graph_json":"https://pith.science/api/pith-number/A2HCQT4HOTEXLCMHHXGBJZYMKC/graph.json","events_json":"https://pith.science/api/pith-number/A2HCQT4HOTEXLCMHHXGBJZYMKC/events.json","paper":"https://pith.science/paper/A2HCQT4H"},"agent_actions":{"view_html":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC","download_json":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC.json","view_paper":"https://pith.science/paper/A2HCQT4H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.09099&json=true","fetch_graph":"https://pith.science/api/pith-number/A2HCQT4HOTEXLCMHHXGBJZYMKC/graph.json","fetch_events":"https://pith.science/api/pith-number/A2HCQT4HOTEXLCMHHXGBJZYMKC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC/action/storage_attestation","attest_author":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC/action/author_attestation","sign_citation":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC/action/citation_signature","submit_replication":"https://pith.science/pith/A2HCQT4HOTEXLCMHHXGBJZYMKC/action/replication_record"}},"created_at":"2026-07-05T10:27:17.262451+00:00","updated_at":"2026-07-05T10:27:17.262451+00:00"}