{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2C7X5JOQCU6VCMOGF3N5DY3TFV","short_pith_number":"pith:2C7X5JOQ","canonical_record":{"source":{"id":"2504.00434","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-01T05:36:13Z","cross_cats_sorted":[],"title_canon_sha256":"5a7b4e8fbb88ae54360cd412120e22f4b69605c693515abdff60539f2b4e7ca9","abstract_canon_sha256":"3956a88b4707ffe778818b13590c5918620b13e66a51329ab3d5f97aaa711cc4"},"schema_version":"1.0"},"canonical_sha256":"d0bf7ea5d0153d5131c62edbd1e3732d7f6e8a596ac0553f4de41bfd57b08fe8","source":{"kind":"arxiv","id":"2504.00434","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.00434","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"arxiv_version","alias_value":"2504.00434v1","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.00434","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"pith_short_12","alias_value":"2C7X5JOQCU6V","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"pith_short_16","alias_value":"2C7X5JOQCU6VCMOG","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"pith_short_8","alias_value":"2C7X5JOQ","created_at":"2026-07-05T10:42:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2C7X5JOQCU6VCMOGF3N5DY3TFV","target":"record","payload":{"canonical_record":{"source":{"id":"2504.00434","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-01T05:36:13Z","cross_cats_sorted":[],"title_canon_sha256":"5a7b4e8fbb88ae54360cd412120e22f4b69605c693515abdff60539f2b4e7ca9","abstract_canon_sha256":"3956a88b4707ffe778818b13590c5918620b13e66a51329ab3d5f97aaa711cc4"},"schema_version":"1.0"},"canonical_sha256":"d0bf7ea5d0153d5131c62edbd1e3732d7f6e8a596ac0553f4de41bfd57b08fe8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:42:26.493553Z","signature_b64":"K+hxNX1hThZ/vxVwQ0XCu0iNLR25EIxyqzZry/xM9X/4Ltp4pzhRbIFVD/EPVzrE+e6e7vYlcKXlHl7yzFxaAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0bf7ea5d0153d5131c62edbd1e3732d7f6e8a596ac0553f4de41bfd57b08fe8","last_reissued_at":"2026-07-05T10:42:26.493040Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:42:26.493040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.00434","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:42:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m0vN9pTySEqg24IBTXXxbLGPipo2oZyGq7eQJee+XnLakbvQc2u3PVuZ/c8JQayrVIZsgI/vC1gUf4969TUECw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:19:34.279802Z"},"content_sha256":"2969f7a486a270987fc5754fcd0533e2b8149391ecf5d51b0479ffd24bb5fdbd","schema_version":"1.0","event_id":"sha256:2969f7a486a270987fc5754fcd0533e2b8149391ecf5d51b0479ffd24bb5fdbd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2C7X5JOQCU6VCMOGF3N5DY3TFV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HERA: Hybrid Edge-cloud Resource Allocation for Cost-Efficient AI Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Haiying Shen, Mahdi Ghandi, Mingqin Li, Shiyi Liu, Shuai Che","submitted_at":"2025-04-01T05:36:13Z","abstract_excerpt":"In the realm of AI, large language models (LLMs) like GPT-4, central to the operation of AI agents, predominantly operate in the cloud, incurring high operational costs. With local-based small language models (SLMs) becoming more accurate, the necessity of cloud-exclusive processing is being reconsidered. An AI agent's response to a user's request comprises a series of subtasks or iterations. Existing approaches only allocate a single request between SLM and LLM to ensure their outputs are similar, but adopting this approach in the AI agent scenario for assigning each subtask is not effective "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.00434","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/2504.00434/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":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:42:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AhixGO2+EoXJe+9ScV7V3CImfrSjAAehKnSyuAnylj4GCsHbYkFTaW+omy6ass3drX48utgPahNi3SjB2bw2Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:19:34.280187Z"},"content_sha256":"8c42d41d8bb23e4523994efb04d6ca276805b7c272cd31caa7b5ea0f353727f9","schema_version":"1.0","event_id":"sha256:8c42d41d8bb23e4523994efb04d6ca276805b7c272cd31caa7b5ea0f353727f9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2C7X5JOQCU6VCMOGF3N5DY3TFV/bundle.json","state_url":"https://pith.science/pith/2C7X5JOQCU6VCMOGF3N5DY3TFV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2C7X5JOQCU6VCMOGF3N5DY3TFV/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":"2026-07-06T17:19:34Z","links":{"resolver":"https://pith.science/pith/2C7X5JOQCU6VCMOGF3N5DY3TFV","bundle":"https://pith.science/pith/2C7X5JOQCU6VCMOGF3N5DY3TFV/bundle.json","state":"https://pith.science/pith/2C7X5JOQCU6VCMOGF3N5DY3TFV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2C7X5JOQCU6VCMOGF3N5DY3TFV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2C7X5JOQCU6VCMOGF3N5DY3TFV","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":"3956a88b4707ffe778818b13590c5918620b13e66a51329ab3d5f97aaa711cc4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-01T05:36:13Z","title_canon_sha256":"5a7b4e8fbb88ae54360cd412120e22f4b69605c693515abdff60539f2b4e7ca9"},"schema_version":"1.0","source":{"id":"2504.00434","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.00434","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"arxiv_version","alias_value":"2504.00434v1","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.00434","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"pith_short_12","alias_value":"2C7X5JOQCU6V","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"pith_short_16","alias_value":"2C7X5JOQCU6VCMOG","created_at":"2026-07-05T10:42:26Z"},{"alias_kind":"pith_short_8","alias_value":"2C7X5JOQ","created_at":"2026-07-05T10:42:26Z"}],"graph_snapshots":[{"event_id":"sha256:8c42d41d8bb23e4523994efb04d6ca276805b7c272cd31caa7b5ea0f353727f9","target":"graph","created_at":"2026-07-05T10:42:26Z","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/2504.00434/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the realm of AI, large language models (LLMs) like GPT-4, central to the operation of AI agents, predominantly operate in the cloud, incurring high operational costs. With local-based small language models (SLMs) becoming more accurate, the necessity of cloud-exclusive processing is being reconsidered. An AI agent's response to a user's request comprises a series of subtasks or iterations. Existing approaches only allocate a single request between SLM and LLM to ensure their outputs are similar, but adopting this approach in the AI agent scenario for assigning each subtask is not effective ","authors_text":"Haiying Shen, Mahdi Ghandi, Mingqin Li, Shiyi Liu, Shuai Che","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-01T05:36:13Z","title":"HERA: Hybrid Edge-cloud Resource Allocation for Cost-Efficient AI Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.00434","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":"sha256:2969f7a486a270987fc5754fcd0533e2b8149391ecf5d51b0479ffd24bb5fdbd","target":"record","created_at":"2026-07-05T10:42:26Z","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":"3956a88b4707ffe778818b13590c5918620b13e66a51329ab3d5f97aaa711cc4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-01T05:36:13Z","title_canon_sha256":"5a7b4e8fbb88ae54360cd412120e22f4b69605c693515abdff60539f2b4e7ca9"},"schema_version":"1.0","source":{"id":"2504.00434","kind":"arxiv","version":1}},"canonical_sha256":"d0bf7ea5d0153d5131c62edbd1e3732d7f6e8a596ac0553f4de41bfd57b08fe8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d0bf7ea5d0153d5131c62edbd1e3732d7f6e8a596ac0553f4de41bfd57b08fe8","first_computed_at":"2026-07-05T10:42:26.493040Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:42:26.493040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"K+hxNX1hThZ/vxVwQ0XCu0iNLR25EIxyqzZry/xM9X/4Ltp4pzhRbIFVD/EPVzrE+e6e7vYlcKXlHl7yzFxaAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:42:26.493553Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.00434","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2969f7a486a270987fc5754fcd0533e2b8149391ecf5d51b0479ffd24bb5fdbd","sha256:8c42d41d8bb23e4523994efb04d6ca276805b7c272cd31caa7b5ea0f353727f9"],"state_sha256":"5719b282455fc5f64a5beb482bf3c101939fffd9c5eb709b43424b7995e1f285"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"62avReNeFOICoOD/IMc/ibMkaclm9Nsgf2jeuTk+cv1VefvOhmK69lxHzp/VZ7wvAReSyqrr5QPgl8YsQJDBDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:19:34.282218Z","bundle_sha256":"72ed72e5bf4c1837a31396d4aead180553f7314d0fa98f1f1035c789d71a5f8a"}}