{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:Z3JIFDZ3DHGYQVT4MXMOQLVRZN","short_pith_number":"pith:Z3JIFDZ3","canonical_record":{"source":{"id":"2507.18004","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-07-24T00:39:19Z","cross_cats_sorted":[],"title_canon_sha256":"ad8b9d2ec5e6691a42e35050d4631ba9779d280c37eb58a3295ffbe7a5f45dc2","abstract_canon_sha256":"9bb6e6c7380c518df0944b6aa25fc16a9cfd974a84b05421a084fd25a5574c8e"},"schema_version":"1.0"},"canonical_sha256":"ced2828f3b19cd88567c65d8e82eb1cb42dddcfc281ab3590f7a64856f9407b8","source":{"kind":"arxiv","id":"2507.18004","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.18004","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"arxiv_version","alias_value":"2507.18004v2","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.18004","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"pith_short_12","alias_value":"Z3JIFDZ3DHGY","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"pith_short_16","alias_value":"Z3JIFDZ3DHGYQVT4","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"pith_short_8","alias_value":"Z3JIFDZ3","created_at":"2026-07-05T11:46:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:Z3JIFDZ3DHGYQVT4MXMOQLVRZN","target":"record","payload":{"canonical_record":{"source":{"id":"2507.18004","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-07-24T00:39:19Z","cross_cats_sorted":[],"title_canon_sha256":"ad8b9d2ec5e6691a42e35050d4631ba9779d280c37eb58a3295ffbe7a5f45dc2","abstract_canon_sha256":"9bb6e6c7380c518df0944b6aa25fc16a9cfd974a84b05421a084fd25a5574c8e"},"schema_version":"1.0"},"canonical_sha256":"ced2828f3b19cd88567c65d8e82eb1cb42dddcfc281ab3590f7a64856f9407b8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:46:45.509192Z","signature_b64":"l+EvJNG0fLxUf175j4GM4l8nH2KYarpDkFpKKHJezO0emcQSwRrtFN28guMRM/dl7HEFgauN1b/MEXizvcYSCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ced2828f3b19cd88567c65d8e82eb1cb42dddcfc281ab3590f7a64856f9407b8","last_reissued_at":"2026-07-05T11:46:45.508712Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:46:45.508712Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.18004","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:46:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q/ZijLJL3/6Do0D+KPYd/mw3iVLXUnzvNEZ+0nzk67/8F3YF2szcgzKlyLFMsx5Rlt9tljbfZyS1MaietRYoCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T09:10:12.615775Z"},"content_sha256":"18ad7e06186db3fd43ab0f5cecc60d64e13da756ac76ca08729659e9381abd13","schema_version":"1.0","event_id":"sha256:18ad7e06186db3fd43ab0f5cecc60d64e13da756ac76ca08729659e9381abd13"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:Z3JIFDZ3DHGYQVT4MXMOQLVRZN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Shuhua Mao, Yusen Peng","submitted_at":"2025-07-24T00:39:19Z","abstract_excerpt":"How can AI move beyond imitation toward genuine creativity? This paper proposes the E.A.R.T.H. framework, a five-stage generative pipeline that transforms model-generated errors into creative assets through Error generation, Amplification, Refine selection, Transform, and Harness feedback. Drawing on cognitive science and generative modeling, we posit that \"creative potential hides in failure\" and operationalize this via structured prompts, semantic scoring, and human-in-the-loop evaluation. Implemented using LLaMA-2-7B-Chat, SBERT, BERTScore, CLIP, BLIP-2, and Stable Diffusion, the pipeline e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.18004","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/2507.18004/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":"2026-07-05T11:46:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tre+wz8xkF6v6FqiJNwDJIvKwiKxMyIOQKVoHV2D7MNYVnxgaQyHLp/5ZP0Cw8+QzKO46VTu5ANrSh3KbFbTAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T09:10:12.616352Z"},"content_sha256":"5dfd0b1f77a1c0f732ab2ba1bf8feaa1e952ff4f32df241cc57e9e40f9dae1b2","schema_version":"1.0","event_id":"sha256:5dfd0b1f77a1c0f732ab2ba1bf8feaa1e952ff4f32df241cc57e9e40f9dae1b2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z3JIFDZ3DHGYQVT4MXMOQLVRZN/bundle.json","state_url":"https://pith.science/pith/Z3JIFDZ3DHGYQVT4MXMOQLVRZN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z3JIFDZ3DHGYQVT4MXMOQLVRZN/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":"2026-08-08T09:10:12Z","links":{"resolver":"https://pith.science/pith/Z3JIFDZ3DHGYQVT4MXMOQLVRZN","bundle":"https://pith.science/pith/Z3JIFDZ3DHGYQVT4MXMOQLVRZN/bundle.json","state":"https://pith.science/pith/Z3JIFDZ3DHGYQVT4MXMOQLVRZN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z3JIFDZ3DHGYQVT4MXMOQLVRZN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:Z3JIFDZ3DHGYQVT4MXMOQLVRZN","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":"9bb6e6c7380c518df0944b6aa25fc16a9cfd974a84b05421a084fd25a5574c8e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-07-24T00:39:19Z","title_canon_sha256":"ad8b9d2ec5e6691a42e35050d4631ba9779d280c37eb58a3295ffbe7a5f45dc2"},"schema_version":"1.0","source":{"id":"2507.18004","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.18004","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"arxiv_version","alias_value":"2507.18004v2","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.18004","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"pith_short_12","alias_value":"Z3JIFDZ3DHGY","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"pith_short_16","alias_value":"Z3JIFDZ3DHGYQVT4","created_at":"2026-07-05T11:46:45Z"},{"alias_kind":"pith_short_8","alias_value":"Z3JIFDZ3","created_at":"2026-07-05T11:46:45Z"}],"graph_snapshots":[{"event_id":"sha256:5dfd0b1f77a1c0f732ab2ba1bf8feaa1e952ff4f32df241cc57e9e40f9dae1b2","target":"graph","created_at":"2026-07-05T11:46:45Z","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/2507.18004/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"How can AI move beyond imitation toward genuine creativity? This paper proposes the E.A.R.T.H. framework, a five-stage generative pipeline that transforms model-generated errors into creative assets through Error generation, Amplification, Refine selection, Transform, and Harness feedback. Drawing on cognitive science and generative modeling, we posit that \"creative potential hides in failure\" and operationalize this via structured prompts, semantic scoring, and human-in-the-loop evaluation. Implemented using LLaMA-2-7B-Chat, SBERT, BERTScore, CLIP, BLIP-2, and Stable Diffusion, the pipeline e","authors_text":"Shuhua Mao, Yusen Peng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-07-24T00:39:19Z","title":"E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.18004","kind":"arxiv","version":2},"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":"sha256:18ad7e06186db3fd43ab0f5cecc60d64e13da756ac76ca08729659e9381abd13","target":"record","created_at":"2026-07-05T11:46:45Z","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":"9bb6e6c7380c518df0944b6aa25fc16a9cfd974a84b05421a084fd25a5574c8e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-07-24T00:39:19Z","title_canon_sha256":"ad8b9d2ec5e6691a42e35050d4631ba9779d280c37eb58a3295ffbe7a5f45dc2"},"schema_version":"1.0","source":{"id":"2507.18004","kind":"arxiv","version":2}},"canonical_sha256":"ced2828f3b19cd88567c65d8e82eb1cb42dddcfc281ab3590f7a64856f9407b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ced2828f3b19cd88567c65d8e82eb1cb42dddcfc281ab3590f7a64856f9407b8","first_computed_at":"2026-07-05T11:46:45.508712Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:46:45.508712Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l+EvJNG0fLxUf175j4GM4l8nH2KYarpDkFpKKHJezO0emcQSwRrtFN28guMRM/dl7HEFgauN1b/MEXizvcYSCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:46:45.509192Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.18004","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18ad7e06186db3fd43ab0f5cecc60d64e13da756ac76ca08729659e9381abd13","sha256:5dfd0b1f77a1c0f732ab2ba1bf8feaa1e952ff4f32df241cc57e9e40f9dae1b2"],"state_sha256":"86f9dc985721de35d65f738572045b392796ee7ea798a11177fae9c12a16e5ec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bxScNReMnC0GBEOWEdeuoeEhKTXAbWQhBCyjiXrrW/RGTk/Vg+Z2Mg65DWPTERtltInAp4/Wb2YVdAuL6EBGAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T09:10:12.621379Z","bundle_sha256":"2dc9bc2766f0390cc9fb06e9a6c8f8113e58991ff05fe5b5a11a8432d3da5780"}}