{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:QUE5QVL542ZLZMMPGYGRRNAMFB","short_pith_number":"pith:QUE5QVL5","schema_version":"1.0","canonical_sha256":"8509d8557de6b2bcb18f360d18b40c2869f8ff537ccdcab55782e2e476579d8a","source":{"kind":"arxiv","id":"2308.10354","version":1},"attestation_state":"computed","paper":{"title":"Imaginations of WALL-E : Reconstructing Experiences with an Imagination-Inspired Module for Advanced AI Systems","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Hamidreza Amirzadeh, Hossein Sameti, Mohammad Jalal Nematbakhsh, Seyed Arshan Dalili, Soroush Gooran, Zeinab Sadat Taghavi","submitted_at":"2023-08-20T20:10:55Z","abstract_excerpt":"In this paper, we introduce a novel Artificial Intelligence (AI) system inspired by the philosophical and psychoanalytical concept of imagination as a ``Re-construction of Experiences\". Our AI system is equipped with an imagination-inspired module that bridges the gap between textual inputs and other modalities, enriching the derived information based on previously learned experiences. A unique feature of our system is its ability to formulate independent perceptions of inputs. This leads to unique interpretations of a concept that may differ from human interpretations but are equally valid, a"},"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":"2308.10354","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2023-08-20T20:10:55Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"bdc5da8ffb7a8454b8ee0250669db4f6aeb1b361bbba93d379754d7f7ea3d55b","abstract_canon_sha256":"106902dc87e868f309b5f7f7aae16e85a4c6678c89e85266581d60736dcd0100"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:43:08.217081Z","signature_b64":"DkKmt43t74aSqnqjvrw1swneJhp/W98eH2hGNMGeu4iwGVKQf8XX7W1yfr2gtfdFtLtofwiRGZWSswW69SmXCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8509d8557de6b2bcb18f360d18b40c2869f8ff537ccdcab55782e2e476579d8a","last_reissued_at":"2026-07-05T06:43:08.216701Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:43:08.216701Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Imaginations of WALL-E : Reconstructing Experiences with an Imagination-Inspired Module for Advanced AI Systems","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Hamidreza Amirzadeh, Hossein Sameti, Mohammad Jalal Nematbakhsh, Seyed Arshan Dalili, Soroush Gooran, Zeinab Sadat Taghavi","submitted_at":"2023-08-20T20:10:55Z","abstract_excerpt":"In this paper, we introduce a novel Artificial Intelligence (AI) system inspired by the philosophical and psychoanalytical concept of imagination as a ``Re-construction of Experiences\". Our AI system is equipped with an imagination-inspired module that bridges the gap between textual inputs and other modalities, enriching the derived information based on previously learned experiences. A unique feature of our system is its ability to formulate independent perceptions of inputs. This leads to unique interpretations of a concept that may differ from human interpretations but are equally valid, a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.10354","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/2308.10354/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":"2308.10354","created_at":"2026-07-05T06:43:08.216767+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.10354v1","created_at":"2026-07-05T06:43:08.216767+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.10354","created_at":"2026-07-05T06:43:08.216767+00:00"},{"alias_kind":"pith_short_12","alias_value":"QUE5QVL542ZL","created_at":"2026-07-05T06:43:08.216767+00:00"},{"alias_kind":"pith_short_16","alias_value":"QUE5QVL542ZLZMMP","created_at":"2026-07-05T06:43:08.216767+00:00"},{"alias_kind":"pith_short_8","alias_value":"QUE5QVL5","created_at":"2026-07-05T06:43:08.216767+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2501.16971","citing_title":"RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples","ref_index":96,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB","json":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB.json","graph_json":"https://pith.science/api/pith-number/QUE5QVL542ZLZMMPGYGRRNAMFB/graph.json","events_json":"https://pith.science/api/pith-number/QUE5QVL542ZLZMMPGYGRRNAMFB/events.json","paper":"https://pith.science/paper/QUE5QVL5"},"agent_actions":{"view_html":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB","download_json":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB.json","view_paper":"https://pith.science/paper/QUE5QVL5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.10354&json=true","fetch_graph":"https://pith.science/api/pith-number/QUE5QVL542ZLZMMPGYGRRNAMFB/graph.json","fetch_events":"https://pith.science/api/pith-number/QUE5QVL542ZLZMMPGYGRRNAMFB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB/action/storage_attestation","attest_author":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB/action/author_attestation","sign_citation":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB/action/citation_signature","submit_replication":"https://pith.science/pith/QUE5QVL542ZLZMMPGYGRRNAMFB/action/replication_record"}},"created_at":"2026-07-05T06:43:08.216767+00:00","updated_at":"2026-07-05T06:43:08.216767+00:00"}