{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:5WIPFGPHZVB25LUUARPY75XTED","short_pith_number":"pith:5WIPFGPH","canonical_record":{"source":{"id":"1803.11203","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-29T18:06:38Z","cross_cats_sorted":[],"title_canon_sha256":"ff59ec9eaa7905b60ff183d626f1dd65cb8aa1ebaf965686fb25979056dd22cc","abstract_canon_sha256":"635d508443a162d5d7c7948d7c26b8551bd8cd0c9f5606c8e912559b553ec7ea"},"schema_version":"1.0"},"canonical_sha256":"ed90f299e7cd43aeae94045f8ff6f320fbeec21221ab8a22a43ec3a71a1d1280","source":{"kind":"arxiv","id":"1803.11203","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.11203","created_at":"2026-05-18T00:19:46Z"},{"alias_kind":"arxiv_version","alias_value":"1803.11203v1","created_at":"2026-05-18T00:19:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.11203","created_at":"2026-05-18T00:19:46Z"},{"alias_kind":"pith_short_12","alias_value":"5WIPFGPHZVB2","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"5WIPFGPHZVB25LUU","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"5WIPFGPH","created_at":"2026-05-18T12:32:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:5WIPFGPHZVB25LUUARPY75XTED","target":"record","payload":{"canonical_record":{"source":{"id":"1803.11203","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-29T18:06:38Z","cross_cats_sorted":[],"title_canon_sha256":"ff59ec9eaa7905b60ff183d626f1dd65cb8aa1ebaf965686fb25979056dd22cc","abstract_canon_sha256":"635d508443a162d5d7c7948d7c26b8551bd8cd0c9f5606c8e912559b553ec7ea"},"schema_version":"1.0"},"canonical_sha256":"ed90f299e7cd43aeae94045f8ff6f320fbeec21221ab8a22a43ec3a71a1d1280","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:19:46.743807Z","signature_b64":"7NrXQxb/nY9NTQm/XhYcDpuFTuQeZJqa/m1vIKyXpFfTzZgmvB1Xq5ZGpWpklwzuCSnJPmjVZmWD66pTFhiDDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ed90f299e7cd43aeae94045f8ff6f320fbeec21221ab8a22a43ec3a71a1d1280","last_reissued_at":"2026-05-18T00:19:46.743139Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:19:46.743139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.11203","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":"2026-05-18T00:19:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oaxPqLsds4n1gke8Gr8Ns6gNoKqFjhba2HSdDwBcqUz9eSUt5CGqW6m3jL2lA+LDq2XYsQeAnuYMYuVH28mSCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:20:43.126181Z"},"content_sha256":"26a7ba0ebae1654fed870bff1d608fd0288dff185587366b6d143c3bcc2a7e09","schema_version":"1.0","event_id":"sha256:26a7ba0ebae1654fed870bff1d608fd0288dff185587366b6d143c3bcc2a7e09"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:5WIPFGPHZVB25LUUARPY75XTED","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MemGEN: Memory is All You Need","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Karol Kurach, Marcin Michalski, Sylvain Gelly, Xiaohua Zhai","submitted_at":"2018-03-29T18:06:38Z","abstract_excerpt":"We propose a new learning paradigm called Deep Memory. It has the potential to completely revolutionize the Machine Learning field. Surprisingly, this paradigm has not been reinvented yet, unlike Deep Learning. At the core of this approach is the \\textit{Learning By Heart} principle, well studied in primary schools all over the world.\n  Inspired by poem recitation, or by $\\pi$ decimal memorization, we propose a concrete algorithm that mimics human behavior. We implement this paradigm on the task of generative modeling, and apply to images, natural language and even the $\\pi$ decimals as long a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.11203","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":""},"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":"2026-05-18T00:19:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EgHkWuuVSrYPIvDdnfLugfOo9+8zUb5BnflG4PZ7tI1hFZYZ+mc7CyT8fJSgkOOAkMoUpuhzISrdgFVI4QVoAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:20:43.126574Z"},"content_sha256":"7f0c7bc3f879017080d0fb0a718f9ad28cc0baa5fc8cadfac2584aa098b7de1e","schema_version":"1.0","event_id":"sha256:7f0c7bc3f879017080d0fb0a718f9ad28cc0baa5fc8cadfac2584aa098b7de1e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5WIPFGPHZVB25LUUARPY75XTED/bundle.json","state_url":"https://pith.science/pith/5WIPFGPHZVB25LUUARPY75XTED/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5WIPFGPHZVB25LUUARPY75XTED/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":"2026-05-31T21:20:43Z","links":{"resolver":"https://pith.science/pith/5WIPFGPHZVB25LUUARPY75XTED","bundle":"https://pith.science/pith/5WIPFGPHZVB25LUUARPY75XTED/bundle.json","state":"https://pith.science/pith/5WIPFGPHZVB25LUUARPY75XTED/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5WIPFGPHZVB25LUUARPY75XTED/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:5WIPFGPHZVB25LUUARPY75XTED","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":"635d508443a162d5d7c7948d7c26b8551bd8cd0c9f5606c8e912559b553ec7ea","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-29T18:06:38Z","title_canon_sha256":"ff59ec9eaa7905b60ff183d626f1dd65cb8aa1ebaf965686fb25979056dd22cc"},"schema_version":"1.0","source":{"id":"1803.11203","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.11203","created_at":"2026-05-18T00:19:46Z"},{"alias_kind":"arxiv_version","alias_value":"1803.11203v1","created_at":"2026-05-18T00:19:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.11203","created_at":"2026-05-18T00:19:46Z"},{"alias_kind":"pith_short_12","alias_value":"5WIPFGPHZVB2","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"5WIPFGPHZVB25LUU","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"5WIPFGPH","created_at":"2026-05-18T12:32:08Z"}],"graph_snapshots":[{"event_id":"sha256:7f0c7bc3f879017080d0fb0a718f9ad28cc0baa5fc8cadfac2584aa098b7de1e","target":"graph","created_at":"2026-05-18T00:19:46Z","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"},"paper":{"abstract_excerpt":"We propose a new learning paradigm called Deep Memory. It has the potential to completely revolutionize the Machine Learning field. Surprisingly, this paradigm has not been reinvented yet, unlike Deep Learning. At the core of this approach is the \\textit{Learning By Heart} principle, well studied in primary schools all over the world.\n  Inspired by poem recitation, or by $\\pi$ decimal memorization, we propose a concrete algorithm that mimics human behavior. We implement this paradigm on the task of generative modeling, and apply to images, natural language and even the $\\pi$ decimals as long a","authors_text":"Karol Kurach, Marcin Michalski, Sylvain Gelly, Xiaohua Zhai","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-29T18:06:38Z","title":"MemGEN: Memory is All You Need"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.11203","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":"sha256:26a7ba0ebae1654fed870bff1d608fd0288dff185587366b6d143c3bcc2a7e09","target":"record","created_at":"2026-05-18T00:19:46Z","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":"635d508443a162d5d7c7948d7c26b8551bd8cd0c9f5606c8e912559b553ec7ea","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-03-29T18:06:38Z","title_canon_sha256":"ff59ec9eaa7905b60ff183d626f1dd65cb8aa1ebaf965686fb25979056dd22cc"},"schema_version":"1.0","source":{"id":"1803.11203","kind":"arxiv","version":1}},"canonical_sha256":"ed90f299e7cd43aeae94045f8ff6f320fbeec21221ab8a22a43ec3a71a1d1280","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ed90f299e7cd43aeae94045f8ff6f320fbeec21221ab8a22a43ec3a71a1d1280","first_computed_at":"2026-05-18T00:19:46.743139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:19:46.743139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7NrXQxb/nY9NTQm/XhYcDpuFTuQeZJqa/m1vIKyXpFfTzZgmvB1Xq5ZGpWpklwzuCSnJPmjVZmWD66pTFhiDDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:19:46.743807Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.11203","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:26a7ba0ebae1654fed870bff1d608fd0288dff185587366b6d143c3bcc2a7e09","sha256:7f0c7bc3f879017080d0fb0a718f9ad28cc0baa5fc8cadfac2584aa098b7de1e"],"state_sha256":"31e148856a8c5e0055903bb2afd1a2410369c2f4b0837159eb7980248f0a6c09"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e6qkVxgSmE8jUznI5KUzF/aTWrWvjPwrYIbMVDcZFVNcukJd2ohZ9ed3KCbEI8xZRH6Y+74dsPjGxx3H8vKjDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T21:20:43.129301Z","bundle_sha256":"1e66e48ff9579f7a795c5f3a7a70e0fec7bb4a69122f6165e7a7681e8bd122be"}}