{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:VONAWWHTKW5VPJVLGL3VOB7IE2","short_pith_number":"pith:VONAWWHT","canonical_record":{"source":{"id":"2102.12037","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-24T02:59:43Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e8c1d8bc35f610bae7388263bd6358fcbc70b1ea723edc2e0389aef781674023","abstract_canon_sha256":"68c2970f317c34e6c64fd7017f5f47deee5d3e1ee937d7a757182ef12bc8a383"},"schema_version":"1.0"},"canonical_sha256":"ab9a0b58f355bb57a6ab32f75707e826bcd40ce8e07d7e2ae1188d8a8c9a5842","source":{"kind":"arxiv","id":"2102.12037","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.12037","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"arxiv_version","alias_value":"2102.12037v3","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.12037","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"pith_short_12","alias_value":"VONAWWHTKW5V","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"pith_short_16","alias_value":"VONAWWHTKW5VPJVL","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"pith_short_8","alias_value":"VONAWWHT","created_at":"2026-07-05T04:27:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:VONAWWHTKW5VPJVLGL3VOB7IE2","target":"record","payload":{"canonical_record":{"source":{"id":"2102.12037","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-24T02:59:43Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e8c1d8bc35f610bae7388263bd6358fcbc70b1ea723edc2e0389aef781674023","abstract_canon_sha256":"68c2970f317c34e6c64fd7017f5f47deee5d3e1ee937d7a757182ef12bc8a383"},"schema_version":"1.0"},"canonical_sha256":"ab9a0b58f355bb57a6ab32f75707e826bcd40ce8e07d7e2ae1188d8a8c9a5842","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:27:04.861551Z","signature_b64":"dgJmQ+zn8fbBs/u+2E0KVLXFxqx9kL63gBmP8Ll5WIjTxg/5BW6ZiPdkfEdms//537U79Jvxkr8wpNZjRZu/Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ab9a0b58f355bb57a6ab32f75707e826bcd40ce8e07d7e2ae1188d8a8c9a5842","last_reissued_at":"2026-07-05T04:27:04.861148Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:27:04.861148Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2102.12037","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:27:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+tWEQPf+H/VQ4T5Tw/7SyX81iQ9S6DIpr5EnYQx3Fdx4QMZvj766b0y4aR/Yu3plNglLy52Y38i8L8jOhoAwDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:32:31.958239Z"},"content_sha256":"bea60ac3b916738b64ddbee6575cc1c235cc143a080310ad9c6f31b916e4a26b","schema_version":"1.0","event_id":"sha256:bea60ac3b916738b64ddbee6575cc1c235cc143a080310ad9c6f31b916e4a26b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:VONAWWHTKW5VPJVLGL3VOB7IE2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Conditional Image Generation by Conditioning Variational Auto-Encoders","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Frank Wood, Saeid Naderiparizi, William Harvey","submitted_at":"2021-02-24T02:59:43Z","abstract_excerpt":"We present a conditional variational auto-encoder (VAE) which, to avoid the substantial cost of training from scratch, uses an architecture and training objective capable of leveraging a foundation model in the form of a pretrained unconditional VAE. To train the conditional VAE, we only need to train an artifact to perform amortized inference over the unconditional VAE's latent variables given a conditioning input. We demonstrate our approach on tasks including image inpainting, for which it outperforms state-of-the-art GAN-based approaches at faithfully representing the inherent uncertainty."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.12037","kind":"arxiv","version":3},"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/2102.12037/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":"2026-07-05T04:27:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dy4HnfAh8AygCdTXlBpfm+x50RAF7wr9Ju2khELLGGcjzVz/vaZeu0W0rFG1AjlaIqV8wffvk4rPwUH8RHvwAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:32:31.958648Z"},"content_sha256":"15e3bf1230ba386c1b1e2c100c74af820f736d99a1266b01f8cb8e5435c6e100","schema_version":"1.0","event_id":"sha256:15e3bf1230ba386c1b1e2c100c74af820f736d99a1266b01f8cb8e5435c6e100"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VONAWWHTKW5VPJVLGL3VOB7IE2/bundle.json","state_url":"https://pith.science/pith/VONAWWHTKW5VPJVLGL3VOB7IE2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VONAWWHTKW5VPJVLGL3VOB7IE2/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":"2026-07-07T11:32:31Z","links":{"resolver":"https://pith.science/pith/VONAWWHTKW5VPJVLGL3VOB7IE2","bundle":"https://pith.science/pith/VONAWWHTKW5VPJVLGL3VOB7IE2/bundle.json","state":"https://pith.science/pith/VONAWWHTKW5VPJVLGL3VOB7IE2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VONAWWHTKW5VPJVLGL3VOB7IE2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:VONAWWHTKW5VPJVLGL3VOB7IE2","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":"68c2970f317c34e6c64fd7017f5f47deee5d3e1ee937d7a757182ef12bc8a383","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-24T02:59:43Z","title_canon_sha256":"e8c1d8bc35f610bae7388263bd6358fcbc70b1ea723edc2e0389aef781674023"},"schema_version":"1.0","source":{"id":"2102.12037","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.12037","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"arxiv_version","alias_value":"2102.12037v3","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.12037","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"pith_short_12","alias_value":"VONAWWHTKW5V","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"pith_short_16","alias_value":"VONAWWHTKW5VPJVL","created_at":"2026-07-05T04:27:04Z"},{"alias_kind":"pith_short_8","alias_value":"VONAWWHT","created_at":"2026-07-05T04:27:04Z"}],"graph_snapshots":[{"event_id":"sha256:15e3bf1230ba386c1b1e2c100c74af820f736d99a1266b01f8cb8e5435c6e100","target":"graph","created_at":"2026-07-05T04:27:04Z","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/2102.12037/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a conditional variational auto-encoder (VAE) which, to avoid the substantial cost of training from scratch, uses an architecture and training objective capable of leveraging a foundation model in the form of a pretrained unconditional VAE. To train the conditional VAE, we only need to train an artifact to perform amortized inference over the unconditional VAE's latent variables given a conditioning input. We demonstrate our approach on tasks including image inpainting, for which it outperforms state-of-the-art GAN-based approaches at faithfully representing the inherent uncertainty.","authors_text":"Frank Wood, Saeid Naderiparizi, William Harvey","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-24T02:59:43Z","title":"Conditional Image Generation by Conditioning Variational Auto-Encoders"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.12037","kind":"arxiv","version":3},"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:bea60ac3b916738b64ddbee6575cc1c235cc143a080310ad9c6f31b916e4a26b","target":"record","created_at":"2026-07-05T04:27:04Z","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":"68c2970f317c34e6c64fd7017f5f47deee5d3e1ee937d7a757182ef12bc8a383","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-24T02:59:43Z","title_canon_sha256":"e8c1d8bc35f610bae7388263bd6358fcbc70b1ea723edc2e0389aef781674023"},"schema_version":"1.0","source":{"id":"2102.12037","kind":"arxiv","version":3}},"canonical_sha256":"ab9a0b58f355bb57a6ab32f75707e826bcd40ce8e07d7e2ae1188d8a8c9a5842","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ab9a0b58f355bb57a6ab32f75707e826bcd40ce8e07d7e2ae1188d8a8c9a5842","first_computed_at":"2026-07-05T04:27:04.861148Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:27:04.861148Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dgJmQ+zn8fbBs/u+2E0KVLXFxqx9kL63gBmP8Ll5WIjTxg/5BW6ZiPdkfEdms//537U79Jvxkr8wpNZjRZu/Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:27:04.861551Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.12037","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bea60ac3b916738b64ddbee6575cc1c235cc143a080310ad9c6f31b916e4a26b","sha256:15e3bf1230ba386c1b1e2c100c74af820f736d99a1266b01f8cb8e5435c6e100"],"state_sha256":"093a1872dc0ee8f2ebd898038c37d449d3914fb846ec227a7e16dfecfc53da15"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PhWsoX3pp3nuGNgrsAZ4QTnY8nHO7uqerkantUgm8c3P6A8ZbPfUDkT9AFmFghaRPYVOJozIWk3Bf8tvHByDAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T11:32:31.960614Z","bundle_sha256":"aa06134d97aaa5915c8bdff24849d9f0a5e38e12bfb059836f299794b0a0abdf"}}