{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:X6A3ZCPKT2NGGXCPKB6C6DOOFD","short_pith_number":"pith:X6A3ZCPK","canonical_record":{"source":{"id":"2201.00308","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-01-02T06:44:23Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"8ed776dafe67b7e823dd76cb27cb1f172bfbd21103cb92924bcc50f169e9f272","abstract_canon_sha256":"d1e47d52213d7ddba2ac51afc5bd063107636c05ff10c4ce7d27c732aa25c08b"},"schema_version":"1.0"},"canonical_sha256":"bf81bc89ea9e9a635c4f507c2f0dce28eefa59bd44263d79867b37bc31bd088e","source":{"kind":"arxiv","id":"2201.00308","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.00308","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"arxiv_version","alias_value":"2201.00308v3","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.00308","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"pith_short_12","alias_value":"X6A3ZCPKT2NG","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"pith_short_16","alias_value":"X6A3ZCPKT2NGGXCP","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"pith_short_8","alias_value":"X6A3ZCPK","created_at":"2026-07-05T05:20:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:X6A3ZCPKT2NGGXCPKB6C6DOOFD","target":"record","payload":{"canonical_record":{"source":{"id":"2201.00308","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-01-02T06:44:23Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"8ed776dafe67b7e823dd76cb27cb1f172bfbd21103cb92924bcc50f169e9f272","abstract_canon_sha256":"d1e47d52213d7ddba2ac51afc5bd063107636c05ff10c4ce7d27c732aa25c08b"},"schema_version":"1.0"},"canonical_sha256":"bf81bc89ea9e9a635c4f507c2f0dce28eefa59bd44263d79867b37bc31bd088e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:20:09.517924Z","signature_b64":"ZA6wkxB7APfgfNvejGQgOVUcbAl3oPsI/jPUT1+VIkHLOK1t6DyqT5Y/rSr41eeFVfmDi+jenQfPw16LbTHKDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bf81bc89ea9e9a635c4f507c2f0dce28eefa59bd44263d79867b37bc31bd088e","last_reissued_at":"2026-07-05T05:20:09.517436Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:20:09.517436Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2201.00308","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":"2026-07-05T05:20:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BQF82W2EiMc/nozv/Y0KNm+IrpEOmbvzVJO5cOZY/7rRY55euDjWK5kGUDFwL+kgcXaqQLyqftuvV5JdHzKoCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T00:43:01.787244Z"},"content_sha256":"aa56869301fb81bbcb40c7fe20c72bb8ec1667a1037068eae39fc00f73b784b2","schema_version":"1.0","event_id":"sha256:aa56869301fb81bbcb40c7fe20c72bb8ec1667a1037068eae39fc00f73b784b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:X6A3ZCPKT2NGGXCPKB6C6DOOFD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Abhishek Kumar, Avideep Mukherjee, Kushagra Pandey, Piyush Rai","submitted_at":"2022-01-02T06:44:23Z","abstract_excerpt":"Diffusion probabilistic models have been shown to generate state-of-the-art results on several competitive image synthesis benchmarks but lack a low-dimensional, interpretable latent space, and are slow at generation. On the other hand, standard Variational Autoencoders (VAEs) typically have access to a low-dimensional latent space but exhibit poor sample quality. We present DiffuseVAE, a novel generative framework that integrates VAE within a diffusion model framework, and leverage this to design novel conditional parameterizations for diffusion models. We show that the resulting model equips"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.00308","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/2201.00308/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":"2026-07-05T05:20:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uribo7mLCLdJVg6AXte3txdLDgRKC4q+D7qR8f4C+g45yYlB/g+yzELp0ee7AXUSk148Z/G6eMa1Jz9oFOZsBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T00:43:01.787641Z"},"content_sha256":"32f1de628ce5b1aa998731acb0980fd2edb29716546a9d6c2c55e4fb5387a5a4","schema_version":"1.0","event_id":"sha256:32f1de628ce5b1aa998731acb0980fd2edb29716546a9d6c2c55e4fb5387a5a4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X6A3ZCPKT2NGGXCPKB6C6DOOFD/bundle.json","state_url":"https://pith.science/pith/X6A3ZCPKT2NGGXCPKB6C6DOOFD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X6A3ZCPKT2NGGXCPKB6C6DOOFD/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":"2026-07-25T00:43:01Z","links":{"resolver":"https://pith.science/pith/X6A3ZCPKT2NGGXCPKB6C6DOOFD","bundle":"https://pith.science/pith/X6A3ZCPKT2NGGXCPKB6C6DOOFD/bundle.json","state":"https://pith.science/pith/X6A3ZCPKT2NGGXCPKB6C6DOOFD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X6A3ZCPKT2NGGXCPKB6C6DOOFD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:X6A3ZCPKT2NGGXCPKB6C6DOOFD","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":"d1e47d52213d7ddba2ac51afc5bd063107636c05ff10c4ce7d27c732aa25c08b","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-01-02T06:44:23Z","title_canon_sha256":"8ed776dafe67b7e823dd76cb27cb1f172bfbd21103cb92924bcc50f169e9f272"},"schema_version":"1.0","source":{"id":"2201.00308","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.00308","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"arxiv_version","alias_value":"2201.00308v3","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.00308","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"pith_short_12","alias_value":"X6A3ZCPKT2NG","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"pith_short_16","alias_value":"X6A3ZCPKT2NGGXCP","created_at":"2026-07-05T05:20:09Z"},{"alias_kind":"pith_short_8","alias_value":"X6A3ZCPK","created_at":"2026-07-05T05:20:09Z"}],"graph_snapshots":[{"event_id":"sha256:32f1de628ce5b1aa998731acb0980fd2edb29716546a9d6c2c55e4fb5387a5a4","target":"graph","created_at":"2026-07-05T05:20:09Z","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/2201.00308/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion probabilistic models have been shown to generate state-of-the-art results on several competitive image synthesis benchmarks but lack a low-dimensional, interpretable latent space, and are slow at generation. On the other hand, standard Variational Autoencoders (VAEs) typically have access to a low-dimensional latent space but exhibit poor sample quality. We present DiffuseVAE, a novel generative framework that integrates VAE within a diffusion model framework, and leverage this to design novel conditional parameterizations for diffusion models. We show that the resulting model equips","authors_text":"Abhishek Kumar, Avideep Mukherjee, Kushagra Pandey, Piyush Rai","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-01-02T06:44:23Z","title":"DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.00308","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:aa56869301fb81bbcb40c7fe20c72bb8ec1667a1037068eae39fc00f73b784b2","target":"record","created_at":"2026-07-05T05:20:09Z","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":"d1e47d52213d7ddba2ac51afc5bd063107636c05ff10c4ce7d27c732aa25c08b","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-01-02T06:44:23Z","title_canon_sha256":"8ed776dafe67b7e823dd76cb27cb1f172bfbd21103cb92924bcc50f169e9f272"},"schema_version":"1.0","source":{"id":"2201.00308","kind":"arxiv","version":3}},"canonical_sha256":"bf81bc89ea9e9a635c4f507c2f0dce28eefa59bd44263d79867b37bc31bd088e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bf81bc89ea9e9a635c4f507c2f0dce28eefa59bd44263d79867b37bc31bd088e","first_computed_at":"2026-07-05T05:20:09.517436Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:20:09.517436Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZA6wkxB7APfgfNvejGQgOVUcbAl3oPsI/jPUT1+VIkHLOK1t6DyqT5Y/rSr41eeFVfmDi+jenQfPw16LbTHKDA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:20:09.517924Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.00308","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aa56869301fb81bbcb40c7fe20c72bb8ec1667a1037068eae39fc00f73b784b2","sha256:32f1de628ce5b1aa998731acb0980fd2edb29716546a9d6c2c55e4fb5387a5a4"],"state_sha256":"4ddcf6bffbaaccb1ca7ca2d6cbba78afcc7c4f75b9d1dec11208bf3da148ff3e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YCXZaMs4wwWYLVLpc9j42DuBrIS2GwjPgoQnYXN7LQRJTV69NlHKsXyY+pnqqbS7KWQvXFiz56u0BmUkSovdAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-25T00:43:01.790616Z","bundle_sha256":"859dbe0a4918ff7c67cc78837b8bc5073d4faa0f4ad2d7c77fb7300f5433e15c"}}