{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:G2FP3ZHSB7ZYTK44ZWCSN5F35A","short_pith_number":"pith:G2FP3ZHS","canonical_record":{"source":{"id":"2504.17219","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T03:17:57Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"12adb0b0a87b904c3b185c24f67bbc060b76ece3405a81fb5b872e5ea7ec0cce","abstract_canon_sha256":"0d427593b5b4c5c49ef71c515e4fac887ea3026dd8fff6cd14a481ba79a82c61"},"schema_version":"1.0"},"canonical_sha256":"368afde4f20ff389ab9ccd8526f4bbe83e0fabef9da6cfbf3d8020e53229dbfb","source":{"kind":"arxiv","id":"2504.17219","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.17219","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"arxiv_version","alias_value":"2504.17219v1","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.17219","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"pith_short_12","alias_value":"G2FP3ZHSB7ZY","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"pith_short_16","alias_value":"G2FP3ZHSB7ZYTK44","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"pith_short_8","alias_value":"G2FP3ZHS","created_at":"2026-07-05T10:53:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:G2FP3ZHSB7ZYTK44ZWCSN5F35A","target":"record","payload":{"canonical_record":{"source":{"id":"2504.17219","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T03:17:57Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"12adb0b0a87b904c3b185c24f67bbc060b76ece3405a81fb5b872e5ea7ec0cce","abstract_canon_sha256":"0d427593b5b4c5c49ef71c515e4fac887ea3026dd8fff6cd14a481ba79a82c61"},"schema_version":"1.0"},"canonical_sha256":"368afde4f20ff389ab9ccd8526f4bbe83e0fabef9da6cfbf3d8020e53229dbfb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:53:24.497117Z","signature_b64":"+Gy0A4oUdofqj35XlUidVPlW4NNkkZKKpylEefmxW2NnXgC3GQ/we9L+mJ2X1oZdUmcHSt5wU9Ixsl1QZuNyCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"368afde4f20ff389ab9ccd8526f4bbe83e0fabef9da6cfbf3d8020e53229dbfb","last_reissued_at":"2026-07-05T10:53:24.496578Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:53:24.496578Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.17219","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":"2026-07-05T10:53:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tTt0mqpImaTK26cMcpUHmNeS7Fpr0RHvKPTLADO6LN7OmEUjkt8pY+gXp+KXUMojqkvYhFEv51tLyq+b0iUICA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T11:20:22.441004Z"},"content_sha256":"a6780b10deabb4493f703f20ccd42e3a3b19cf58f1745e81720607cde17cfe94","schema_version":"1.0","event_id":"sha256:a6780b10deabb4493f703f20ccd42e3a3b19cf58f1745e81720607cde17cfe94"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:G2FP3ZHSB7ZYTK44ZWCSN5F35A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enhancing Variational Autoencoders with Smooth Robust Latent Encoding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.LG","authors_text":"Hyomin Lee, Jongheon Jeong, Minseon Kim, Sangwon Jang, Sung Ju Hwang","submitted_at":"2025-04-24T03:17:57Z","abstract_excerpt":"Variational Autoencoders (VAEs) have played a key role in scaling up diffusion-based generative models, as in Stable Diffusion, yet questions regarding their robustness remain largely underexplored. Although adversarial training has been an established technique for enhancing robustness in predictive models, it has been overlooked for generative models due to concerns about potential fidelity degradation by the nature of trade-offs between performance and robustness. In this work, we challenge this presumption, introducing Smooth Robust Latent VAE (SRL-VAE), a novel adversarial training framew"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.17219","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/2504.17219/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":"2026-07-05T10:53:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tOcUEwJLmtAfOOytrrOSye5lZ4mlbHF5+dKTMyXFkDvGHW+MOgwTz6q+KDzlQK4CgSd+pv1cZI6n3+QvFh+RBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T11:20:22.441485Z"},"content_sha256":"bee06c56894bf6c77a759499d426d279831ab346ce3213268525683e19ba634a","schema_version":"1.0","event_id":"sha256:bee06c56894bf6c77a759499d426d279831ab346ce3213268525683e19ba634a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G2FP3ZHSB7ZYTK44ZWCSN5F35A/bundle.json","state_url":"https://pith.science/pith/G2FP3ZHSB7ZYTK44ZWCSN5F35A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G2FP3ZHSB7ZYTK44ZWCSN5F35A/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":"2026-08-08T11:20:22Z","links":{"resolver":"https://pith.science/pith/G2FP3ZHSB7ZYTK44ZWCSN5F35A","bundle":"https://pith.science/pith/G2FP3ZHSB7ZYTK44ZWCSN5F35A/bundle.json","state":"https://pith.science/pith/G2FP3ZHSB7ZYTK44ZWCSN5F35A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G2FP3ZHSB7ZYTK44ZWCSN5F35A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:G2FP3ZHSB7ZYTK44ZWCSN5F35A","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":"0d427593b5b4c5c49ef71c515e4fac887ea3026dd8fff6cd14a481ba79a82c61","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T03:17:57Z","title_canon_sha256":"12adb0b0a87b904c3b185c24f67bbc060b76ece3405a81fb5b872e5ea7ec0cce"},"schema_version":"1.0","source":{"id":"2504.17219","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.17219","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"arxiv_version","alias_value":"2504.17219v1","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.17219","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"pith_short_12","alias_value":"G2FP3ZHSB7ZY","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"pith_short_16","alias_value":"G2FP3ZHSB7ZYTK44","created_at":"2026-07-05T10:53:24Z"},{"alias_kind":"pith_short_8","alias_value":"G2FP3ZHS","created_at":"2026-07-05T10:53:24Z"}],"graph_snapshots":[{"event_id":"sha256:bee06c56894bf6c77a759499d426d279831ab346ce3213268525683e19ba634a","target":"graph","created_at":"2026-07-05T10:53:24Z","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/2504.17219/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Variational Autoencoders (VAEs) have played a key role in scaling up diffusion-based generative models, as in Stable Diffusion, yet questions regarding their robustness remain largely underexplored. Although adversarial training has been an established technique for enhancing robustness in predictive models, it has been overlooked for generative models due to concerns about potential fidelity degradation by the nature of trade-offs between performance and robustness. In this work, we challenge this presumption, introducing Smooth Robust Latent VAE (SRL-VAE), a novel adversarial training framew","authors_text":"Hyomin Lee, Jongheon Jeong, Minseon Kim, Sangwon Jang, Sung Ju Hwang","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T03:17:57Z","title":"Enhancing Variational Autoencoders with Smooth Robust Latent Encoding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.17219","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:a6780b10deabb4493f703f20ccd42e3a3b19cf58f1745e81720607cde17cfe94","target":"record","created_at":"2026-07-05T10:53:24Z","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":"0d427593b5b4c5c49ef71c515e4fac887ea3026dd8fff6cd14a481ba79a82c61","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-24T03:17:57Z","title_canon_sha256":"12adb0b0a87b904c3b185c24f67bbc060b76ece3405a81fb5b872e5ea7ec0cce"},"schema_version":"1.0","source":{"id":"2504.17219","kind":"arxiv","version":1}},"canonical_sha256":"368afde4f20ff389ab9ccd8526f4bbe83e0fabef9da6cfbf3d8020e53229dbfb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"368afde4f20ff389ab9ccd8526f4bbe83e0fabef9da6cfbf3d8020e53229dbfb","first_computed_at":"2026-07-05T10:53:24.496578Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:53:24.496578Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+Gy0A4oUdofqj35XlUidVPlW4NNkkZKKpylEefmxW2NnXgC3GQ/we9L+mJ2X1oZdUmcHSt5wU9Ixsl1QZuNyCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:53:24.497117Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.17219","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a6780b10deabb4493f703f20ccd42e3a3b19cf58f1745e81720607cde17cfe94","sha256:bee06c56894bf6c77a759499d426d279831ab346ce3213268525683e19ba634a"],"state_sha256":"49ceeb6c39e3aad601e416564f49f2f1038bcca696fe8c91f84971a857ffab77"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C7plT+88DyVO7Dbjo73GS4L3aP92Klw/JC9Qhc4oNK1be5Uot1otK/KQM1XyCQaXw/9qY/RsB1qwBfkFW5LfDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T11:20:22.444785Z","bundle_sha256":"46ddd5410dd3dc10bc5c3e89376f60f73f208f6f6dbc1ac58df7140dd0978920"}}