{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:GU5DAMCRKNOVQWDYIHXEYRCXS5","short_pith_number":"pith:GU5DAMCR","canonical_record":{"source":{"id":"2505.14476","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-20T15:10:01Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5ea559df1161b5291e1fc086bc9510d387034741cbfc7d61ba95fdf50d7e9ec9","abstract_canon_sha256":"db927de4a2e4173633386fd48d3c86e0d2c77c5c71160aff3a6b1c58c722e960"},"schema_version":"1.0"},"canonical_sha256":"353a303051535d58587841ee4c4457977ee79f19554177d9256c2fe7b12cf862","source":{"kind":"arxiv","id":"2505.14476","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.14476","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"arxiv_version","alias_value":"2505.14476v1","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.14476","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"pith_short_12","alias_value":"GU5DAMCRKNOV","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"pith_short_16","alias_value":"GU5DAMCRKNOVQWDY","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"pith_short_8","alias_value":"GU5DAMCR","created_at":"2026-07-05T11:06:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:GU5DAMCRKNOVQWDYIHXEYRCXS5","target":"record","payload":{"canonical_record":{"source":{"id":"2505.14476","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-20T15:10:01Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5ea559df1161b5291e1fc086bc9510d387034741cbfc7d61ba95fdf50d7e9ec9","abstract_canon_sha256":"db927de4a2e4173633386fd48d3c86e0d2c77c5c71160aff3a6b1c58c722e960"},"schema_version":"1.0"},"canonical_sha256":"353a303051535d58587841ee4c4457977ee79f19554177d9256c2fe7b12cf862","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:06:01.855137Z","signature_b64":"n34U8R+5SXQU4fK4sCbDFa0Iclbjt1ZtnYKlv+qYRtvAqQuSQeUgZyBFtMFICGHHMb/B4u36xplmWL/5LFTIAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"353a303051535d58587841ee4c4457977ee79f19554177d9256c2fe7b12cf862","last_reissued_at":"2026-07-05T11:06:01.854628Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:06:01.854628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.14476","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":"2026-07-05T11:06:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ksoURvTuB4YJbUkLW6NkxMpztVhFzCee5lgHCcWZF0FXpMuKTdzDuDG20bsUoUEkolU65OmUX1T4SOtN0TcJDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T22:42:49.683044Z"},"content_sha256":"740c58ccbb1b8a525747013e07331c8bd8d4f85a32833d4caf9e2907b8d8a8d1","schema_version":"1.0","event_id":"sha256:740c58ccbb1b8a525747013e07331c8bd8d4f85a32833d4caf9e2907b8d8a8d1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:GU5DAMCRKNOVQWDYIHXEYRCXS5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enhancing Interpretability of Sparse Latent Representations with Class Information","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Babak N. Araabi, Farshad Sangari Abiz, Reshad Hosseini","submitted_at":"2025-05-20T15:10:01Z","abstract_excerpt":"Variational Autoencoders (VAEs) are powerful generative models for learning latent representations. Standard VAEs generate dispersed and unstructured latent spaces by utilizing all dimensions, which limits their interpretability, especially in high-dimensional spaces. To address this challenge, Variational Sparse Coding (VSC) introduces a spike-and-slab prior distribution, resulting in sparse latent representations for each input. These sparse representations, characterized by a limited number of active dimensions, are inherently more interpretable. Despite this advantage, VSC falls short in p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.14476","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/2505.14476/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":"2026-07-05T11:06:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o9cWzTb18Fd797iyJX3ut1mfm4M1LxBZbAlybsWbiLYrY6/16207fYToam0A1JbBnaRuikyKlt5q6q4cmkFdCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T22:42:49.683620Z"},"content_sha256":"c597f480d84e93abbf1ccb20926c38730f34dfbfe78cd45ae515efbe3974def2","schema_version":"1.0","event_id":"sha256:c597f480d84e93abbf1ccb20926c38730f34dfbfe78cd45ae515efbe3974def2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GU5DAMCRKNOVQWDYIHXEYRCXS5/bundle.json","state_url":"https://pith.science/pith/GU5DAMCRKNOVQWDYIHXEYRCXS5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GU5DAMCRKNOVQWDYIHXEYRCXS5/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":"2026-08-07T22:42:49Z","links":{"resolver":"https://pith.science/pith/GU5DAMCRKNOVQWDYIHXEYRCXS5","bundle":"https://pith.science/pith/GU5DAMCRKNOVQWDYIHXEYRCXS5/bundle.json","state":"https://pith.science/pith/GU5DAMCRKNOVQWDYIHXEYRCXS5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GU5DAMCRKNOVQWDYIHXEYRCXS5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GU5DAMCRKNOVQWDYIHXEYRCXS5","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":"db927de4a2e4173633386fd48d3c86e0d2c77c5c71160aff3a6b1c58c722e960","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-20T15:10:01Z","title_canon_sha256":"5ea559df1161b5291e1fc086bc9510d387034741cbfc7d61ba95fdf50d7e9ec9"},"schema_version":"1.0","source":{"id":"2505.14476","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.14476","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"arxiv_version","alias_value":"2505.14476v1","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.14476","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"pith_short_12","alias_value":"GU5DAMCRKNOV","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"pith_short_16","alias_value":"GU5DAMCRKNOVQWDY","created_at":"2026-07-05T11:06:01Z"},{"alias_kind":"pith_short_8","alias_value":"GU5DAMCR","created_at":"2026-07-05T11:06:01Z"}],"graph_snapshots":[{"event_id":"sha256:c597f480d84e93abbf1ccb20926c38730f34dfbfe78cd45ae515efbe3974def2","target":"graph","created_at":"2026-07-05T11:06:01Z","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/2505.14476/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Variational Autoencoders (VAEs) are powerful generative models for learning latent representations. Standard VAEs generate dispersed and unstructured latent spaces by utilizing all dimensions, which limits their interpretability, especially in high-dimensional spaces. To address this challenge, Variational Sparse Coding (VSC) introduces a spike-and-slab prior distribution, resulting in sparse latent representations for each input. These sparse representations, characterized by a limited number of active dimensions, are inherently more interpretable. Despite this advantage, VSC falls short in p","authors_text":"Babak N. Araabi, Farshad Sangari Abiz, Reshad Hosseini","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-20T15:10:01Z","title":"Enhancing Interpretability of Sparse Latent Representations with Class Information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.14476","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":"sha256:740c58ccbb1b8a525747013e07331c8bd8d4f85a32833d4caf9e2907b8d8a8d1","target":"record","created_at":"2026-07-05T11:06:01Z","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":"db927de4a2e4173633386fd48d3c86e0d2c77c5c71160aff3a6b1c58c722e960","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-20T15:10:01Z","title_canon_sha256":"5ea559df1161b5291e1fc086bc9510d387034741cbfc7d61ba95fdf50d7e9ec9"},"schema_version":"1.0","source":{"id":"2505.14476","kind":"arxiv","version":1}},"canonical_sha256":"353a303051535d58587841ee4c4457977ee79f19554177d9256c2fe7b12cf862","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"353a303051535d58587841ee4c4457977ee79f19554177d9256c2fe7b12cf862","first_computed_at":"2026-07-05T11:06:01.854628Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:06:01.854628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n34U8R+5SXQU4fK4sCbDFa0Iclbjt1ZtnYKlv+qYRtvAqQuSQeUgZyBFtMFICGHHMb/B4u36xplmWL/5LFTIAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:06:01.855137Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.14476","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:740c58ccbb1b8a525747013e07331c8bd8d4f85a32833d4caf9e2907b8d8a8d1","sha256:c597f480d84e93abbf1ccb20926c38730f34dfbfe78cd45ae515efbe3974def2"],"state_sha256":"785e18f24ba085927030bde796cb07b6268fa919d7d06d9a4f395af49b4a554b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uC9aqF6KZlSgtuvstYTU5wfl4h1umI31EGTaDE+0cyou2eL6kEPkCYTTH2p+y2zXW5XE7h6YCgfdFE/3pfYjAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T22:42:49.687513Z","bundle_sha256":"5cd979aba5e422288c0c19256a506e208d0660f1ebcddd5b51716b6174f70ad5"}}