{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:B2Q7WGCWTK5QN2ISX2PIGFYVIL","short_pith_number":"pith:B2Q7WGCW","canonical_record":{"source":{"id":"1805.07468","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T23:02:14Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a61dba6f3f2a2c4ef19689ed4565e19ed2fc8d77df2b19c74ab68436ea48b28a","abstract_canon_sha256":"3581189d199ecedf005bb7313eb40a70a68da92dc07b92c35c96dcc2be7ac946"},"schema_version":"1.0"},"canonical_sha256":"0ea1fb18569abb06e912be9e83171542e78fe554a54f77fea64e37d81d3192e0","source":{"kind":"arxiv","id":"1805.07468","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.07468","created_at":"2026-05-18T00:15:33Z"},{"alias_kind":"arxiv_version","alias_value":"1805.07468v1","created_at":"2026-05-18T00:15:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.07468","created_at":"2026-05-18T00:15:33Z"},{"alias_kind":"pith_short_12","alias_value":"B2Q7WGCWTK5Q","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"B2Q7WGCWTK5QN2IS","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"B2Q7WGCW","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:B2Q7WGCWTK5QN2ISX2PIGFYVIL","target":"record","payload":{"canonical_record":{"source":{"id":"1805.07468","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T23:02:14Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a61dba6f3f2a2c4ef19689ed4565e19ed2fc8d77df2b19c74ab68436ea48b28a","abstract_canon_sha256":"3581189d199ecedf005bb7313eb40a70a68da92dc07b92c35c96dcc2be7ac946"},"schema_version":"1.0"},"canonical_sha256":"0ea1fb18569abb06e912be9e83171542e78fe554a54f77fea64e37d81d3192e0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:33.512339Z","signature_b64":"CGnhup4cVujr+/be5b1O1DTOMGS2bqMnTgFDbdMWd4j+ItaEO8Xk1GAgJvacJGYYkhujRxyFXNCSGW9i5fgnAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0ea1fb18569abb06e912be9e83171542e78fe554a54f77fea64e37d81d3192e0","last_reissued_at":"2026-05-18T00:15:33.511703Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:33.511703Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.07468","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":"2026-05-18T00:15:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KpmP/sAnFoWuv/NW2z7W5WEfgx5+4cm1gJFRIlfDzNiug2MfBxap7BTkAfJQ4GXNjDaf0Hur3oUDAhmK/fMIBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T23:38:23.643077Z"},"content_sha256":"29b4e63d803d65d8463ae00a214f134a61ae6fe20efcfcc240a5e029b69c28d4","schema_version":"1.0","event_id":"sha256:29b4e63d803d65d8463ae00a214f134a61ae6fe20efcfcc240a5e029b69c28d4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:B2Q7WGCWTK5QN2ISX2PIGFYVIL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Learning of Neural Networks to Explain Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Quanshi Zhang, Song-Chun Zhu, Ying Nian Wu, Yuchen Liu, Yu Yang","submitted_at":"2018-05-18T23:02:14Z","abstract_excerpt":"This paper presents an unsupervised method to learn a neural network, namely an explainer, to interpret a pre-trained convolutional neural network (CNN), i.e., explaining knowledge representations hidden in middle conv-layers of the CNN. Given feature maps of a certain conv-layer of the CNN, the explainer performs like an auto-encoder, which first disentangles the feature maps into object-part features and then inverts object-part features back to features of higher conv-layers of the CNN. More specifically, the explainer contains interpretable conv-layers, where each filter disentangles the r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.07468","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":"2026-05-18T00:15:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+MubxVbAnvmPRyNi/IJMN3u3ma2hDaq8TnalRRltvJfsztYyQwmCHd8iF5x5eBmKiYiYsM9e1Rk9vsCIV9skDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T23:38:23.643819Z"},"content_sha256":"ad9081d0b425844b7b26864096fb18ebb6ae043b3f93ec31691c31f64062f4b7","schema_version":"1.0","event_id":"sha256:ad9081d0b425844b7b26864096fb18ebb6ae043b3f93ec31691c31f64062f4b7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B2Q7WGCWTK5QN2ISX2PIGFYVIL/bundle.json","state_url":"https://pith.science/pith/B2Q7WGCWTK5QN2ISX2PIGFYVIL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B2Q7WGCWTK5QN2ISX2PIGFYVIL/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":"2026-05-28T23:38:23Z","links":{"resolver":"https://pith.science/pith/B2Q7WGCWTK5QN2ISX2PIGFYVIL","bundle":"https://pith.science/pith/B2Q7WGCWTK5QN2ISX2PIGFYVIL/bundle.json","state":"https://pith.science/pith/B2Q7WGCWTK5QN2ISX2PIGFYVIL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B2Q7WGCWTK5QN2ISX2PIGFYVIL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:B2Q7WGCWTK5QN2ISX2PIGFYVIL","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":"3581189d199ecedf005bb7313eb40a70a68da92dc07b92c35c96dcc2be7ac946","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T23:02:14Z","title_canon_sha256":"a61dba6f3f2a2c4ef19689ed4565e19ed2fc8d77df2b19c74ab68436ea48b28a"},"schema_version":"1.0","source":{"id":"1805.07468","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.07468","created_at":"2026-05-18T00:15:33Z"},{"alias_kind":"arxiv_version","alias_value":"1805.07468v1","created_at":"2026-05-18T00:15:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.07468","created_at":"2026-05-18T00:15:33Z"},{"alias_kind":"pith_short_12","alias_value":"B2Q7WGCWTK5Q","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"B2Q7WGCWTK5QN2IS","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"B2Q7WGCW","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:ad9081d0b425844b7b26864096fb18ebb6ae043b3f93ec31691c31f64062f4b7","target":"graph","created_at":"2026-05-18T00:15:33Z","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":"This paper presents an unsupervised method to learn a neural network, namely an explainer, to interpret a pre-trained convolutional neural network (CNN), i.e., explaining knowledge representations hidden in middle conv-layers of the CNN. Given feature maps of a certain conv-layer of the CNN, the explainer performs like an auto-encoder, which first disentangles the feature maps into object-part features and then inverts object-part features back to features of higher conv-layers of the CNN. More specifically, the explainer contains interpretable conv-layers, where each filter disentangles the r","authors_text":"Quanshi Zhang, Song-Chun Zhu, Ying Nian Wu, Yuchen Liu, Yu Yang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T23:02:14Z","title":"Unsupervised Learning of Neural Networks to Explain Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.07468","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":"sha256:29b4e63d803d65d8463ae00a214f134a61ae6fe20efcfcc240a5e029b69c28d4","target":"record","created_at":"2026-05-18T00:15:33Z","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":"3581189d199ecedf005bb7313eb40a70a68da92dc07b92c35c96dcc2be7ac946","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T23:02:14Z","title_canon_sha256":"a61dba6f3f2a2c4ef19689ed4565e19ed2fc8d77df2b19c74ab68436ea48b28a"},"schema_version":"1.0","source":{"id":"1805.07468","kind":"arxiv","version":1}},"canonical_sha256":"0ea1fb18569abb06e912be9e83171542e78fe554a54f77fea64e37d81d3192e0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0ea1fb18569abb06e912be9e83171542e78fe554a54f77fea64e37d81d3192e0","first_computed_at":"2026-05-18T00:15:33.511703Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:33.511703Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CGnhup4cVujr+/be5b1O1DTOMGS2bqMnTgFDbdMWd4j+ItaEO8Xk1GAgJvacJGYYkhujRxyFXNCSGW9i5fgnAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:33.512339Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.07468","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29b4e63d803d65d8463ae00a214f134a61ae6fe20efcfcc240a5e029b69c28d4","sha256:ad9081d0b425844b7b26864096fb18ebb6ae043b3f93ec31691c31f64062f4b7"],"state_sha256":"6c9bca0be428bffb81d228246d61365715a9c864268439e293ef1de0885aabd0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7B/yIg+yEKYGLUrJXoBm7Am13hv7c5JN/qe0jmQ82PrejTBYjxZc0jt3zOnZOg9qhbD4mCBeecfKSJZElTFvDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T23:38:23.647834Z","bundle_sha256":"2ad81319ff962b681c3a1569e7cc8cbb74a6164feeba201746289ae70f2965ce"}}