{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:SFPLHD45DHXU7X74FFGVDYCNVN","short_pith_number":"pith:SFPLHD45","canonical_record":{"source":{"id":"1905.12213","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-29T04:38:54Z","cross_cats_sorted":["cs.AI","cs.IT","math.IT","stat.ML"],"title_canon_sha256":"6a112d8ee3d055542241d569ffd55ffdd69bde118748551fb1df77b35cece04b","abstract_canon_sha256":"bab00936f15520b186e1f4a1cf0648a0d977aef3993d85684b72b1c76a5abde8"},"schema_version":"1.0"},"canonical_sha256":"915eb38f9d19ef4fdffc294d51e04dab7fa6bd22b9e004c028e2de4788414234","source":{"kind":"arxiv","id":"1905.12213","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.12213","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"arxiv_version","alias_value":"1905.12213v5","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.12213","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"pith_short_12","alias_value":"SFPLHD45DHXU","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"pith_short_16","alias_value":"SFPLHD45DHXU7X74","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"pith_short_8","alias_value":"SFPLHD45","created_at":"2026-07-05T01:11:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:SFPLHD45DHXU7X74FFGVDYCNVN","target":"record","payload":{"canonical_record":{"source":{"id":"1905.12213","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-29T04:38:54Z","cross_cats_sorted":["cs.AI","cs.IT","math.IT","stat.ML"],"title_canon_sha256":"6a112d8ee3d055542241d569ffd55ffdd69bde118748551fb1df77b35cece04b","abstract_canon_sha256":"bab00936f15520b186e1f4a1cf0648a0d977aef3993d85684b72b1c76a5abde8"},"schema_version":"1.0"},"canonical_sha256":"915eb38f9d19ef4fdffc294d51e04dab7fa6bd22b9e004c028e2de4788414234","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:11:40.266212Z","signature_b64":"rOvBQ8mea8Jw2hX3HxnSKaZ/dwxDsG1T6tu2fGDnuOZz5tcany2r3r4OuNVhL0xnxIFD9+VL1EhxIfq5YB1cAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"915eb38f9d19ef4fdffc294d51e04dab7fa6bd22b9e004c028e2de4788414234","last_reissued_at":"2026-07-05T01:11:40.265738Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:11:40.265738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.12213","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:11:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oyxKZwpExF4Ycy7CdPqf27aGbvJyIKAZXgzdB+/tzxIJeeSZLDw9UvdrlpGQ3ui48OCbbikVcHS3w0tGkwHvAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:21:07.127407Z"},"content_sha256":"5757e972f213bf07c5e4a77271ca6660e3d429ad6e2333000b14a5edfe37a5a0","schema_version":"1.0","event_id":"sha256:5757e972f213bf07c5e4a77271ca6660e3d429ad6e2333000b14a5edfe37a5a0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:SFPLHD45DHXU7X74FFGVDYCNVN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Where is the Information in a Deep Neural Network?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.IT","math.IT","stat.ML"],"primary_cat":"cs.LG","authors_text":"Alessandro Achille, Giovanni Paolini, Stefano Soatto","submitted_at":"2019-05-29T04:38:54Z","abstract_excerpt":"Whatever information a deep neural network has gleaned from training data is encoded in its weights. How this information affects the response of the network to future data remains largely an open question. Indeed, even defining and measuring information entails some subtleties, since a trained network is a deterministic map, so standard information measures can be degenerate. We measure information in a neural network via the optimal trade-off between accuracy of the response and complexity of the weights, measured by their coding length. Depending on the choice of code, the definition can re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.12213","kind":"arxiv","version":5},"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/1905.12213/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":"2026-07-05T01:11:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U366Z9B85kSALm6vt0Nnsx3gBUky7l4gWrvxisxDJP9h0ucLWJ/9DZCq1m0vTkF1dm2rdrNaaWRy30FKQmlfDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:21:07.127944Z"},"content_sha256":"16beab308aaa229ed54358e5fd9939cc61bf7e64ea5ccf25af1e3fbdcd2008b7","schema_version":"1.0","event_id":"sha256:16beab308aaa229ed54358e5fd9939cc61bf7e64ea5ccf25af1e3fbdcd2008b7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SFPLHD45DHXU7X74FFGVDYCNVN/bundle.json","state_url":"https://pith.science/pith/SFPLHD45DHXU7X74FFGVDYCNVN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SFPLHD45DHXU7X74FFGVDYCNVN/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":"2026-08-04T14:21:07Z","links":{"resolver":"https://pith.science/pith/SFPLHD45DHXU7X74FFGVDYCNVN","bundle":"https://pith.science/pith/SFPLHD45DHXU7X74FFGVDYCNVN/bundle.json","state":"https://pith.science/pith/SFPLHD45DHXU7X74FFGVDYCNVN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SFPLHD45DHXU7X74FFGVDYCNVN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:SFPLHD45DHXU7X74FFGVDYCNVN","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":"bab00936f15520b186e1f4a1cf0648a0d977aef3993d85684b72b1c76a5abde8","cross_cats_sorted":["cs.AI","cs.IT","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-29T04:38:54Z","title_canon_sha256":"6a112d8ee3d055542241d569ffd55ffdd69bde118748551fb1df77b35cece04b"},"schema_version":"1.0","source":{"id":"1905.12213","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.12213","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"arxiv_version","alias_value":"1905.12213v5","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.12213","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"pith_short_12","alias_value":"SFPLHD45DHXU","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"pith_short_16","alias_value":"SFPLHD45DHXU7X74","created_at":"2026-07-05T01:11:40Z"},{"alias_kind":"pith_short_8","alias_value":"SFPLHD45","created_at":"2026-07-05T01:11:40Z"}],"graph_snapshots":[{"event_id":"sha256:16beab308aaa229ed54358e5fd9939cc61bf7e64ea5ccf25af1e3fbdcd2008b7","target":"graph","created_at":"2026-07-05T01:11:40Z","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/1905.12213/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Whatever information a deep neural network has gleaned from training data is encoded in its weights. How this information affects the response of the network to future data remains largely an open question. Indeed, even defining and measuring information entails some subtleties, since a trained network is a deterministic map, so standard information measures can be degenerate. We measure information in a neural network via the optimal trade-off between accuracy of the response and complexity of the weights, measured by their coding length. Depending on the choice of code, the definition can re","authors_text":"Alessandro Achille, Giovanni Paolini, Stefano Soatto","cross_cats":["cs.AI","cs.IT","math.IT","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-29T04:38:54Z","title":"Where is the Information in a Deep Neural Network?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.12213","kind":"arxiv","version":5},"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":"sha256:5757e972f213bf07c5e4a77271ca6660e3d429ad6e2333000b14a5edfe37a5a0","target":"record","created_at":"2026-07-05T01:11:40Z","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":"bab00936f15520b186e1f4a1cf0648a0d977aef3993d85684b72b1c76a5abde8","cross_cats_sorted":["cs.AI","cs.IT","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-29T04:38:54Z","title_canon_sha256":"6a112d8ee3d055542241d569ffd55ffdd69bde118748551fb1df77b35cece04b"},"schema_version":"1.0","source":{"id":"1905.12213","kind":"arxiv","version":5}},"canonical_sha256":"915eb38f9d19ef4fdffc294d51e04dab7fa6bd22b9e004c028e2de4788414234","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"915eb38f9d19ef4fdffc294d51e04dab7fa6bd22b9e004c028e2de4788414234","first_computed_at":"2026-07-05T01:11:40.265738Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:11:40.265738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rOvBQ8mea8Jw2hX3HxnSKaZ/dwxDsG1T6tu2fGDnuOZz5tcany2r3r4OuNVhL0xnxIFD9+VL1EhxIfq5YB1cAA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:11:40.266212Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.12213","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5757e972f213bf07c5e4a77271ca6660e3d429ad6e2333000b14a5edfe37a5a0","sha256:16beab308aaa229ed54358e5fd9939cc61bf7e64ea5ccf25af1e3fbdcd2008b7"],"state_sha256":"46c6d141b2cb86aa583682160c6dc81105a8412ec30c02115c5b29c0d13c6165"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+ksOdxwPFWofSWg59GKU3hI1OBVRA42AIcUKVGtZw/zm2vT6dn3OcVmI7fJeuwFI8nmFk7qHUNfI83su8GjrCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T14:21:07.158834Z","bundle_sha256":"6109249862633fa0890afc7ec4ca528e521711d12c47e26b5297fa6e6c86a1e7"}}