{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WRQINHTQJSBFK2QZ7NDBYVLAZX","short_pith_number":"pith:WRQINHTQ","canonical_record":{"source":{"id":"2604.12254","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-04-14T04:01:34Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c2e115dbdf0834b2c5db3dc7e4c6d2d63f85a3fcf3c1cf1d5034dea866930118","abstract_canon_sha256":"f501051a18f26d8c65a0b78929e5b204998bee6b6bb6bf11e749990433694ffc"},"schema_version":"1.0"},"canonical_sha256":"b460869e704c82556a19fb461c5560cdde6091c939444c956a43667f0cc2cb3b","source":{"kind":"arxiv","id":"2604.12254","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.12254","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"arxiv_version","alias_value":"2604.12254v2","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.12254","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"pith_short_12","alias_value":"WRQINHTQJSBF","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"pith_short_16","alias_value":"WRQINHTQJSBFK2QZ","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"pith_short_8","alias_value":"WRQINHTQ","created_at":"2026-05-20T00:03:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WRQINHTQJSBFK2QZ7NDBYVLAZX","target":"record","payload":{"canonical_record":{"source":{"id":"2604.12254","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-04-14T04:01:34Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c2e115dbdf0834b2c5db3dc7e4c6d2d63f85a3fcf3c1cf1d5034dea866930118","abstract_canon_sha256":"f501051a18f26d8c65a0b78929e5b204998bee6b6bb6bf11e749990433694ffc"},"schema_version":"1.0"},"canonical_sha256":"b460869e704c82556a19fb461c5560cdde6091c939444c956a43667f0cc2cb3b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:03:11.159018Z","signature_b64":"DATWux0eP+jo/ZROZ3e5WZlLkjiDuJ5EhqmG2dvoQ7wEABDqFz1er4RtyoQ2uN+K9osd105LLKIzb3PkYrePBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b460869e704c82556a19fb461c5560cdde6091c939444c956a43667f0cc2cb3b","last_reissued_at":"2026-05-20T00:03:11.158193Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:03:11.158193Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.12254","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:03:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lW1XbbIuuveRfGARL6C+CHl94uNmcAU2A+YTOW4DbtE3KbOZG2ngFTHVs8enrUDVarldV+Kwj3MgMUu8WeHqBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T22:49:23.686981Z"},"content_sha256":"0cb9feb038f7b4c9e88be045440978d7890ba87cdd72a6a5a9fa63ae8154c4c8","schema_version":"1.0","event_id":"sha256:0cb9feb038f7b4c9e88be045440978d7890ba87cdd72a6a5a9fa63ae8154c4c8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WRQINHTQJSBFK2QZ7NDBYVLAZX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SpanKey: Dynamic Key Space Conditioning for Neural Network Access Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"SpanKey gates neural network inference by conditioning activations on keys from a defined low-dimensional subspace.","cross_cats":["cs.AI"],"primary_cat":"cs.CR","authors_text":"WenBin Yan","submitted_at":"2026-04-14T04:01:34Z","abstract_excerpt":"SpanKey is a lightweight way to gate inference without encrypting weights or chasing leaderboard accuracy on gated inference. The idea is to condition activations on secret keys. A basis matrix $B$ defines a low-dimensional key subspace $Span(B)$; during training we sample coefficients $\\alpha$ and form keys $k=\\alpha^\\top B$, then inject them into intermediate activations with additive or multiplicative maps and strength $\\gamma$. Valid keys lie in $Span(B)$; invalid keys are sampled outside that subspace. We make three points. (i) Mechanism: subspace key injection and a multi-layer design sp"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Subspace key injection with multi-layer design, together with deny losses and margin-tail diagnostics, enables practical key-based gating of neural network inference, as demonstrated by CIFAR-10 ResNet-18 runs and MNIST ablations.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the network does not absorb the key signal into its weights in a way that collapses separation between valid and invalid keys at deployment scale, despite the analytical Beta-energy split and margin diagnostics provided.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"SpanKey injects keys from a learned subspace into network activations via additive or multiplicative maps to enable key-based access control for neural network inference.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"SpanKey gates neural network inference by conditioning activations on keys from a defined low-dimensional subspace.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"62f76804eabf2e507acf835b0c3ca516278b181c8ecc5b9be102a528ec5c21e7"},"source":{"id":"2604.12254","kind":"arxiv","version":2},"verdict":{"id":"1bb38d14-2076-4f4e-b1b0-c0babc128d08","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-10T15:54:32.601623Z","strongest_claim":"Subspace key injection with multi-layer design, together with deny losses and margin-tail diagnostics, enables practical key-based gating of neural network inference, as demonstrated by CIFAR-10 ResNet-18 runs and MNIST ablations.","one_line_summary":"SpanKey injects keys from a learned subspace into network activations via additive or multiplicative maps to enable key-based access control for neural network inference.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the network does not absorb the key signal into its weights in a way that collapses separation between valid and invalid keys at deployment scale, despite the analytical Beta-energy split and margin diagnostics provided.","pith_extraction_headline":"SpanKey gates neural network inference by conditioning activations on keys from a defined low-dimensional subspace."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.12254/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":"1bb38d14-2076-4f4e-b1b0-c0babc128d08"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:03:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rf+rhyGvLWAD0i+zb9RgzVL+hBR2K2PTdWKNInAPAj4sAs4TzAorjwvPiPjGvPAywwBrlKC1z2dB4AvWV07ICw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T22:49:23.687511Z"},"content_sha256":"d72587266325842594d3e3614696ea3708fdebecd11129fbff3146d9f9f84af9","schema_version":"1.0","event_id":"sha256:d72587266325842594d3e3614696ea3708fdebecd11129fbff3146d9f9f84af9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WRQINHTQJSBFK2QZ7NDBYVLAZX/bundle.json","state_url":"https://pith.science/pith/WRQINHTQJSBFK2QZ7NDBYVLAZX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WRQINHTQJSBFK2QZ7NDBYVLAZX/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":"2026-05-24T22:49:23Z","links":{"resolver":"https://pith.science/pith/WRQINHTQJSBFK2QZ7NDBYVLAZX","bundle":"https://pith.science/pith/WRQINHTQJSBFK2QZ7NDBYVLAZX/bundle.json","state":"https://pith.science/pith/WRQINHTQJSBFK2QZ7NDBYVLAZX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WRQINHTQJSBFK2QZ7NDBYVLAZX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WRQINHTQJSBFK2QZ7NDBYVLAZX","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":"f501051a18f26d8c65a0b78929e5b204998bee6b6bb6bf11e749990433694ffc","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-04-14T04:01:34Z","title_canon_sha256":"c2e115dbdf0834b2c5db3dc7e4c6d2d63f85a3fcf3c1cf1d5034dea866930118"},"schema_version":"1.0","source":{"id":"2604.12254","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.12254","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"arxiv_version","alias_value":"2604.12254v2","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.12254","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"pith_short_12","alias_value":"WRQINHTQJSBF","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"pith_short_16","alias_value":"WRQINHTQJSBFK2QZ","created_at":"2026-05-20T00:03:11Z"},{"alias_kind":"pith_short_8","alias_value":"WRQINHTQ","created_at":"2026-05-20T00:03:11Z"}],"graph_snapshots":[{"event_id":"sha256:d72587266325842594d3e3614696ea3708fdebecd11129fbff3146d9f9f84af9","target":"graph","created_at":"2026-05-20T00:03:11Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"Subspace key injection with multi-layer design, together with deny losses and margin-tail diagnostics, enables practical key-based gating of neural network inference, as demonstrated by CIFAR-10 ResNet-18 runs and MNIST ablations."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That the network does not absorb the key signal into its weights in a way that collapses separation between valid and invalid keys at deployment scale, despite the analytical Beta-energy split and margin diagnostics provided."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"SpanKey injects keys from a learned subspace into network activations via additive or multiplicative maps to enable key-based access control for neural network inference."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"SpanKey gates neural network inference by conditioning activations on keys from a defined low-dimensional subspace."}],"snapshot_sha256":"62f76804eabf2e507acf835b0c3ca516278b181c8ecc5b9be102a528ec5c21e7"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2604.12254/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"SpanKey is a lightweight way to gate inference without encrypting weights or chasing leaderboard accuracy on gated inference. The idea is to condition activations on secret keys. A basis matrix $B$ defines a low-dimensional key subspace $Span(B)$; during training we sample coefficients $\\alpha$ and form keys $k=\\alpha^\\top B$, then inject them into intermediate activations with additive or multiplicative maps and strength $\\gamma$. Valid keys lie in $Span(B)$; invalid keys are sampled outside that subspace. We make three points. (i) Mechanism: subspace key injection and a multi-layer design sp","authors_text":"WenBin Yan","cross_cats":["cs.AI"],"headline":"SpanKey gates neural network inference by conditioning activations on keys from a defined low-dimensional subspace.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-04-14T04:01:34Z","title":"SpanKey: Dynamic Key Space Conditioning for Neural Network Access Control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.12254","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-10T15:54:32.601623Z","id":"1bb38d14-2076-4f4e-b1b0-c0babc128d08","model_set":{"reader":"grok-4.3"},"one_line_summary":"SpanKey injects keys from a learned subspace into network activations via additive or multiplicative maps to enable key-based access control for neural network inference.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"SpanKey gates neural network inference by conditioning activations on keys from a defined low-dimensional subspace.","strongest_claim":"Subspace key injection with multi-layer design, together with deny losses and margin-tail diagnostics, enables practical key-based gating of neural network inference, as demonstrated by CIFAR-10 ResNet-18 runs and MNIST ablations.","weakest_assumption":"That the network does not absorb the key signal into its weights in a way that collapses separation between valid and invalid keys at deployment scale, despite the analytical Beta-energy split and margin diagnostics provided."}},"verdict_id":"1bb38d14-2076-4f4e-b1b0-c0babc128d08"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0cb9feb038f7b4c9e88be045440978d7890ba87cdd72a6a5a9fa63ae8154c4c8","target":"record","created_at":"2026-05-20T00:03:11Z","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":"f501051a18f26d8c65a0b78929e5b204998bee6b6bb6bf11e749990433694ffc","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-04-14T04:01:34Z","title_canon_sha256":"c2e115dbdf0834b2c5db3dc7e4c6d2d63f85a3fcf3c1cf1d5034dea866930118"},"schema_version":"1.0","source":{"id":"2604.12254","kind":"arxiv","version":2}},"canonical_sha256":"b460869e704c82556a19fb461c5560cdde6091c939444c956a43667f0cc2cb3b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b460869e704c82556a19fb461c5560cdde6091c939444c956a43667f0cc2cb3b","first_computed_at":"2026-05-20T00:03:11.158193Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:03:11.158193Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DATWux0eP+jo/ZROZ3e5WZlLkjiDuJ5EhqmG2dvoQ7wEABDqFz1er4RtyoQ2uN+K9osd105LLKIzb3PkYrePBg==","signature_status":"signed_v1","signed_at":"2026-05-20T00:03:11.159018Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.12254","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0cb9feb038f7b4c9e88be045440978d7890ba87cdd72a6a5a9fa63ae8154c4c8","sha256:d72587266325842594d3e3614696ea3708fdebecd11129fbff3146d9f9f84af9"],"state_sha256":"9cdf4a5e4129e4758b084d3466682e9c57a4bffcb68dea85997f3fe05941e635"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G2VmQUBCLDsOaeLveLxoTkh/hfJyhL3k28sZl3e7CKZFa5O0d9bY24+mgd7dy6waO9OzFK3v9E2inAwRDghzDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-24T22:49:23.691029Z","bundle_sha256":"b70497ffe3cee1931189787b6fcaf1cc43e48e61d98bf11442a3881e514c0ed7"}}