{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:Y6SI25K3L6ZLGW6ZNUHLVB25AV","short_pith_number":"pith:Y6SI25K3","canonical_record":{"source":{"id":"1805.09786","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-05-24T17:11:35Z","cross_cats_sorted":[],"title_canon_sha256":"2cbf6fe5e31a6e0969a69d6e1e5c22c01cde5da540ae549916c3779bcc828536","abstract_canon_sha256":"6e8a7e501a1f1c7c15b1585f3119bc979969bcbb778bb01ef8d613a565e0b0c9"},"schema_version":"1.0"},"canonical_sha256":"c7a48d755b5fb2b35bd96d0eba875d057171af22da1f19fd67c6b36bf24d7e53","source":{"kind":"arxiv","id":"1805.09786","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.09786","created_at":"2026-05-18T00:15:02Z"},{"alias_kind":"arxiv_version","alias_value":"1805.09786v1","created_at":"2026-05-18T00:15:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.09786","created_at":"2026-05-18T00:15:02Z"},{"alias_kind":"pith_short_12","alias_value":"Y6SI25K3L6ZL","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"Y6SI25K3L6ZLGW6Z","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"Y6SI25K3","created_at":"2026-05-18T12:33:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:Y6SI25K3L6ZLGW6ZNUHLVB25AV","target":"record","payload":{"canonical_record":{"source":{"id":"1805.09786","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-05-24T17:11:35Z","cross_cats_sorted":[],"title_canon_sha256":"2cbf6fe5e31a6e0969a69d6e1e5c22c01cde5da540ae549916c3779bcc828536","abstract_canon_sha256":"6e8a7e501a1f1c7c15b1585f3119bc979969bcbb778bb01ef8d613a565e0b0c9"},"schema_version":"1.0"},"canonical_sha256":"c7a48d755b5fb2b35bd96d0eba875d057171af22da1f19fd67c6b36bf24d7e53","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:02.857624Z","signature_b64":"wdnkUrSVDko/MTyeKjAowSPWk+XSZ3FAG+ieY7X5fNHKEh9Y1BDzAhESo9TDy190kykGDidaJD6I1i6W/PY4CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c7a48d755b5fb2b35bd96d0eba875d057171af22da1f19fd67c6b36bf24d7e53","last_reissued_at":"2026-05-18T00:15:02.856900Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:02.856900Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.09786","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":"2026-05-18T00:15:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bo6xROnXH5XFGThxNeBOxAT9l0JooB+6Sr9e4PonJ+bGbpwSqskS9n22cgn17KMXgBaDu2WWhDMfIIZvIAWEBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T00:09:02.296343Z"},"content_sha256":"aee66ad0d5474c08b4b4d4dd7668aef64edac3dde31ddea25b69d0871ace641d","schema_version":"1.0","event_id":"sha256:aee66ad0d5474c08b4b4d4dd7668aef64edac3dde31ddea25b69d0871ace641d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:Y6SI25K3L6ZLGW6ZNUHLVB25AV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hyperbolic Attention Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Adam Santoro, Ali Razavi, Caglar Gulcehre, David Raposo, Karl Moritz Hermann, Mateusz Malinowski, Misha Denil, Nando de Freitas, Peter Battaglia, Razvan Pascanu, Victor Bapst","submitted_at":"2018-05-24T17:11:35Z","abstract_excerpt":"We introduce hyperbolic attention networks to endow neural networks with enough capacity to match the complexity of data with hierarchical and power-law structure. A few recent approaches have successfully demonstrated the benefits of imposing hyperbolic geometry on the parameters of shallow networks. We extend this line of work by imposing hyperbolic geometry on the activations of neural networks. This allows us to exploit hyperbolic geometry to reason about embeddings produced by deep networks. We achieve this by re-expressing the ubiquitous mechanism of soft attention in terms of operations"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.09786","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":"2026-05-18T00:15:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MMDpFxVuf0YTFpikBLVK2F0KrtBGktHLpjxmJr6oi0wf7rIpx9tSc+VpuNnwIcCIjJDVod9iIxVaBFikqFk+BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T00:09:02.297053Z"},"content_sha256":"a95094c0137f6899afdd9dd34f4d15825d3a23e51a8344b290f20083096ca82c","schema_version":"1.0","event_id":"sha256:a95094c0137f6899afdd9dd34f4d15825d3a23e51a8344b290f20083096ca82c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y6SI25K3L6ZLGW6ZNUHLVB25AV/bundle.json","state_url":"https://pith.science/pith/Y6SI25K3L6ZLGW6ZNUHLVB25AV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y6SI25K3L6ZLGW6ZNUHLVB25AV/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":"2026-06-07T00:09:02Z","links":{"resolver":"https://pith.science/pith/Y6SI25K3L6ZLGW6ZNUHLVB25AV","bundle":"https://pith.science/pith/Y6SI25K3L6ZLGW6ZNUHLVB25AV/bundle.json","state":"https://pith.science/pith/Y6SI25K3L6ZLGW6ZNUHLVB25AV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y6SI25K3L6ZLGW6ZNUHLVB25AV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:Y6SI25K3L6ZLGW6ZNUHLVB25AV","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":"6e8a7e501a1f1c7c15b1585f3119bc979969bcbb778bb01ef8d613a565e0b0c9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-05-24T17:11:35Z","title_canon_sha256":"2cbf6fe5e31a6e0969a69d6e1e5c22c01cde5da540ae549916c3779bcc828536"},"schema_version":"1.0","source":{"id":"1805.09786","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.09786","created_at":"2026-05-18T00:15:02Z"},{"alias_kind":"arxiv_version","alias_value":"1805.09786v1","created_at":"2026-05-18T00:15:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.09786","created_at":"2026-05-18T00:15:02Z"},{"alias_kind":"pith_short_12","alias_value":"Y6SI25K3L6ZL","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"Y6SI25K3L6ZLGW6Z","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"Y6SI25K3","created_at":"2026-05-18T12:33:04Z"}],"graph_snapshots":[{"event_id":"sha256:a95094c0137f6899afdd9dd34f4d15825d3a23e51a8344b290f20083096ca82c","target":"graph","created_at":"2026-05-18T00:15:02Z","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":"We introduce hyperbolic attention networks to endow neural networks with enough capacity to match the complexity of data with hierarchical and power-law structure. A few recent approaches have successfully demonstrated the benefits of imposing hyperbolic geometry on the parameters of shallow networks. We extend this line of work by imposing hyperbolic geometry on the activations of neural networks. This allows us to exploit hyperbolic geometry to reason about embeddings produced by deep networks. We achieve this by re-expressing the ubiquitous mechanism of soft attention in terms of operations","authors_text":"Adam Santoro, Ali Razavi, Caglar Gulcehre, David Raposo, Karl Moritz Hermann, Mateusz Malinowski, Misha Denil, Nando de Freitas, Peter Battaglia, Razvan Pascanu, Victor Bapst","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-05-24T17:11:35Z","title":"Hyperbolic Attention Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.09786","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:aee66ad0d5474c08b4b4d4dd7668aef64edac3dde31ddea25b69d0871ace641d","target":"record","created_at":"2026-05-18T00:15:02Z","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":"6e8a7e501a1f1c7c15b1585f3119bc979969bcbb778bb01ef8d613a565e0b0c9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-05-24T17:11:35Z","title_canon_sha256":"2cbf6fe5e31a6e0969a69d6e1e5c22c01cde5da540ae549916c3779bcc828536"},"schema_version":"1.0","source":{"id":"1805.09786","kind":"arxiv","version":1}},"canonical_sha256":"c7a48d755b5fb2b35bd96d0eba875d057171af22da1f19fd67c6b36bf24d7e53","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c7a48d755b5fb2b35bd96d0eba875d057171af22da1f19fd67c6b36bf24d7e53","first_computed_at":"2026-05-18T00:15:02.856900Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:02.856900Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wdnkUrSVDko/MTyeKjAowSPWk+XSZ3FAG+ieY7X5fNHKEh9Y1BDzAhESo9TDy190kykGDidaJD6I1i6W/PY4CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:02.857624Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.09786","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aee66ad0d5474c08b4b4d4dd7668aef64edac3dde31ddea25b69d0871ace641d","sha256:a95094c0137f6899afdd9dd34f4d15825d3a23e51a8344b290f20083096ca82c"],"state_sha256":"3cb0b6781ad7ce4d645764e367b0219d247965f83a820949018285c5848a1f9b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z+FKM+LZYfRk/Od8gIPeE/WnNqMcH2njrRdbDkv7iqgkLrxTU3sAtJPLzvXAhFDESuMjJfy2kHLHpkVcUvURCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T00:09:02.300742Z","bundle_sha256":"b35007e287a69149e732cac92d2699be81fe1c11b0886f5f5f4d19fd81572839"}}