{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:2WYFVELRDUOZX2XGKDSXZMNQUH","short_pith_number":"pith:2WYFVELR","canonical_record":{"source":{"id":"2003.05997","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-12T19:50:14Z","cross_cats_sorted":["eess.AS","stat.ML"],"title_canon_sha256":"65437cff0a2cda8057eb3d01c308993e2abbd57c95c8ff4f15e528d07b1a51a5","abstract_canon_sha256":"4fdc36c75d72d8a70e23ccfc6f02cff683438b913f5e2e143906df26a4aa318d"},"schema_version":"1.0"},"canonical_sha256":"d5b05a91711d1d9beae650e57cb1b0a1e652e82c5a11c9df7b4ef1dad61b75e4","source":{"kind":"arxiv","id":"2003.05997","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.05997","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"arxiv_version","alias_value":"2003.05997v5","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.05997","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"pith_short_12","alias_value":"2WYFVELRDUOZ","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"pith_short_16","alias_value":"2WYFVELRDUOZX2XG","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"pith_short_8","alias_value":"2WYFVELR","created_at":"2026-07-05T01:45:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:2WYFVELRDUOZX2XGKDSXZMNQUH","target":"record","payload":{"canonical_record":{"source":{"id":"2003.05997","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-12T19:50:14Z","cross_cats_sorted":["eess.AS","stat.ML"],"title_canon_sha256":"65437cff0a2cda8057eb3d01c308993e2abbd57c95c8ff4f15e528d07b1a51a5","abstract_canon_sha256":"4fdc36c75d72d8a70e23ccfc6f02cff683438b913f5e2e143906df26a4aa318d"},"schema_version":"1.0"},"canonical_sha256":"d5b05a91711d1d9beae650e57cb1b0a1e652e82c5a11c9df7b4ef1dad61b75e4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:45:41.999455Z","signature_b64":"vZGEOVE59hZ5YtYmJbyGum1ITyUjyQZi3faTQyCp5F+6M70Dr9I1M0KD4M9mdeetpjT424E+aMD2oTLT/dNDBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5b05a91711d1d9beae650e57cb1b0a1e652e82c5a11c9df7b4ef1dad61b75e4","last_reissued_at":"2026-07-05T01:45:41.998969Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:45:41.998969Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2003.05997","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":"2026-07-05T01:45:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0JSBiyvz14f8bC8jcRx7UdFPgsY8Er94bStQXtZcr3zK3k/hslhG5cWNs3cVH7sKSJfWwhCNDd2PqFII++JhAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:05:44.068655Z"},"content_sha256":"5ecef20ac416bf6d0cf04c244778c8ff858fd0ea4fff0ed92fadb5a76d0bfb42","schema_version":"1.0","event_id":"sha256:5ecef20ac416bf6d0cf04c244778c8ff858fd0ea4fff0ed92fadb5a76d0bfb42"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:2WYFVELRDUOZX2XGKDSXZMNQUH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Content-Based Sparse Attention with Routing Transformers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS","stat.ML"],"primary_cat":"cs.LG","authors_text":"Ashish Vaswani, Aurko Roy, David Grangier, Mohammad Saffar","submitted_at":"2020-03-12T19:50:14Z","abstract_excerpt":"Self-attention has recently been adopted for a wide range of sequence modeling problems. Despite its effectiveness, self-attention suffers from quadratic compute and memory requirements with respect to sequence length. Successful approaches to reduce this complexity focused on attending to local sliding windows or a small set of locations independent of content. Our work proposes to learn dynamic sparse attention patterns that avoid allocating computation and memory to attend to content unrelated to the query of interest. This work builds upon two lines of research: it combines the modeling fl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.05997","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/2003.05997/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":"2026-07-05T01:45:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"++X/9rl25UfqiGobBkH1qc7WB2SKTU5N5g6QehhfNAHhxlSvO9zw5JpxsnFtx0zakdHuUeHPx7xdRKYLolXiDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:05:44.069065Z"},"content_sha256":"90e16e42af9be29f8281632af739a30b38b3e24870b1eeb99e128a6aa646655d","schema_version":"1.0","event_id":"sha256:90e16e42af9be29f8281632af739a30b38b3e24870b1eeb99e128a6aa646655d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2WYFVELRDUOZX2XGKDSXZMNQUH/bundle.json","state_url":"https://pith.science/pith/2WYFVELRDUOZX2XGKDSXZMNQUH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2WYFVELRDUOZX2XGKDSXZMNQUH/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":"2026-08-04T10:05:44Z","links":{"resolver":"https://pith.science/pith/2WYFVELRDUOZX2XGKDSXZMNQUH","bundle":"https://pith.science/pith/2WYFVELRDUOZX2XGKDSXZMNQUH/bundle.json","state":"https://pith.science/pith/2WYFVELRDUOZX2XGKDSXZMNQUH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2WYFVELRDUOZX2XGKDSXZMNQUH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:2WYFVELRDUOZX2XGKDSXZMNQUH","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":"4fdc36c75d72d8a70e23ccfc6f02cff683438b913f5e2e143906df26a4aa318d","cross_cats_sorted":["eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-12T19:50:14Z","title_canon_sha256":"65437cff0a2cda8057eb3d01c308993e2abbd57c95c8ff4f15e528d07b1a51a5"},"schema_version":"1.0","source":{"id":"2003.05997","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.05997","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"arxiv_version","alias_value":"2003.05997v5","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.05997","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"pith_short_12","alias_value":"2WYFVELRDUOZ","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"pith_short_16","alias_value":"2WYFVELRDUOZX2XG","created_at":"2026-07-05T01:45:41Z"},{"alias_kind":"pith_short_8","alias_value":"2WYFVELR","created_at":"2026-07-05T01:45:41Z"}],"graph_snapshots":[{"event_id":"sha256:90e16e42af9be29f8281632af739a30b38b3e24870b1eeb99e128a6aa646655d","target":"graph","created_at":"2026-07-05T01:45:41Z","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/2003.05997/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Self-attention has recently been adopted for a wide range of sequence modeling problems. Despite its effectiveness, self-attention suffers from quadratic compute and memory requirements with respect to sequence length. Successful approaches to reduce this complexity focused on attending to local sliding windows or a small set of locations independent of content. Our work proposes to learn dynamic sparse attention patterns that avoid allocating computation and memory to attend to content unrelated to the query of interest. This work builds upon two lines of research: it combines the modeling fl","authors_text":"Ashish Vaswani, Aurko Roy, David Grangier, Mohammad Saffar","cross_cats":["eess.AS","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-12T19:50:14Z","title":"Efficient Content-Based Sparse Attention with Routing Transformers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.05997","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":"sha256:5ecef20ac416bf6d0cf04c244778c8ff858fd0ea4fff0ed92fadb5a76d0bfb42","target":"record","created_at":"2026-07-05T01:45:41Z","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":"4fdc36c75d72d8a70e23ccfc6f02cff683438b913f5e2e143906df26a4aa318d","cross_cats_sorted":["eess.AS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-12T19:50:14Z","title_canon_sha256":"65437cff0a2cda8057eb3d01c308993e2abbd57c95c8ff4f15e528d07b1a51a5"},"schema_version":"1.0","source":{"id":"2003.05997","kind":"arxiv","version":5}},"canonical_sha256":"d5b05a91711d1d9beae650e57cb1b0a1e652e82c5a11c9df7b4ef1dad61b75e4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d5b05a91711d1d9beae650e57cb1b0a1e652e82c5a11c9df7b4ef1dad61b75e4","first_computed_at":"2026-07-05T01:45:41.998969Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:45:41.998969Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vZGEOVE59hZ5YtYmJbyGum1ITyUjyQZi3faTQyCp5F+6M70Dr9I1M0KD4M9mdeetpjT424E+aMD2oTLT/dNDBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:45:41.999455Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.05997","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5ecef20ac416bf6d0cf04c244778c8ff858fd0ea4fff0ed92fadb5a76d0bfb42","sha256:90e16e42af9be29f8281632af739a30b38b3e24870b1eeb99e128a6aa646655d"],"state_sha256":"72a5c8857db689e6c6c35b28ccfa2e13780348bf87c1cc46a4d5a86f367e5bc3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qw1o4GEr6OqlfpKXIruVA36v/ZKlx2t3RQK0qOYQpIVkjy2x0EtH4mQpyR0AhDryGc/qwgjux5M8AwQ5SWvfDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T10:05:44.072337Z","bundle_sha256":"d52a61b652bf93d7d80b18f9b0a677f43d43c5bc6fdb2e96d46920ee6211a0d0"}}