{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:KU5G6KYSHHTUGEN7VR7I2O3XUZ","short_pith_number":"pith:KU5G6KYS","canonical_record":{"source":{"id":"1810.02114","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-04T09:20:32Z","cross_cats_sorted":[],"title_canon_sha256":"862c5121122d0025182d4845ffdfcbcab42dca9c971599b331020d3801e1a2ee","abstract_canon_sha256":"99ad4a140bf5c9250f0741a237116443d1c1d82690bdb9c17c200af6426cf9be"},"schema_version":"1.0"},"canonical_sha256":"553a6f2b1239e74311bfac7e8d3b77a6721dabdd7a7cfd7a1f7f2752df428afa","source":{"kind":"arxiv","id":"1810.02114","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.02114","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.02114v1","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02114","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"KU5G6KYSHHTU","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KU5G6KYSHHTUGEN7","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KU5G6KYS","created_at":"2026-05-18T12:32:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:KU5G6KYSHHTUGEN7VR7I2O3XUZ","target":"record","payload":{"canonical_record":{"source":{"id":"1810.02114","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-04T09:20:32Z","cross_cats_sorted":[],"title_canon_sha256":"862c5121122d0025182d4845ffdfcbcab42dca9c971599b331020d3801e1a2ee","abstract_canon_sha256":"99ad4a140bf5c9250f0741a237116443d1c1d82690bdb9c17c200af6426cf9be"},"schema_version":"1.0"},"canonical_sha256":"553a6f2b1239e74311bfac7e8d3b77a6721dabdd7a7cfd7a1f7f2752df428afa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:06.211927Z","signature_b64":"CY4gEB4M0hhNIYnTBpNZ3cMGQNi4EtSohQV9K7YoaMUtNhyYLUP0uGcOV88xQ4RWMXxzjhAlKt+m9ZiIcpYgCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"553a6f2b1239e74311bfac7e8d3b77a6721dabdd7a7cfd7a1f7f2752df428afa","last_reissued_at":"2026-05-18T00:04:06.211257Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:06.211257Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.02114","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":"2026-05-18T00:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7e2R82IChiocQ5GhBMsht03EJPLblWxgjSiRRemEkOlxH1hXK+ydUYKqx8r4Cy7EPF7eCklh4lsv7D/l1HPPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T08:07:00.008524Z"},"content_sha256":"f523b9b04d3acf01064153dda5ace0635838291c682a8bb18283bc99fc5d5284","schema_version":"1.0","event_id":"sha256:f523b9b04d3acf01064153dda5ace0635838291c682a8bb18283bc99fc5d5284"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:KU5G6KYSHHTUGEN7VR7I2O3XUZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Zooming Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Daqi Zheng, Sen Song, Yukun Yan, Zhengdong Lu","submitted_at":"2018-10-04T09:20:32Z","abstract_excerpt":"Structural information is important in natural language understanding. Although some current neural net-based models have a limited ability to take local syntactic information, they fail to use high-level and large-scale structures of documents. This information is valuable for text understanding since it contains the author's strategy to express information, in building an effective representation and forming appropriate output modes. We propose a neural net-based model, Zooming Network, capable of representing and leveraging text structure of long document and developing its own analyzing rh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02114","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":"2026-05-18T00:04:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0XRRZGjLNaW8VpviDIQpWo6EV9K/cK9Dnl+qFi4F9YYETVa64O1NDxKzdjmOqtnM0z5I0Gs2ZfE1/l6CPhMcDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T08:07:00.009067Z"},"content_sha256":"2bc06a25699ba4b6694709be985fc71b0d6c801d8106393b16690dc2153b1350","schema_version":"1.0","event_id":"sha256:2bc06a25699ba4b6694709be985fc71b0d6c801d8106393b16690dc2153b1350"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KU5G6KYSHHTUGEN7VR7I2O3XUZ/bundle.json","state_url":"https://pith.science/pith/KU5G6KYSHHTUGEN7VR7I2O3XUZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KU5G6KYSHHTUGEN7VR7I2O3XUZ/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":"2026-06-07T08:07:00Z","links":{"resolver":"https://pith.science/pith/KU5G6KYSHHTUGEN7VR7I2O3XUZ","bundle":"https://pith.science/pith/KU5G6KYSHHTUGEN7VR7I2O3XUZ/bundle.json","state":"https://pith.science/pith/KU5G6KYSHHTUGEN7VR7I2O3XUZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KU5G6KYSHHTUGEN7VR7I2O3XUZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:KU5G6KYSHHTUGEN7VR7I2O3XUZ","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":"99ad4a140bf5c9250f0741a237116443d1c1d82690bdb9c17c200af6426cf9be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-04T09:20:32Z","title_canon_sha256":"862c5121122d0025182d4845ffdfcbcab42dca9c971599b331020d3801e1a2ee"},"schema_version":"1.0","source":{"id":"1810.02114","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.02114","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"arxiv_version","alias_value":"1810.02114v1","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02114","created_at":"2026-05-18T00:04:06Z"},{"alias_kind":"pith_short_12","alias_value":"KU5G6KYSHHTU","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KU5G6KYSHHTUGEN7","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KU5G6KYS","created_at":"2026-05-18T12:32:33Z"}],"graph_snapshots":[{"event_id":"sha256:2bc06a25699ba4b6694709be985fc71b0d6c801d8106393b16690dc2153b1350","target":"graph","created_at":"2026-05-18T00:04:06Z","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":"Structural information is important in natural language understanding. Although some current neural net-based models have a limited ability to take local syntactic information, they fail to use high-level and large-scale structures of documents. This information is valuable for text understanding since it contains the author's strategy to express information, in building an effective representation and forming appropriate output modes. We propose a neural net-based model, Zooming Network, capable of representing and leveraging text structure of long document and developing its own analyzing rh","authors_text":"Daqi Zheng, Sen Song, Yukun Yan, Zhengdong Lu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-04T09:20:32Z","title":"Zooming Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02114","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:f523b9b04d3acf01064153dda5ace0635838291c682a8bb18283bc99fc5d5284","target":"record","created_at":"2026-05-18T00:04:06Z","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":"99ad4a140bf5c9250f0741a237116443d1c1d82690bdb9c17c200af6426cf9be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-10-04T09:20:32Z","title_canon_sha256":"862c5121122d0025182d4845ffdfcbcab42dca9c971599b331020d3801e1a2ee"},"schema_version":"1.0","source":{"id":"1810.02114","kind":"arxiv","version":1}},"canonical_sha256":"553a6f2b1239e74311bfac7e8d3b77a6721dabdd7a7cfd7a1f7f2752df428afa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"553a6f2b1239e74311bfac7e8d3b77a6721dabdd7a7cfd7a1f7f2752df428afa","first_computed_at":"2026-05-18T00:04:06.211257Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:04:06.211257Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CY4gEB4M0hhNIYnTBpNZ3cMGQNi4EtSohQV9K7YoaMUtNhyYLUP0uGcOV88xQ4RWMXxzjhAlKt+m9ZiIcpYgCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:04:06.211927Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.02114","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f523b9b04d3acf01064153dda5ace0635838291c682a8bb18283bc99fc5d5284","sha256:2bc06a25699ba4b6694709be985fc71b0d6c801d8106393b16690dc2153b1350"],"state_sha256":"f397d12241a3d6417dec5e28ec6b4308baff606c85dfee63208394a9a36806ab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/26VLf4W57wyBh0OItTQCmpj3GWzXB5+yWHbHVnnV8yE1T0wa0vvbXniBgcbwoUNI2zy9VmJt8gIrnOOdBnuAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T08:07:00.012074Z","bundle_sha256":"8911f54d4847087d526e27e6b1615648caa4a11b9edaac65db5beea068e96653"}}