{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:2TQLXBPAWVEURXQM5PW2UUTDT5","short_pith_number":"pith:2TQLXBPA","canonical_record":{"source":{"id":"2004.10610","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-22T14:48:03Z","cross_cats_sorted":[],"title_canon_sha256":"b79a9dc2a298dea24dfd99bf2e9f1ea7a18bab6998ac4016ea41d75078deb20c","abstract_canon_sha256":"b5afe950416ed3fe5cea6033ce892d60c4fcdfa7c71421800f9c230b450061f5"},"schema_version":"1.0"},"canonical_sha256":"d4e0bb85e0b54948de0cebedaa52639f66444b5f2352f193dbf7623a14fe0ea0","source":{"kind":"arxiv","id":"2004.10610","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.10610","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"arxiv_version","alias_value":"2004.10610v1","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.10610","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"pith_short_12","alias_value":"2TQLXBPAWVEU","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"pith_short_16","alias_value":"2TQLXBPAWVEURXQM","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"pith_short_8","alias_value":"2TQLXBPA","created_at":"2026-07-05T00:57:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:2TQLXBPAWVEURXQM5PW2UUTDT5","target":"record","payload":{"canonical_record":{"source":{"id":"2004.10610","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-22T14:48:03Z","cross_cats_sorted":[],"title_canon_sha256":"b79a9dc2a298dea24dfd99bf2e9f1ea7a18bab6998ac4016ea41d75078deb20c","abstract_canon_sha256":"b5afe950416ed3fe5cea6033ce892d60c4fcdfa7c71421800f9c230b450061f5"},"schema_version":"1.0"},"canonical_sha256":"d4e0bb85e0b54948de0cebedaa52639f66444b5f2352f193dbf7623a14fe0ea0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:57:30.633566Z","signature_b64":"e0h7f70kjztHGF/RBz3RNZt//Hi937xxKdeY38MyLLv15pHWc3+nFJlFxlJkZsTbywY7VZJp0RyLWYKIdBVWCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d4e0bb85e0b54948de0cebedaa52639f66444b5f2352f193dbf7623a14fe0ea0","last_reissued_at":"2026-07-05T00:57:30.633208Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:57:30.633208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.10610","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":"2026-07-05T00:57:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F0qf0dMUgde2Un2EB3Rlf1XFdwdB/atJ+qmTJ/kv5vpi5q0HFrLwamLUPIz6l6r7voz/FbXFINLvKjaR7WFKAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T10:13:59.812179Z"},"content_sha256":"a86348fb28252cc6aca3f836fc34c6cc044ec4cc42f8bebbec9c86792a473628","schema_version":"1.0","event_id":"sha256:a86348fb28252cc6aca3f836fc34c6cc044ec4cc42f8bebbec9c86792a473628"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:2TQLXBPAWVEURXQM5PW2UUTDT5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"R-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Alexander Fabbri, Dragomir Radev, Irene Li, Swapnil Hingmire","submitted_at":"2020-04-22T14:48:03Z","abstract_excerpt":"The task of concept prerequisite chain learning is to automatically determine the existence of prerequisite relationships among concept pairs. In this paper, we frame learning prerequisite relationships among concepts as an unsupervised task with no access to labeled concept pairs during training. We propose a model called the Relational-Variational Graph AutoEncoder (R-VGAE) to predict concept relations within a graph consisting of concept and resource nodes. Results show that our unsupervised approach outperforms graph-based semi-supervised methods and other baseline methods by up to 9.77% a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.10610","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2004.10610/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":"2026-07-05T00:57:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3Y9t7JRMwVNDnpmDiNOJOf3NfFJLm9GZl9+h6jbIUi9hAKx5JRrp2cjQoue0Jznv+AXawAAM2z5zKdqDIY5nDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T10:13:59.812816Z"},"content_sha256":"f0cf561253d1d9541adc1e4be79a786daf9d1523fbb89cca79d7fbcd43b3818b","schema_version":"1.0","event_id":"sha256:f0cf561253d1d9541adc1e4be79a786daf9d1523fbb89cca79d7fbcd43b3818b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2TQLXBPAWVEURXQM5PW2UUTDT5/bundle.json","state_url":"https://pith.science/pith/2TQLXBPAWVEURXQM5PW2UUTDT5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2TQLXBPAWVEURXQM5PW2UUTDT5/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":"2026-08-13T10:13:59Z","links":{"resolver":"https://pith.science/pith/2TQLXBPAWVEURXQM5PW2UUTDT5","bundle":"https://pith.science/pith/2TQLXBPAWVEURXQM5PW2UUTDT5/bundle.json","state":"https://pith.science/pith/2TQLXBPAWVEURXQM5PW2UUTDT5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2TQLXBPAWVEURXQM5PW2UUTDT5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:2TQLXBPAWVEURXQM5PW2UUTDT5","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":"b5afe950416ed3fe5cea6033ce892d60c4fcdfa7c71421800f9c230b450061f5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-22T14:48:03Z","title_canon_sha256":"b79a9dc2a298dea24dfd99bf2e9f1ea7a18bab6998ac4016ea41d75078deb20c"},"schema_version":"1.0","source":{"id":"2004.10610","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.10610","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"arxiv_version","alias_value":"2004.10610v1","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.10610","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"pith_short_12","alias_value":"2TQLXBPAWVEU","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"pith_short_16","alias_value":"2TQLXBPAWVEURXQM","created_at":"2026-07-05T00:57:30Z"},{"alias_kind":"pith_short_8","alias_value":"2TQLXBPA","created_at":"2026-07-05T00:57:30Z"}],"graph_snapshots":[{"event_id":"sha256:f0cf561253d1d9541adc1e4be79a786daf9d1523fbb89cca79d7fbcd43b3818b","target":"graph","created_at":"2026-07-05T00:57:30Z","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/2004.10610/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The task of concept prerequisite chain learning is to automatically determine the existence of prerequisite relationships among concept pairs. In this paper, we frame learning prerequisite relationships among concepts as an unsupervised task with no access to labeled concept pairs during training. We propose a model called the Relational-Variational Graph AutoEncoder (R-VGAE) to predict concept relations within a graph consisting of concept and resource nodes. Results show that our unsupervised approach outperforms graph-based semi-supervised methods and other baseline methods by up to 9.77% a","authors_text":"Alexander Fabbri, Dragomir Radev, Irene Li, Swapnil Hingmire","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-22T14:48:03Z","title":"R-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.10610","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:a86348fb28252cc6aca3f836fc34c6cc044ec4cc42f8bebbec9c86792a473628","target":"record","created_at":"2026-07-05T00:57:30Z","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":"b5afe950416ed3fe5cea6033ce892d60c4fcdfa7c71421800f9c230b450061f5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-04-22T14:48:03Z","title_canon_sha256":"b79a9dc2a298dea24dfd99bf2e9f1ea7a18bab6998ac4016ea41d75078deb20c"},"schema_version":"1.0","source":{"id":"2004.10610","kind":"arxiv","version":1}},"canonical_sha256":"d4e0bb85e0b54948de0cebedaa52639f66444b5f2352f193dbf7623a14fe0ea0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d4e0bb85e0b54948de0cebedaa52639f66444b5f2352f193dbf7623a14fe0ea0","first_computed_at":"2026-07-05T00:57:30.633208Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:57:30.633208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e0h7f70kjztHGF/RBz3RNZt//Hi937xxKdeY38MyLLv15pHWc3+nFJlFxlJkZsTbywY7VZJp0RyLWYKIdBVWCw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:57:30.633566Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.10610","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a86348fb28252cc6aca3f836fc34c6cc044ec4cc42f8bebbec9c86792a473628","sha256:f0cf561253d1d9541adc1e4be79a786daf9d1523fbb89cca79d7fbcd43b3818b"],"state_sha256":"ed6fb1b2442c90af5dbfeca0ec2d815aed760f147348720c5162515ba157ac77"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MvjGUZexRWs7o7PRXGBSrW82mHQkHXRl9MMkiNJSIfKjkkUrIZ6IaHt5VcHqVvPRxHRoZo3LjIOg1CVHlOQqCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T10:13:59.817011Z","bundle_sha256":"e75a1fced64c50d184540f04179230701c80195764c50977c222c8bbd9da927d"}}