{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:JZ5HCZF2QZHFXETMAXKGPJTRUJ","short_pith_number":"pith:JZ5HCZF2","schema_version":"1.0","canonical_sha256":"4e7a7164ba864e5b926c05d467a671a265703dd19c49eeaf434e2ea25b016b17","source":{"kind":"arxiv","id":"2305.17219","version":1},"attestation_state":"computed","paper":{"title":"GVdoc: Graph-based Visual Document Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Ashish Verma, Catherine Finegan-Dollak, Fnu Mohbat, Mohammed J. Zaki","submitted_at":"2023-05-26T19:23:20Z","abstract_excerpt":"The robustness of a model for real-world deployment is decided by how well it performs on unseen data and distinguishes between in-domain and out-of-domain samples. Visual document classifiers have shown impressive performance on in-distribution test sets. However, they tend to have a hard time correctly classifying and differentiating out-of-distribution examples. Image-based classifiers lack the text component, whereas multi-modality transformer-based models face the token serialization problem in visual documents due to their diverse layouts. They also require a lot of computing power durin"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2305.17219","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-26T19:23:20Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"d05813095c5ca28be82ac89298648d85aed378da388f68e945aaafa97d014744","abstract_canon_sha256":"1f30aa191fa3872c261eaded5b29a08adfc1bea5b67394ba8e00e5f967bb4c38"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:14:25.328837Z","signature_b64":"ZtuuuT9jjCgSeoBuGoetbCbC1Bpr1ywLii3mf1p3zCkg+MyfRBI1fIqCqpDT4NXGzOJsWQJ3S4DLjZdW7RcKAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e7a7164ba864e5b926c05d467a671a265703dd19c49eeaf434e2ea25b016b17","last_reissued_at":"2026-07-05T06:14:25.328405Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:14:25.328405Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GVdoc: Graph-based Visual Document Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Ashish Verma, Catherine Finegan-Dollak, Fnu Mohbat, Mohammed J. Zaki","submitted_at":"2023-05-26T19:23:20Z","abstract_excerpt":"The robustness of a model for real-world deployment is decided by how well it performs on unseen data and distinguishes between in-domain and out-of-domain samples. Visual document classifiers have shown impressive performance on in-distribution test sets. However, they tend to have a hard time correctly classifying and differentiating out-of-distribution examples. Image-based classifiers lack the text component, whereas multi-modality transformer-based models face the token serialization problem in visual documents due to their diverse layouts. They also require a lot of computing power durin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.17219","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/2305.17219/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2305.17219","created_at":"2026-07-05T06:14:25.328463+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.17219v1","created_at":"2026-07-05T06:14:25.328463+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.17219","created_at":"2026-07-05T06:14:25.328463+00:00"},{"alias_kind":"pith_short_12","alias_value":"JZ5HCZF2QZHF","created_at":"2026-07-05T06:14:25.328463+00:00"},{"alias_kind":"pith_short_16","alias_value":"JZ5HCZF2QZHFXETM","created_at":"2026-07-05T06:14:25.328463+00:00"},{"alias_kind":"pith_short_8","alias_value":"JZ5HCZF2","created_at":"2026-07-05T06:14:25.328463+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ","json":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ.json","graph_json":"https://pith.science/api/pith-number/JZ5HCZF2QZHFXETMAXKGPJTRUJ/graph.json","events_json":"https://pith.science/api/pith-number/JZ5HCZF2QZHFXETMAXKGPJTRUJ/events.json","paper":"https://pith.science/paper/JZ5HCZF2"},"agent_actions":{"view_html":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ","download_json":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ.json","view_paper":"https://pith.science/paper/JZ5HCZF2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.17219&json=true","fetch_graph":"https://pith.science/api/pith-number/JZ5HCZF2QZHFXETMAXKGPJTRUJ/graph.json","fetch_events":"https://pith.science/api/pith-number/JZ5HCZF2QZHFXETMAXKGPJTRUJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ/action/storage_attestation","attest_author":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ/action/author_attestation","sign_citation":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ/action/citation_signature","submit_replication":"https://pith.science/pith/JZ5HCZF2QZHFXETMAXKGPJTRUJ/action/replication_record"}},"created_at":"2026-07-05T06:14:25.328463+00:00","updated_at":"2026-07-05T06:14:25.328463+00:00"}