{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:RT3IN45JNJEES2TNZ7ZFP2KNSQ","short_pith_number":"pith:RT3IN45J","schema_version":"1.0","canonical_sha256":"8cf686f3a96a48496a6dcff257e94d9418c7f9c0f61062450f67f79d7ea7ae4c","source":{"kind":"arxiv","id":"2103.01403","version":3},"attestation_state":"computed","paper":{"title":"A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Qing Li, Siyuan Huang, Song-Chun Zhu, Ying Nian Wu, Yining Hong, Yixin Zhu","submitted_at":"2021-03-02T01:32:54Z","abstract_excerpt":"Inspired by humans' exceptional ability to master arithmetic and generalize to new problems, we present a new dataset, Handwritten arithmetic with INTegers (HINT), to examine machines' capability of learning generalizable concepts at three levels: perception, syntax, and semantics. In HINT, machines are tasked with learning how concepts are perceived from raw signals such as images (i.e., perception), how multiple concepts are structurally combined to form a valid expression (i.e., syntax), and how concepts are realized to afford various reasoning tasks (i.e., semantics), all in a weakly super"},"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":"2103.01403","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-03-02T01:32:54Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"084c35fe581ec8a1d06e19877f9eda3e9ac4b8d64e11969a2cf6256302ab22d2","abstract_canon_sha256":"964116e15149405e37087ec43817130729fb6ee0e17aa69e055a0faeb4b61abc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:01:54.955242Z","signature_b64":"meXjOEfweDZBitm5q4s48D4YFLdxIEXbGTFLqlcyji037RArjGILkHQIMUM6ar8mCba5QXd5cLTEs6qYr8hAAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8cf686f3a96a48496a6dcff257e94d9418c7f9c0f61062450f67f79d7ea7ae4c","last_reissued_at":"2026-07-05T06:01:54.954784Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:01:54.954784Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Qing Li, Siyuan Huang, Song-Chun Zhu, Ying Nian Wu, Yining Hong, Yixin Zhu","submitted_at":"2021-03-02T01:32:54Z","abstract_excerpt":"Inspired by humans' exceptional ability to master arithmetic and generalize to new problems, we present a new dataset, Handwritten arithmetic with INTegers (HINT), to examine machines' capability of learning generalizable concepts at three levels: perception, syntax, and semantics. In HINT, machines are tasked with learning how concepts are perceived from raw signals such as images (i.e., perception), how multiple concepts are structurally combined to form a valid expression (i.e., syntax), and how concepts are realized to afford various reasoning tasks (i.e., semantics), all in a weakly super"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.01403","kind":"arxiv","version":3},"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/2103.01403/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":"2103.01403","created_at":"2026-07-05T06:01:54.954841+00:00"},{"alias_kind":"arxiv_version","alias_value":"2103.01403v3","created_at":"2026-07-05T06:01:54.954841+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.01403","created_at":"2026-07-05T06:01:54.954841+00:00"},{"alias_kind":"pith_short_12","alias_value":"RT3IN45JNJEE","created_at":"2026-07-05T06:01:54.954841+00:00"},{"alias_kind":"pith_short_16","alias_value":"RT3IN45JNJEES2TN","created_at":"2026-07-05T06:01:54.954841+00:00"},{"alias_kind":"pith_short_8","alias_value":"RT3IN45J","created_at":"2026-07-05T06:01:54.954841+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/RT3IN45JNJEES2TNZ7ZFP2KNSQ","json":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ.json","graph_json":"https://pith.science/api/pith-number/RT3IN45JNJEES2TNZ7ZFP2KNSQ/graph.json","events_json":"https://pith.science/api/pith-number/RT3IN45JNJEES2TNZ7ZFP2KNSQ/events.json","paper":"https://pith.science/paper/RT3IN45J"},"agent_actions":{"view_html":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ","download_json":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ.json","view_paper":"https://pith.science/paper/RT3IN45J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2103.01403&json=true","fetch_graph":"https://pith.science/api/pith-number/RT3IN45JNJEES2TNZ7ZFP2KNSQ/graph.json","fetch_events":"https://pith.science/api/pith-number/RT3IN45JNJEES2TNZ7ZFP2KNSQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ/action/storage_attestation","attest_author":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ/action/author_attestation","sign_citation":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ/action/citation_signature","submit_replication":"https://pith.science/pith/RT3IN45JNJEES2TNZ7ZFP2KNSQ/action/replication_record"}},"created_at":"2026-07-05T06:01:54.954841+00:00","updated_at":"2026-07-05T06:01:54.954841+00:00"}