{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:KBNKMSNQXCWCJXU5NMSSWZHJQA","short_pith_number":"pith:KBNKMSNQ","schema_version":"1.0","canonical_sha256":"505aa649b0b8ac24de9d6b252b64e980385aa1be85f130f94c54cffb42cf44fd","source":{"kind":"arxiv","id":"2310.06440","version":1},"attestation_state":"computed","paper":{"title":"Solution for SMART-101 Challenge of ICCV Multi-modal Algorithmic Reasoning Task 2023","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jianfeng Lu, Qingguo Chen, Shengdong Xu, Xiangyu Wu, Yang Yang, Yifeng Wu","submitted_at":"2023-10-10T09:12:27Z","abstract_excerpt":"In this paper, we present our solution to a Multi-modal Algorithmic Reasoning Task: SMART-101 Challenge. Different from the traditional visual question-answering datasets, this challenge evaluates the abstraction, deduction, and generalization abilities of neural networks in solving visuolinguistic puzzles designed specifically for children in the 6-8 age group. We employed a divide-and-conquer approach. At the data level, inspired by the challenge paper, we categorized the whole questions into eight types and utilized the llama-2-chat model to directly generate the type for each question in a"},"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":"2310.06440","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-10-10T09:12:27Z","cross_cats_sorted":[],"title_canon_sha256":"ec816044e59f61cb9a24b9018381ac126f616b6cbb0177af68221ed548c39c0f","abstract_canon_sha256":"735a5839ef6156223f2f1c5223b00c24085c1fb4422566bc69d01e1c0f84737a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:59:11.531731Z","signature_b64":"hyHr5Jxcy1zxjN2X1URvRDUHNddAXmOvM317B83OBGYhaLVWqmJHMl6C0rVVQmpGJX3SjoRS2XByVW3y4KglBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"505aa649b0b8ac24de9d6b252b64e980385aa1be85f130f94c54cffb42cf44fd","last_reissued_at":"2026-07-05T06:59:11.531334Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:59:11.531334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Solution for SMART-101 Challenge of ICCV Multi-modal Algorithmic Reasoning Task 2023","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jianfeng Lu, Qingguo Chen, Shengdong Xu, Xiangyu Wu, Yang Yang, Yifeng Wu","submitted_at":"2023-10-10T09:12:27Z","abstract_excerpt":"In this paper, we present our solution to a Multi-modal Algorithmic Reasoning Task: SMART-101 Challenge. Different from the traditional visual question-answering datasets, this challenge evaluates the abstraction, deduction, and generalization abilities of neural networks in solving visuolinguistic puzzles designed specifically for children in the 6-8 age group. We employed a divide-and-conquer approach. At the data level, inspired by the challenge paper, we categorized the whole questions into eight types and utilized the llama-2-chat model to directly generate the type for each question in a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.06440","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/2310.06440/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":"2310.06440","created_at":"2026-07-05T06:59:11.531385+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.06440v1","created_at":"2026-07-05T06:59:11.531385+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.06440","created_at":"2026-07-05T06:59:11.531385+00:00"},{"alias_kind":"pith_short_12","alias_value":"KBNKMSNQXCWC","created_at":"2026-07-05T06:59:11.531385+00:00"},{"alias_kind":"pith_short_16","alias_value":"KBNKMSNQXCWCJXU5","created_at":"2026-07-05T06:59:11.531385+00:00"},{"alias_kind":"pith_short_8","alias_value":"KBNKMSNQ","created_at":"2026-07-05T06:59:11.531385+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/KBNKMSNQXCWCJXU5NMSSWZHJQA","json":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA.json","graph_json":"https://pith.science/api/pith-number/KBNKMSNQXCWCJXU5NMSSWZHJQA/graph.json","events_json":"https://pith.science/api/pith-number/KBNKMSNQXCWCJXU5NMSSWZHJQA/events.json","paper":"https://pith.science/paper/KBNKMSNQ"},"agent_actions":{"view_html":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA","download_json":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA.json","view_paper":"https://pith.science/paper/KBNKMSNQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.06440&json=true","fetch_graph":"https://pith.science/api/pith-number/KBNKMSNQXCWCJXU5NMSSWZHJQA/graph.json","fetch_events":"https://pith.science/api/pith-number/KBNKMSNQXCWCJXU5NMSSWZHJQA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA/action/storage_attestation","attest_author":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA/action/author_attestation","sign_citation":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA/action/citation_signature","submit_replication":"https://pith.science/pith/KBNKMSNQXCWCJXU5NMSSWZHJQA/action/replication_record"}},"created_at":"2026-07-05T06:59:11.531385+00:00","updated_at":"2026-07-05T06:59:11.531385+00:00"}