{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:BVGKYIOGHB2BUBLZQAHQYFERKI","short_pith_number":"pith:BVGKYIOG","schema_version":"1.0","canonical_sha256":"0d4cac21c638741a0579800f0c14915211edb034f84e6ed1ec25ea0d89836d83","source":{"kind":"arxiv","id":"2202.08396","version":2},"attestation_state":"computed","paper":{"title":"Augment with Care: Contrastive Learning for Combinatorial Problems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LO"],"primary_cat":"cs.LG","authors_text":"Chris J. Maddison, Haonan Duan, Max B. Paulus, Pashootan Vaezipoor, Yangjun Ruan","submitted_at":"2022-02-17T01:31:32Z","abstract_excerpt":"Supervised learning can improve the design of state-of-the-art solvers for combinatorial problems, but labelling large numbers of combinatorial instances is often impractical due to exponential worst-case complexity. Inspired by the recent success of contrastive pre-training for images, we conduct a scientific study of the effect of augmentation design on contrastive pre-training for the Boolean satisfiability problem. While typical graph contrastive pre-training uses label-agnostic augmentations, our key insight is that many combinatorial problems have well-studied invariances, which allow fo"},"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":"2202.08396","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-02-17T01:31:32Z","cross_cats_sorted":["cs.AI","cs.LO"],"title_canon_sha256":"073008f88c44ce3839281a37b3a86060026006a170b5353bb19c0fe407f3aba0","abstract_canon_sha256":"b363b8979aa3f0e938ee5f031ddc9179b31cb82272cbb515130b02eccc2d1610"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:33:30.861688Z","signature_b64":"taNiuUrWeCpSaPVfBxH0WnBhMGfq/0IaHoMKR/Z7iTsadU2LGi7GJsbf3hd9ChpitKIoDhcPcmXH7bAp5LLRAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d4cac21c638741a0579800f0c14915211edb034f84e6ed1ec25ea0d89836d83","last_reissued_at":"2026-07-05T04:33:30.861143Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:33:30.861143Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Augment with Care: Contrastive Learning for Combinatorial Problems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LO"],"primary_cat":"cs.LG","authors_text":"Chris J. Maddison, Haonan Duan, Max B. Paulus, Pashootan Vaezipoor, Yangjun Ruan","submitted_at":"2022-02-17T01:31:32Z","abstract_excerpt":"Supervised learning can improve the design of state-of-the-art solvers for combinatorial problems, but labelling large numbers of combinatorial instances is often impractical due to exponential worst-case complexity. Inspired by the recent success of contrastive pre-training for images, we conduct a scientific study of the effect of augmentation design on contrastive pre-training for the Boolean satisfiability problem. While typical graph contrastive pre-training uses label-agnostic augmentations, our key insight is that many combinatorial problems have well-studied invariances, which allow fo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.08396","kind":"arxiv","version":2},"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/2202.08396/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":"2202.08396","created_at":"2026-07-05T04:33:30.861212+00:00"},{"alias_kind":"arxiv_version","alias_value":"2202.08396v2","created_at":"2026-07-05T04:33:30.861212+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.08396","created_at":"2026-07-05T04:33:30.861212+00:00"},{"alias_kind":"pith_short_12","alias_value":"BVGKYIOGHB2B","created_at":"2026-07-05T04:33:30.861212+00:00"},{"alias_kind":"pith_short_16","alias_value":"BVGKYIOGHB2BUBLZ","created_at":"2026-07-05T04:33:30.861212+00:00"},{"alias_kind":"pith_short_8","alias_value":"BVGKYIOG","created_at":"2026-07-05T04:33:30.861212+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/BVGKYIOGHB2BUBLZQAHQYFERKI","json":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI.json","graph_json":"https://pith.science/api/pith-number/BVGKYIOGHB2BUBLZQAHQYFERKI/graph.json","events_json":"https://pith.science/api/pith-number/BVGKYIOGHB2BUBLZQAHQYFERKI/events.json","paper":"https://pith.science/paper/BVGKYIOG"},"agent_actions":{"view_html":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI","download_json":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI.json","view_paper":"https://pith.science/paper/BVGKYIOG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2202.08396&json=true","fetch_graph":"https://pith.science/api/pith-number/BVGKYIOGHB2BUBLZQAHQYFERKI/graph.json","fetch_events":"https://pith.science/api/pith-number/BVGKYIOGHB2BUBLZQAHQYFERKI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI/action/storage_attestation","attest_author":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI/action/author_attestation","sign_citation":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI/action/citation_signature","submit_replication":"https://pith.science/pith/BVGKYIOGHB2BUBLZQAHQYFERKI/action/replication_record"}},"created_at":"2026-07-05T04:33:30.861212+00:00","updated_at":"2026-07-05T04:33:30.861212+00:00"}