{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:WHHVJDXVCFOL5FSZ3T5QIDVIEL","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":"ebeac8d66b8ff6712c13903897f83ba3f4039621e7d259b0f78e1e1904f2a081","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2020-03-02T00:37:36Z","title_canon_sha256":"d858c6b11524f13d26ff657e39fdf34edec38946f37ac8fb31e5f4fd6c0b1571"},"schema_version":"1.0","source":{"id":"2003.01497","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.01497","created_at":"2026-07-05T03:25:09Z"},{"alias_kind":"arxiv_version","alias_value":"2003.01497v4","created_at":"2026-07-05T03:25:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.01497","created_at":"2026-07-05T03:25:09Z"},{"alias_kind":"pith_short_12","alias_value":"WHHVJDXVCFOL","created_at":"2026-07-05T03:25:09Z"},{"alias_kind":"pith_short_16","alias_value":"WHHVJDXVCFOL5FSZ","created_at":"2026-07-05T03:25:09Z"},{"alias_kind":"pith_short_8","alias_value":"WHHVJDXV","created_at":"2026-07-05T03:25:09Z"}],"graph_snapshots":[{"event_id":"sha256:b4711cf082eb7fa511634b2d3107ab13def4aa27b536af4728ce21c446ffed3c","target":"graph","created_at":"2026-07-05T03:25:09Z","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/2003.01497/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Designing an incentive compatible auction that maximizes expected revenue is a central problem in Auction Design. Theoretical approaches to the problem have hit some limits in the past decades and analytical solutions are known for only a few simple settings. Computational approaches to the problem through the use of LPs have their own set of limitations. Building on the success of deep learning, a new approach was recently proposed by Duetting et al. (2019) in which the auction is modeled by a feed-forward neural network and the design problem is framed as a learning problem. The neural archi","authors_text":"Jad Rahme, Joan Bruna, Samy Jelassi, S. Matthew Weinberg","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2020-03-02T00:37:36Z","title":"A Permutation-Equivariant Neural Network Architecture For Auction Design"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.01497","kind":"arxiv","version":4},"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:b11c49cd80a6c0da7793cce16f5cfb1107f5c097f837fbe3a11425f2acb4526c","target":"record","created_at":"2026-07-05T03:25:09Z","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":"ebeac8d66b8ff6712c13903897f83ba3f4039621e7d259b0f78e1e1904f2a081","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2020-03-02T00:37:36Z","title_canon_sha256":"d858c6b11524f13d26ff657e39fdf34edec38946f37ac8fb31e5f4fd6c0b1571"},"schema_version":"1.0","source":{"id":"2003.01497","kind":"arxiv","version":4}},"canonical_sha256":"b1cf548ef5115cbe9659dcfb040ea822d1e710c8980db14d525b9b98d0588265","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b1cf548ef5115cbe9659dcfb040ea822d1e710c8980db14d525b9b98d0588265","first_computed_at":"2026-07-05T03:25:09.698165Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:25:09.698165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kxvMQ0JjcNZEoCKTBM1FnBCNgPNxjCbSIK/5VuRLiOVdWY0ishki+Yu/xwqnPsG/nORuqj1q5QbQkOx5es6RCg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:25:09.698676Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.01497","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b11c49cd80a6c0da7793cce16f5cfb1107f5c097f837fbe3a11425f2acb4526c","sha256:b4711cf082eb7fa511634b2d3107ab13def4aa27b536af4728ce21c446ffed3c"],"state_sha256":"0b0e794db96001dd76e62cd613240b47aa1bde69c7c6368f13f67f4871d8190a"}