{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:XM4S2A57VOSL3K6FSWEOQQUKR5","short_pith_number":"pith:XM4S2A57","schema_version":"1.0","canonical_sha256":"bb392d03bfaba4bdabc59588e8428a8f5ba0e37fa22341ab2508458eeecbfd43","source":{"kind":"arxiv","id":"2405.00295","version":3},"attestation_state":"computed","paper":{"title":"Proof of Sampling: A Nash Equilibrium-Based Verification Protocol for Decentralized Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Ciamac C. Moallemi, Raluca Ada Popa, Shouqiao Wang, Sijun Tan, Xiaoyuan Liu, Yue Zhang","submitted_at":"2024-05-01T03:27:58Z","abstract_excerpt":"This paper introduces the Proof of Sampling (PoSP) protocol, a Nash Equilibrium-based verification mechanism, and its application to decentralized machine learning inference through spML. Our protocol has a pure strategy Nash Equilibrium, compelling rational participants to act honestly. It economically disincentivizes dishonest behavior, making it costly for participants to compromise the network's integrity. In our spML protocol, we apply PoSP to decentralized inference for AI applications via a novel cryptographic protocol. The resulting protocol is much more efficient than zero knowledge p"},"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":"2405.00295","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2024-05-01T03:27:58Z","cross_cats_sorted":[],"title_canon_sha256":"ee04a7c4c8347e592f007ff7321455d3eca385e6ec479abaccdc31a72b301b14","abstract_canon_sha256":"18b8763f85a70bea8931e0255cf9e09a35a29b4836128f7fcb861b5a067197fe"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:13:09.287885Z","signature_b64":"e3JuR73nirmCPhtTBTDaKbBZLiJ1+QUeardWiJbn1T1tlno97bwPwGBJYl2oFj0j8z2GdPpDfce7ZWb84QkuAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bb392d03bfaba4bdabc59588e8428a8f5ba0e37fa22341ab2508458eeecbfd43","last_reissued_at":"2026-07-05T11:13:09.287290Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:13:09.287290Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Proof of Sampling: A Nash Equilibrium-Based Verification Protocol for Decentralized Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Ciamac C. Moallemi, Raluca Ada Popa, Shouqiao Wang, Sijun Tan, Xiaoyuan Liu, Yue Zhang","submitted_at":"2024-05-01T03:27:58Z","abstract_excerpt":"This paper introduces the Proof of Sampling (PoSP) protocol, a Nash Equilibrium-based verification mechanism, and its application to decentralized machine learning inference through spML. Our protocol has a pure strategy Nash Equilibrium, compelling rational participants to act honestly. It economically disincentivizes dishonest behavior, making it costly for participants to compromise the network's integrity. In our spML protocol, we apply PoSP to decentralized inference for AI applications via a novel cryptographic protocol. The resulting protocol is much more efficient than zero knowledge p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.00295","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/2405.00295/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":"2405.00295","created_at":"2026-07-05T11:13:09.287371+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.00295v3","created_at":"2026-07-05T11:13:09.287371+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.00295","created_at":"2026-07-05T11:13:09.287371+00:00"},{"alias_kind":"pith_short_12","alias_value":"XM4S2A57VOSL","created_at":"2026-07-05T11:13:09.287371+00:00"},{"alias_kind":"pith_short_16","alias_value":"XM4S2A57VOSL3K6F","created_at":"2026-07-05T11:13:09.287371+00:00"},{"alias_kind":"pith_short_8","alias_value":"XM4S2A57","created_at":"2026-07-05T11:13:09.287371+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2404.09005","citing_title":"Proof-of-Learning with Incentive Security","ref_index":68,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5","json":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5.json","graph_json":"https://pith.science/api/pith-number/XM4S2A57VOSL3K6FSWEOQQUKR5/graph.json","events_json":"https://pith.science/api/pith-number/XM4S2A57VOSL3K6FSWEOQQUKR5/events.json","paper":"https://pith.science/paper/XM4S2A57"},"agent_actions":{"view_html":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5","download_json":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5.json","view_paper":"https://pith.science/paper/XM4S2A57","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.00295&json=true","fetch_graph":"https://pith.science/api/pith-number/XM4S2A57VOSL3K6FSWEOQQUKR5/graph.json","fetch_events":"https://pith.science/api/pith-number/XM4S2A57VOSL3K6FSWEOQQUKR5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5/action/storage_attestation","attest_author":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5/action/author_attestation","sign_citation":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5/action/citation_signature","submit_replication":"https://pith.science/pith/XM4S2A57VOSL3K6FSWEOQQUKR5/action/replication_record"}},"created_at":"2026-07-05T11:13:09.287371+00:00","updated_at":"2026-07-05T11:13:09.287371+00:00"}