{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:MY73L7ICSL4CDB54O4JRP5ZW4B","short_pith_number":"pith:MY73L7IC","schema_version":"1.0","canonical_sha256":"663fb5fd0292f82187bc771317f736e07050253746d86158f0717b318329a42e","source":{"kind":"arxiv","id":"2605.19302","version":1},"attestation_state":"computed","paper":{"title":"Distributionally Robust Games via Coherent Risk Measures","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Arunesh Sinha, Bharat Gangwani","submitted_at":"2026-05-19T03:27:07Z","abstract_excerpt":"We study strategic interaction in data-driven games where players face uncertainty about payoff distributions inferred from finite samples. To model calibrated attitudes toward such uncertainty, we formulate distributionally robust games with a special focus on coherent utility (risk) measures, including Mean-semideviation and Conditional Value-at-Risk. This framework treats risk sensitivity as a primitive feature of player preferences while retaining a formal connection to distributional robustness. We make a number of contributions that are enumerated next. (1) We use prior results for the e"},"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":"2605.19302","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2026-05-19T03:27:07Z","cross_cats_sorted":[],"title_canon_sha256":"8f1d953bd90cfc378f4a2f9f5d74f4c78750a0f94c906a1d8ac94d48c1cf3b31","abstract_canon_sha256":"b77bb90ffb1f2c481eaff26f8f13d3798559a6df5507af83bbc8ab898665d14e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:05:38.385779Z","signature_b64":"qgL40KoXCn25Khaibdn4k9sH4Yb9B+8+q/0XOYcFKJUHSoWG6vi9e6hXx3yFAclM0AAxwPy24lRR5eXIS0J6AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"663fb5fd0292f82187bc771317f736e07050253746d86158f0717b318329a42e","last_reissued_at":"2026-05-20T01:05:38.385001Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:05:38.385001Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributionally Robust Games via Coherent Risk Measures","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Arunesh Sinha, Bharat Gangwani","submitted_at":"2026-05-19T03:27:07Z","abstract_excerpt":"We study strategic interaction in data-driven games where players face uncertainty about payoff distributions inferred from finite samples. To model calibrated attitudes toward such uncertainty, we formulate distributionally robust games with a special focus on coherent utility (risk) measures, including Mean-semideviation and Conditional Value-at-Risk. This framework treats risk sensitivity as a primitive feature of player preferences while retaining a formal connection to distributional robustness. We make a number of contributions that are enumerated next. (1) We use prior results for the e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19302","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/2605.19302/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":"2605.19302","created_at":"2026-05-20T01:05:38.385130+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.19302v1","created_at":"2026-05-20T01:05:38.385130+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19302","created_at":"2026-05-20T01:05:38.385130+00:00"},{"alias_kind":"pith_short_12","alias_value":"MY73L7ICSL4C","created_at":"2026-05-20T01:05:38.385130+00:00"},{"alias_kind":"pith_short_16","alias_value":"MY73L7ICSL4CDB54","created_at":"2026-05-20T01:05:38.385130+00:00"},{"alias_kind":"pith_short_8","alias_value":"MY73L7IC","created_at":"2026-05-20T01:05:38.385130+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/MY73L7ICSL4CDB54O4JRP5ZW4B","json":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B.json","graph_json":"https://pith.science/api/pith-number/MY73L7ICSL4CDB54O4JRP5ZW4B/graph.json","events_json":"https://pith.science/api/pith-number/MY73L7ICSL4CDB54O4JRP5ZW4B/events.json","paper":"https://pith.science/paper/MY73L7IC"},"agent_actions":{"view_html":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B","download_json":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B.json","view_paper":"https://pith.science/paper/MY73L7IC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.19302&json=true","fetch_graph":"https://pith.science/api/pith-number/MY73L7ICSL4CDB54O4JRP5ZW4B/graph.json","fetch_events":"https://pith.science/api/pith-number/MY73L7ICSL4CDB54O4JRP5ZW4B/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B/action/storage_attestation","attest_author":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B/action/author_attestation","sign_citation":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B/action/citation_signature","submit_replication":"https://pith.science/pith/MY73L7ICSL4CDB54O4JRP5ZW4B/action/replication_record"}},"created_at":"2026-05-20T01:05:38.385130+00:00","updated_at":"2026-05-20T01:05:38.385130+00:00"}