{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:Y55LADY7EARGIRURTVXI5YW6QD","short_pith_number":"pith:Y55LADY7","schema_version":"1.0","canonical_sha256":"c77ab00f1f20226446919d6e8ee2de80e2e5e661249834fb57a1c110dd650e8f","source":{"kind":"arxiv","id":"2503.06602","version":1},"attestation_state":"computed","paper":{"title":"FW-Shapley: Real-time Estimation of Weighted Shapley Values","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Pranoy Panda, Siddharth Tandon, Vineeth N Balasubramanian","submitted_at":"2025-03-09T13:13:14Z","abstract_excerpt":"Fair credit assignment is essential in various machine learning (ML) applications, and Shapley values have emerged as a valuable tool for this purpose. However, in critical ML applications such as data valuation and feature attribution, the uniform weighting of Shapley values across subset cardinalities leads to unintuitive credit assignments. To address this, weighted Shapley values were proposed as a generalization, allowing different weights for subsets with different cardinalities. Despite their advantages, similar to Shapley values, Weighted Shapley values suffer from exponential compute "},"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":"2503.06602","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-09T13:13:14Z","cross_cats_sorted":[],"title_canon_sha256":"699fbfd9d300855cbe43c144b9b292b7bbd1c057866d4ffaa3541424bb902955","abstract_canon_sha256":"63a2a7d8e2db9948136a7dac75e806ba318da18eac45bfe04ec03b0b2c915c2e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:27:37.940482Z","signature_b64":"sSUa3TVSfTeLkH3TZEt2171eR8E8bZoO9HQEeXoCVyxU5C6kiTig9Nq/JSiWCL4KAYP6xGak7RDC1lOYCSBaBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c77ab00f1f20226446919d6e8ee2de80e2e5e661249834fb57a1c110dd650e8f","last_reissued_at":"2026-07-05T10:27:37.939986Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:27:37.939986Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FW-Shapley: Real-time Estimation of Weighted Shapley Values","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Pranoy Panda, Siddharth Tandon, Vineeth N Balasubramanian","submitted_at":"2025-03-09T13:13:14Z","abstract_excerpt":"Fair credit assignment is essential in various machine learning (ML) applications, and Shapley values have emerged as a valuable tool for this purpose. However, in critical ML applications such as data valuation and feature attribution, the uniform weighting of Shapley values across subset cardinalities leads to unintuitive credit assignments. To address this, weighted Shapley values were proposed as a generalization, allowing different weights for subsets with different cardinalities. Despite their advantages, similar to Shapley values, Weighted Shapley values suffer from exponential compute "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.06602","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/2503.06602/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":"2503.06602","created_at":"2026-07-05T10:27:37.940043+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.06602v1","created_at":"2026-07-05T10:27:37.940043+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.06602","created_at":"2026-07-05T10:27:37.940043+00:00"},{"alias_kind":"pith_short_12","alias_value":"Y55LADY7EARG","created_at":"2026-07-05T10:27:37.940043+00:00"},{"alias_kind":"pith_short_16","alias_value":"Y55LADY7EARGIRUR","created_at":"2026-07-05T10:27:37.940043+00:00"},{"alias_kind":"pith_short_8","alias_value":"Y55LADY7","created_at":"2026-07-05T10:27:37.940043+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/Y55LADY7EARGIRURTVXI5YW6QD","json":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD.json","graph_json":"https://pith.science/api/pith-number/Y55LADY7EARGIRURTVXI5YW6QD/graph.json","events_json":"https://pith.science/api/pith-number/Y55LADY7EARGIRURTVXI5YW6QD/events.json","paper":"https://pith.science/paper/Y55LADY7"},"agent_actions":{"view_html":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD","download_json":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD.json","view_paper":"https://pith.science/paper/Y55LADY7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.06602&json=true","fetch_graph":"https://pith.science/api/pith-number/Y55LADY7EARGIRURTVXI5YW6QD/graph.json","fetch_events":"https://pith.science/api/pith-number/Y55LADY7EARGIRURTVXI5YW6QD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD/action/storage_attestation","attest_author":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD/action/author_attestation","sign_citation":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD/action/citation_signature","submit_replication":"https://pith.science/pith/Y55LADY7EARGIRURTVXI5YW6QD/action/replication_record"}},"created_at":"2026-07-05T10:27:37.940043+00:00","updated_at":"2026-07-05T10:27:37.940043+00:00"}