{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QSGI5WN3YIRHWZHTKYR6OEGZWW","short_pith_number":"pith:QSGI5WN3","canonical_record":{"source":{"id":"2403.04015","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T19:58:19Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"4f27d024aff92cb665db0ae2a92c3ee4bb484d938ed87fd00eabf69dae846cea","abstract_canon_sha256":"01a72003560848572c0458a724cda0d783a3ac3aea6c8d87dfc513e1a728c053"},"schema_version":"1.0"},"canonical_sha256":"848c8ed9bbc2227b64f35623e710d9b59b09b083bef613bee80c0d2f75b48442","source":{"kind":"arxiv","id":"2403.04015","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.04015","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"arxiv_version","alias_value":"2403.04015v1","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.04015","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"pith_short_12","alias_value":"QSGI5WN3YIRH","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"pith_short_16","alias_value":"QSGI5WN3YIRHWZHT","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"pith_short_8","alias_value":"QSGI5WN3","created_at":"2026-07-05T07:53:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QSGI5WN3YIRHWZHTKYR6OEGZWW","target":"record","payload":{"canonical_record":{"source":{"id":"2403.04015","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T19:58:19Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"4f27d024aff92cb665db0ae2a92c3ee4bb484d938ed87fd00eabf69dae846cea","abstract_canon_sha256":"01a72003560848572c0458a724cda0d783a3ac3aea6c8d87dfc513e1a728c053"},"schema_version":"1.0"},"canonical_sha256":"848c8ed9bbc2227b64f35623e710d9b59b09b083bef613bee80c0d2f75b48442","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:17.132601Z","signature_b64":"Hr5iv0ye8lExRsJnTvuw28q+x7Z96cAsW1t2UtL8JwUB9yeUhFHaM2tHv3xNYJdANzXk+4jn4ThEyXL/0zJXCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"848c8ed9bbc2227b64f35623e710d9b59b09b083bef613bee80c0d2f75b48442","last_reissued_at":"2026-07-05T07:53:17.132117Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:17.132117Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.04015","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:53:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Cmu6bnjN+SBFkfykbZ9lRlWU7owUXbDkDUidKz8BzyQEOhe9MTxxdDvJW0vicOgHAtVa5ajXyAIDKCe15AdYBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:55:27.232256Z"},"content_sha256":"924c0f9d39c84dd600f0f1a8e711ddc8869459053fb3b64f85c6efb7ccb6dbf5","schema_version":"1.0","event_id":"sha256:924c0f9d39c84dd600f0f1a8e711ddc8869459053fb3b64f85c6efb7ccb6dbf5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QSGI5WN3YIRHWZHTKYR6OEGZWW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Knockoff-Guided Feature Selection via A Single Pre-trained Reinforced Agent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Dongjie Wang, Haifeng Chen, Rui Xie, Wangyang Ying, Xinyuan Wang, Yanjie Fu","submitted_at":"2024-03-06T19:58:19Z","abstract_excerpt":"Feature selection prepares the AI-readiness of data by eliminating redundant features. Prior research falls into two primary categories: i) Supervised Feature Selection, which identifies the optimal feature subset based on their relevance to the target variable; ii) Unsupervised Feature Selection, which reduces the feature space dimensionality by capturing the essential information within the feature set instead of using target variable. However, SFS approaches suffer from time-consuming processes and limited generalizability due to the dependence on the target variable and downstream ML tasks"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.04015","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/2403.04015/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:53:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4Ii6IhGL9JGdpsv6j6FXL/FUJmGoCPUrkdhpxi26l9cYQ6S4Vv0JVWg97ejBE8MO2psOXSdWTf5kKCoRUPN1Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:55:27.232746Z"},"content_sha256":"0e0588be9c80cf2ee2b0324486d0197bd489a98d85ffd5dd24eb5cf032ae8232","schema_version":"1.0","event_id":"sha256:0e0588be9c80cf2ee2b0324486d0197bd489a98d85ffd5dd24eb5cf032ae8232"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QSGI5WN3YIRHWZHTKYR6OEGZWW/bundle.json","state_url":"https://pith.science/pith/QSGI5WN3YIRHWZHTKYR6OEGZWW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QSGI5WN3YIRHWZHTKYR6OEGZWW/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T04:55:27Z","links":{"resolver":"https://pith.science/pith/QSGI5WN3YIRHWZHTKYR6OEGZWW","bundle":"https://pith.science/pith/QSGI5WN3YIRHWZHTKYR6OEGZWW/bundle.json","state":"https://pith.science/pith/QSGI5WN3YIRHWZHTKYR6OEGZWW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QSGI5WN3YIRHWZHTKYR6OEGZWW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QSGI5WN3YIRHWZHTKYR6OEGZWW","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":"01a72003560848572c0458a724cda0d783a3ac3aea6c8d87dfc513e1a728c053","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T19:58:19Z","title_canon_sha256":"4f27d024aff92cb665db0ae2a92c3ee4bb484d938ed87fd00eabf69dae846cea"},"schema_version":"1.0","source":{"id":"2403.04015","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.04015","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"arxiv_version","alias_value":"2403.04015v1","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.04015","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"pith_short_12","alias_value":"QSGI5WN3YIRH","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"pith_short_16","alias_value":"QSGI5WN3YIRHWZHT","created_at":"2026-07-05T07:53:17Z"},{"alias_kind":"pith_short_8","alias_value":"QSGI5WN3","created_at":"2026-07-05T07:53:17Z"}],"graph_snapshots":[{"event_id":"sha256:0e0588be9c80cf2ee2b0324486d0197bd489a98d85ffd5dd24eb5cf032ae8232","target":"graph","created_at":"2026-07-05T07:53:17Z","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/2403.04015/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Feature selection prepares the AI-readiness of data by eliminating redundant features. Prior research falls into two primary categories: i) Supervised Feature Selection, which identifies the optimal feature subset based on their relevance to the target variable; ii) Unsupervised Feature Selection, which reduces the feature space dimensionality by capturing the essential information within the feature set instead of using target variable. However, SFS approaches suffer from time-consuming processes and limited generalizability due to the dependence on the target variable and downstream ML tasks","authors_text":"Dongjie Wang, Haifeng Chen, Rui Xie, Wangyang Ying, Xinyuan Wang, Yanjie Fu","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T19:58:19Z","title":"Knockoff-Guided Feature Selection via A Single Pre-trained Reinforced Agent"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.04015","kind":"arxiv","version":1},"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":"sha256:924c0f9d39c84dd600f0f1a8e711ddc8869459053fb3b64f85c6efb7ccb6dbf5","target":"record","created_at":"2026-07-05T07:53:17Z","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":"01a72003560848572c0458a724cda0d783a3ac3aea6c8d87dfc513e1a728c053","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-06T19:58:19Z","title_canon_sha256":"4f27d024aff92cb665db0ae2a92c3ee4bb484d938ed87fd00eabf69dae846cea"},"schema_version":"1.0","source":{"id":"2403.04015","kind":"arxiv","version":1}},"canonical_sha256":"848c8ed9bbc2227b64f35623e710d9b59b09b083bef613bee80c0d2f75b48442","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"848c8ed9bbc2227b64f35623e710d9b59b09b083bef613bee80c0d2f75b48442","first_computed_at":"2026-07-05T07:53:17.132117Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:53:17.132117Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Hr5iv0ye8lExRsJnTvuw28q+x7Z96cAsW1t2UtL8JwUB9yeUhFHaM2tHv3xNYJdANzXk+4jn4ThEyXL/0zJXCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:53:17.132601Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.04015","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:924c0f9d39c84dd600f0f1a8e711ddc8869459053fb3b64f85c6efb7ccb6dbf5","sha256:0e0588be9c80cf2ee2b0324486d0197bd489a98d85ffd5dd24eb5cf032ae8232"],"state_sha256":"62a10c2039ed0b3f90c8235a0543410e502bf13cc4ad531e9966cd4eb08f7172"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4bKhqRnZDs9m7tg2bW1rigER0p9Y7lic+Ekayl/ltDi/wYp6QPmsyDw2PMA9AAEuHVmdiUgTLiIbpo6XTEubDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T04:55:27.237732Z","bundle_sha256":"004b7b8288c1011c532209c2bc271f2fdf711790352f0207cb0d138e372da18c"}}