{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YXMIUQXUO7LPVLLNK52MS3CCRK","short_pith_number":"pith:YXMIUQXU","canonical_record":{"source":{"id":"2503.18061","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-03-23T13:07:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b7aa8c2bfe6ba33f052bf70ccb995709ffe26c47324cc1a9b37ae012d1a78aac","abstract_canon_sha256":"5330846e9dbf52452b4e42d7d08116ff208b7fb088bd4c5b7709ab7e917ebafe"},"schema_version":"1.0"},"canonical_sha256":"c5d88a42f477d6faad6d5774c96c428aa216f10e9eda0c63a073722c6464b364","source":{"kind":"arxiv","id":"2503.18061","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.18061","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"arxiv_version","alias_value":"2503.18061v1","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18061","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"pith_short_12","alias_value":"YXMIUQXUO7LP","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"pith_short_16","alias_value":"YXMIUQXUO7LPVLLN","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"pith_short_8","alias_value":"YXMIUQXU","created_at":"2026-07-05T10:38:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YXMIUQXUO7LPVLLNK52MS3CCRK","target":"record","payload":{"canonical_record":{"source":{"id":"2503.18061","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-03-23T13:07:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b7aa8c2bfe6ba33f052bf70ccb995709ffe26c47324cc1a9b37ae012d1a78aac","abstract_canon_sha256":"5330846e9dbf52452b4e42d7d08116ff208b7fb088bd4c5b7709ab7e917ebafe"},"schema_version":"1.0"},"canonical_sha256":"c5d88a42f477d6faad6d5774c96c428aa216f10e9eda0c63a073722c6464b364","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:38:01.617212Z","signature_b64":"H11RQPJpjaX+IWK3E7FB2hznMvvCgvdVCT8VHnq1tnDTi/LshbqXcKkvisv+rP7qnSp2uoznnHAL1/b552m8Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c5d88a42f477d6faad6d5774c96c428aa216f10e9eda0c63a073722c6464b364","last_reissued_at":"2026-07-05T10:38:01.616747Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:38:01.616747Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.18061","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":"2026-07-05T10:38:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0YtL/b5R98R7/ZqNEfDKXkE6zyJZzOQm6Q75RmOPg15HF9YOylVqYutF6Z8yKgu0n0WQ5zV1PQL1Qia2uVwoAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T02:01:37.934661Z"},"content_sha256":"2027ca790480bc78d9bf33d09a2f9a1173c1cffaa7a077bb2c76d18802a9d4e5","schema_version":"1.0","event_id":"sha256:2027ca790480bc78d9bf33d09a2f9a1173c1cffaa7a077bb2c76d18802a9d4e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YXMIUQXUO7LPVLLNK52MS3CCRK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reinforcement Learning-based Self-adaptive Differential Evolution through Automated Landscape Feature Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NE","authors_text":"Hongshu Guo, Sijie Ma, Xinglin Zhang, Yue-Jiao Gong, Yuzhi Hu, Zechuan Huang, Zeyuan Ma","submitted_at":"2025-03-23T13:07:57Z","abstract_excerpt":"Recently, Meta-Black-Box-Optimization (MetaBBO) methods significantly enhance the performance of traditional black-box optimizers through meta-learning flexible and generalizable meta-level policies that excel in dynamic algorithm configuration (DAC) tasks within the low-level optimization, reducing the expertise required to adapt optimizers for novel optimization tasks. Though promising, existing MetaBBO methods heavily rely on human-crafted feature extraction approach to secure learning effectiveness. To address this issue, this paper introduces a novel MetaBBO method that supports automated"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18061","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/2503.18061/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":"2026-07-05T10:38:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"axCLUMROSQ6BMw2aI2YlFVeyxiSTOBkCl9+wIF9P/siLY6eTB9R3a2etazrfZYIFYOsI71Y6/cwBdd4u2reoCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T02:01:37.935053Z"},"content_sha256":"b17b42531806b49fe15354432345a03506237410860a581c9248979175c9277e","schema_version":"1.0","event_id":"sha256:b17b42531806b49fe15354432345a03506237410860a581c9248979175c9277e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YXMIUQXUO7LPVLLNK52MS3CCRK/bundle.json","state_url":"https://pith.science/pith/YXMIUQXUO7LPVLLNK52MS3CCRK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YXMIUQXUO7LPVLLNK52MS3CCRK/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":"2026-07-11T02:01:37Z","links":{"resolver":"https://pith.science/pith/YXMIUQXUO7LPVLLNK52MS3CCRK","bundle":"https://pith.science/pith/YXMIUQXUO7LPVLLNK52MS3CCRK/bundle.json","state":"https://pith.science/pith/YXMIUQXUO7LPVLLNK52MS3CCRK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YXMIUQXUO7LPVLLNK52MS3CCRK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YXMIUQXUO7LPVLLNK52MS3CCRK","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":"5330846e9dbf52452b4e42d7d08116ff208b7fb088bd4c5b7709ab7e917ebafe","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-03-23T13:07:57Z","title_canon_sha256":"b7aa8c2bfe6ba33f052bf70ccb995709ffe26c47324cc1a9b37ae012d1a78aac"},"schema_version":"1.0","source":{"id":"2503.18061","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.18061","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"arxiv_version","alias_value":"2503.18061v1","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18061","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"pith_short_12","alias_value":"YXMIUQXUO7LP","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"pith_short_16","alias_value":"YXMIUQXUO7LPVLLN","created_at":"2026-07-05T10:38:01Z"},{"alias_kind":"pith_short_8","alias_value":"YXMIUQXU","created_at":"2026-07-05T10:38:01Z"}],"graph_snapshots":[{"event_id":"sha256:b17b42531806b49fe15354432345a03506237410860a581c9248979175c9277e","target":"graph","created_at":"2026-07-05T10:38:01Z","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/2503.18061/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, Meta-Black-Box-Optimization (MetaBBO) methods significantly enhance the performance of traditional black-box optimizers through meta-learning flexible and generalizable meta-level policies that excel in dynamic algorithm configuration (DAC) tasks within the low-level optimization, reducing the expertise required to adapt optimizers for novel optimization tasks. Though promising, existing MetaBBO methods heavily rely on human-crafted feature extraction approach to secure learning effectiveness. To address this issue, this paper introduces a novel MetaBBO method that supports automated","authors_text":"Hongshu Guo, Sijie Ma, Xinglin Zhang, Yue-Jiao Gong, Yuzhi Hu, Zechuan Huang, Zeyuan Ma","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-03-23T13:07:57Z","title":"Reinforcement Learning-based Self-adaptive Differential Evolution through Automated Landscape Feature Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18061","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":"sha256:2027ca790480bc78d9bf33d09a2f9a1173c1cffaa7a077bb2c76d18802a9d4e5","target":"record","created_at":"2026-07-05T10:38:01Z","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":"5330846e9dbf52452b4e42d7d08116ff208b7fb088bd4c5b7709ab7e917ebafe","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-03-23T13:07:57Z","title_canon_sha256":"b7aa8c2bfe6ba33f052bf70ccb995709ffe26c47324cc1a9b37ae012d1a78aac"},"schema_version":"1.0","source":{"id":"2503.18061","kind":"arxiv","version":1}},"canonical_sha256":"c5d88a42f477d6faad6d5774c96c428aa216f10e9eda0c63a073722c6464b364","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c5d88a42f477d6faad6d5774c96c428aa216f10e9eda0c63a073722c6464b364","first_computed_at":"2026-07-05T10:38:01.616747Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:38:01.616747Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"H11RQPJpjaX+IWK3E7FB2hznMvvCgvdVCT8VHnq1tnDTi/LshbqXcKkvisv+rP7qnSp2uoznnHAL1/b552m8Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:38:01.617212Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.18061","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2027ca790480bc78d9bf33d09a2f9a1173c1cffaa7a077bb2c76d18802a9d4e5","sha256:b17b42531806b49fe15354432345a03506237410860a581c9248979175c9277e"],"state_sha256":"552e02f0c05e2315c3b08293b1d934768b9f037a43ee63a9313cd2424f373330"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VDG8jGqLygMKAIDJVTHzSKyk2nfP6MoZmEpXLstym8VTdJwGYy9s3GLnNffSBbWFZ2jL4MCf4/F1zGP7H/8kCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T02:01:37.938244Z","bundle_sha256":"d7eeffd21b7b8d90a4efe3d1e772509e70c93f2f9d207cb3877ed6983496f89d"}}