{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:236MV2UC7ARHAGQAYRH2WPOWD2","short_pith_number":"pith:236MV2UC","canonical_record":{"source":{"id":"2408.10672","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-20T09:17:11Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"e29bbd3c55fe596f9820b827f209186e927c290c0fc1ab43dad01ac890101624","abstract_canon_sha256":"4d55146ed5fa196ead1e3db35a537a1f58d6617ac51e7dcde63bd84f55d28171"},"schema_version":"1.0"},"canonical_sha256":"d6fccaea82f822701a00c44fab3dd61e8c92c8063e892ffe697550f404454b31","source":{"kind":"arxiv","id":"2408.10672","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.10672","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"arxiv_version","alias_value":"2408.10672v3","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.10672","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_12","alias_value":"236MV2UC7ARH","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_16","alias_value":"236MV2UC7ARHAGQA","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_8","alias_value":"236MV2UC","created_at":"2026-07-05T10:39:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:236MV2UC7ARHAGQAYRH2WPOWD2","target":"record","payload":{"canonical_record":{"source":{"id":"2408.10672","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-20T09:17:11Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"e29bbd3c55fe596f9820b827f209186e927c290c0fc1ab43dad01ac890101624","abstract_canon_sha256":"4d55146ed5fa196ead1e3db35a537a1f58d6617ac51e7dcde63bd84f55d28171"},"schema_version":"1.0"},"canonical_sha256":"d6fccaea82f822701a00c44fab3dd61e8c92c8063e892ffe697550f404454b31","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:39:46.080754Z","signature_b64":"KM/dCES4TIYv4kl4yJIuObgC74rwwijS6ZaIJLhXd6nJMbL8HoQ32RIBolqsVQry9lv7Wqh/dkisILwiJgaHDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6fccaea82f822701a00c44fab3dd61e8c92c8063e892ffe697550f404454b31","last_reissued_at":"2026-07-05T10:39:46.080231Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:39:46.080231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.10672","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:39:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zCL4cx5aXLg8yJJixLLY9Rm4FBF+YXvedZA5R00aPxqB60x2g72lLDpUIgqt9N32o9ztpd/UNyW6xuYSIX8aDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T09:18:51.625136Z"},"content_sha256":"e2092e6cef8ba2c30e18303a235916ccfed94e3fa1b68a274c8ac11ccbe88334","schema_version":"1.0","event_id":"sha256:e2092e6cef8ba2c30e18303a235916ccfed94e3fa1b68a274c8ac11ccbe88334"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:236MV2UC7ARHAGQAYRH2WPOWD2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Hongshu Guo, Jiacheng Chen, Yue-Jiao Gong, Zeyuan Ma","submitted_at":"2024-08-20T09:17:11Z","abstract_excerpt":"Recent research in Meta-Black-Box Optimization (MetaBBO) have shown that meta-trained neural networks can effectively guide the design of black-box optimizers, significantly reducing the need for expert tuning and delivering robust performance across complex problem distributions. Despite their success, a paradox remains: MetaBBO still rely on human-crafted Exploratory Landscape Analysis features to inform the meta-level agent about the low-level optimization progress. To address the gap, this paper proposes Neural Exploratory Landscape Analysis (NeurELA), a novel framework that dynamically pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.10672","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/2408.10672/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":"2026-07-05T10:39:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FF583Zzl7l0PT1JCC7HM0NDazEbO3UccrKzhcPo9qakZaSWK/sD9tbEU5gjLIH12GLB3sd/cTiBf5sWoGuCxCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T09:18:51.625805Z"},"content_sha256":"27688b478d0ee228621faf47288b710131e0af31e8a65f217bac91e4e3a9a5fd","schema_version":"1.0","event_id":"sha256:27688b478d0ee228621faf47288b710131e0af31e8a65f217bac91e4e3a9a5fd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/236MV2UC7ARHAGQAYRH2WPOWD2/bundle.json","state_url":"https://pith.science/pith/236MV2UC7ARHAGQAYRH2WPOWD2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/236MV2UC7ARHAGQAYRH2WPOWD2/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":"2026-08-13T09:18:51Z","links":{"resolver":"https://pith.science/pith/236MV2UC7ARHAGQAYRH2WPOWD2","bundle":"https://pith.science/pith/236MV2UC7ARHAGQAYRH2WPOWD2/bundle.json","state":"https://pith.science/pith/236MV2UC7ARHAGQAYRH2WPOWD2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/236MV2UC7ARHAGQAYRH2WPOWD2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:236MV2UC7ARHAGQAYRH2WPOWD2","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":"4d55146ed5fa196ead1e3db35a537a1f58d6617ac51e7dcde63bd84f55d28171","cross_cats_sorted":["cs.NE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-20T09:17:11Z","title_canon_sha256":"e29bbd3c55fe596f9820b827f209186e927c290c0fc1ab43dad01ac890101624"},"schema_version":"1.0","source":{"id":"2408.10672","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.10672","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"arxiv_version","alias_value":"2408.10672v3","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.10672","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_12","alias_value":"236MV2UC7ARH","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_16","alias_value":"236MV2UC7ARHAGQA","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_8","alias_value":"236MV2UC","created_at":"2026-07-05T10:39:46Z"}],"graph_snapshots":[{"event_id":"sha256:27688b478d0ee228621faf47288b710131e0af31e8a65f217bac91e4e3a9a5fd","target":"graph","created_at":"2026-07-05T10:39:46Z","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/2408.10672/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent research in Meta-Black-Box Optimization (MetaBBO) have shown that meta-trained neural networks can effectively guide the design of black-box optimizers, significantly reducing the need for expert tuning and delivering robust performance across complex problem distributions. Despite their success, a paradox remains: MetaBBO still rely on human-crafted Exploratory Landscape Analysis features to inform the meta-level agent about the low-level optimization progress. To address the gap, this paper proposes Neural Exploratory Landscape Analysis (NeurELA), a novel framework that dynamically pr","authors_text":"Hongshu Guo, Jiacheng Chen, Yue-Jiao Gong, Zeyuan Ma","cross_cats":["cs.NE"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-20T09:17:11Z","title":"Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.10672","kind":"arxiv","version":3},"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:e2092e6cef8ba2c30e18303a235916ccfed94e3fa1b68a274c8ac11ccbe88334","target":"record","created_at":"2026-07-05T10:39:46Z","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":"4d55146ed5fa196ead1e3db35a537a1f58d6617ac51e7dcde63bd84f55d28171","cross_cats_sorted":["cs.NE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-20T09:17:11Z","title_canon_sha256":"e29bbd3c55fe596f9820b827f209186e927c290c0fc1ab43dad01ac890101624"},"schema_version":"1.0","source":{"id":"2408.10672","kind":"arxiv","version":3}},"canonical_sha256":"d6fccaea82f822701a00c44fab3dd61e8c92c8063e892ffe697550f404454b31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6fccaea82f822701a00c44fab3dd61e8c92c8063e892ffe697550f404454b31","first_computed_at":"2026-07-05T10:39:46.080231Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:39:46.080231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KM/dCES4TIYv4kl4yJIuObgC74rwwijS6ZaIJLhXd6nJMbL8HoQ32RIBolqsVQry9lv7Wqh/dkisILwiJgaHDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:39:46.080754Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.10672","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e2092e6cef8ba2c30e18303a235916ccfed94e3fa1b68a274c8ac11ccbe88334","sha256:27688b478d0ee228621faf47288b710131e0af31e8a65f217bac91e4e3a9a5fd"],"state_sha256":"78f5b6584ef3f6cd5c258f4f33bddb80aca663f812fe1ec625a15a179d4edcf2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gHzIoBiuWYgXojs++1CuX8Lc1uXPTVjqOpHVG31zNVDXIMoZBkzULsvOduOmrTupX9gtjFzVXYBHs9+oyJaqAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T09:18:51.632415Z","bundle_sha256":"d76af5795386b39b4ca136a25981f6d617f4b8f14b2a24475ab445a099bdcb3b"}}