{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:L47ZTGDOCPL3GPALVOPAXMLZZN","short_pith_number":"pith:L47ZTGDO","canonical_record":{"source":{"id":"2106.05065","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T13:35:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ef61a792a40b21b97a992cebb9bdb8dce1a7e5fa550fe095abc1358aa63ab810","abstract_canon_sha256":"e304353648fec1d116bfebfabaffc57b7e7bb67c6ff02618b35f9c48c31f0195"},"schema_version":"1.0"},"canonical_sha256":"5f3f99986e13d7b33c0bab9e0bb179cb690cba43bb86d101db42b9b3cdb62c52","source":{"kind":"arxiv","id":"2106.05065","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.05065","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"arxiv_version","alias_value":"2106.05065v1","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.05065","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"pith_short_12","alias_value":"L47ZTGDOCPL3","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"pith_short_16","alias_value":"L47ZTGDOCPL3GPAL","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"pith_short_8","alias_value":"L47ZTGDO","created_at":"2026-07-05T02:47:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:L47ZTGDOCPL3GPALVOPAXMLZZN","target":"record","payload":{"canonical_record":{"source":{"id":"2106.05065","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T13:35:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ef61a792a40b21b97a992cebb9bdb8dce1a7e5fa550fe095abc1358aa63ab810","abstract_canon_sha256":"e304353648fec1d116bfebfabaffc57b7e7bb67c6ff02618b35f9c48c31f0195"},"schema_version":"1.0"},"canonical_sha256":"5f3f99986e13d7b33c0bab9e0bb179cb690cba43bb86d101db42b9b3cdb62c52","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:47:52.388930Z","signature_b64":"ZOQeKrFE2u2QNhM/FsXNSrKqV1O3/9BKGk8LDO+a+wQ3OzdqwqdVxXlrahlthbDoGwLnhwaWVCHSKSch+McCDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f3f99986e13d7b33c0bab9e0bb179cb690cba43bb86d101db42b9b3cdb62c52","last_reissued_at":"2026-07-05T02:47:52.388586Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:47:52.388586Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.05065","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":"2026-07-05T02:47:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Li+81PoLPGMi9gnVuhRZEucvGUiDSWdTMUJkOYjca5E6/7ur84glZyHKCKMce9Pu6/RyoGdvHhwYhhotzzZCAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:20:17.388324Z"},"content_sha256":"f2804ddc897a021c057d62f5ce07041177aa2cac5d8e6c508ce07487751ff05b","schema_version":"1.0","event_id":"sha256:f2804ddc897a021c057d62f5ce07041177aa2cac5d8e6c508ce07487751ff05b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:L47ZTGDOCPL3GPALVOPAXMLZZN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jinhang Zuo, John C.S. Lui, Wei Chen, Xiaowei Chen, Xutong Liu","submitted_at":"2021-06-09T13:35:39Z","abstract_excerpt":"Multi-layered network exploration (MuLaNE) problem is an important problem abstracted from many applications. In MuLaNE, there are multiple network layers where each node has an importance weight and each layer is explored by a random walk. The MuLaNE task is to allocate total random walk budget $B$ into each network layer so that the total weights of the unique nodes visited by random walks are maximized. We systematically study this problem from offline optimization to online learning. For the offline optimization setting where the network structure and node weights are known, we provide gre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.05065","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/2106.05065/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":"2026-07-05T02:47:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O2hfUTbYWeYuB/RIHgqFsUJyK6sH/gwuS9miGnZsUKyDpBIKlTjl5e/3Xzbu0VmfEdjiWpRPaQFma5o/FjYZAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:20:17.388868Z"},"content_sha256":"7353ffcc5e8cb6188fdd75f1323a848f02d8c29904c7e3f3a7c2f57a668ade54","schema_version":"1.0","event_id":"sha256:7353ffcc5e8cb6188fdd75f1323a848f02d8c29904c7e3f3a7c2f57a668ade54"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L47ZTGDOCPL3GPALVOPAXMLZZN/bundle.json","state_url":"https://pith.science/pith/L47ZTGDOCPL3GPALVOPAXMLZZN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L47ZTGDOCPL3GPALVOPAXMLZZN/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":"2026-08-06T19:20:17Z","links":{"resolver":"https://pith.science/pith/L47ZTGDOCPL3GPALVOPAXMLZZN","bundle":"https://pith.science/pith/L47ZTGDOCPL3GPALVOPAXMLZZN/bundle.json","state":"https://pith.science/pith/L47ZTGDOCPL3GPALVOPAXMLZZN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L47ZTGDOCPL3GPALVOPAXMLZZN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:L47ZTGDOCPL3GPALVOPAXMLZZN","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":"e304353648fec1d116bfebfabaffc57b7e7bb67c6ff02618b35f9c48c31f0195","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T13:35:39Z","title_canon_sha256":"ef61a792a40b21b97a992cebb9bdb8dce1a7e5fa550fe095abc1358aa63ab810"},"schema_version":"1.0","source":{"id":"2106.05065","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.05065","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"arxiv_version","alias_value":"2106.05065v1","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.05065","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"pith_short_12","alias_value":"L47ZTGDOCPL3","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"pith_short_16","alias_value":"L47ZTGDOCPL3GPAL","created_at":"2026-07-05T02:47:52Z"},{"alias_kind":"pith_short_8","alias_value":"L47ZTGDO","created_at":"2026-07-05T02:47:52Z"}],"graph_snapshots":[{"event_id":"sha256:7353ffcc5e8cb6188fdd75f1323a848f02d8c29904c7e3f3a7c2f57a668ade54","target":"graph","created_at":"2026-07-05T02:47:52Z","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/2106.05065/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-layered network exploration (MuLaNE) problem is an important problem abstracted from many applications. In MuLaNE, there are multiple network layers where each node has an importance weight and each layer is explored by a random walk. The MuLaNE task is to allocate total random walk budget $B$ into each network layer so that the total weights of the unique nodes visited by random walks are maximized. We systematically study this problem from offline optimization to online learning. For the offline optimization setting where the network structure and node weights are known, we provide gre","authors_text":"Jinhang Zuo, John C.S. Lui, Wei Chen, Xiaowei Chen, Xutong Liu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T13:35:39Z","title":"Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.05065","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:f2804ddc897a021c057d62f5ce07041177aa2cac5d8e6c508ce07487751ff05b","target":"record","created_at":"2026-07-05T02:47:52Z","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":"e304353648fec1d116bfebfabaffc57b7e7bb67c6ff02618b35f9c48c31f0195","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-09T13:35:39Z","title_canon_sha256":"ef61a792a40b21b97a992cebb9bdb8dce1a7e5fa550fe095abc1358aa63ab810"},"schema_version":"1.0","source":{"id":"2106.05065","kind":"arxiv","version":1}},"canonical_sha256":"5f3f99986e13d7b33c0bab9e0bb179cb690cba43bb86d101db42b9b3cdb62c52","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f3f99986e13d7b33c0bab9e0bb179cb690cba43bb86d101db42b9b3cdb62c52","first_computed_at":"2026-07-05T02:47:52.388586Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:47:52.388586Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZOQeKrFE2u2QNhM/FsXNSrKqV1O3/9BKGk8LDO+a+wQ3OzdqwqdVxXlrahlthbDoGwLnhwaWVCHSKSch+McCDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:47:52.388930Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.05065","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f2804ddc897a021c057d62f5ce07041177aa2cac5d8e6c508ce07487751ff05b","sha256:7353ffcc5e8cb6188fdd75f1323a848f02d8c29904c7e3f3a7c2f57a668ade54"],"state_sha256":"908907ca8c64233c2b0ae34f3c2a362470398a71809fee3c7c6f6b4e185f325a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nn40XHqEXz11ls7ypuNmrJKpS2vG4EE899dPOsXFphVOVCjDTJism6OYmrCGGCIcLMV2AX/zmqqMcwUZiuSOAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:20:17.392841Z","bundle_sha256":"97b835e3dc43a698a8389abbe47753fa5ba83788a22f8a2859ae3762bb9992a4"}}