{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:DXPTOQ4W6CVUUZDX4N2LFRHRMA","short_pith_number":"pith:DXPTOQ4W","canonical_record":{"source":{"id":"1507.02351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-07-09T02:31:20Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"ce593cdebc4df2bd3e242549bfeba69b6078d9e6e5db5da808090d933090be96","abstract_canon_sha256":"6f1b925c946fc40c81b27ad3b0d0306a1ad698391c24611f56c658c9072f1276"},"schema_version":"1.0"},"canonical_sha256":"1ddf374396f0ab4a6477e374b2c4f1603aa4c10810b969cd044d0a3d7bbc6d2b","source":{"kind":"arxiv","id":"1507.02351","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1507.02351","created_at":"2026-05-18T01:37:06Z"},{"alias_kind":"arxiv_version","alias_value":"1507.02351v1","created_at":"2026-05-18T01:37:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1507.02351","created_at":"2026-05-18T01:37:06Z"},{"alias_kind":"pith_short_12","alias_value":"DXPTOQ4W6CVU","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_16","alias_value":"DXPTOQ4W6CVUUZDX","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_8","alias_value":"DXPTOQ4W","created_at":"2026-05-18T12:29:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:DXPTOQ4W6CVUUZDX4N2LFRHRMA","target":"record","payload":{"canonical_record":{"source":{"id":"1507.02351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-07-09T02:31:20Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"ce593cdebc4df2bd3e242549bfeba69b6078d9e6e5db5da808090d933090be96","abstract_canon_sha256":"6f1b925c946fc40c81b27ad3b0d0306a1ad698391c24611f56c658c9072f1276"},"schema_version":"1.0"},"canonical_sha256":"1ddf374396f0ab4a6477e374b2c4f1603aa4c10810b969cd044d0a3d7bbc6d2b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:37:06.932946Z","signature_b64":"UDfLxwpYIm4geZpVsSD34FC6xfntxCAu6Oc1kqJVIRZ6c5I6vdsk6PiEgWvM59/pbDmZLIpd1BJxURusBs2lAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1ddf374396f0ab4a6477e374b2c4f1603aa4c10810b969cd044d0a3d7bbc6d2b","last_reissued_at":"2026-05-18T01:37:06.932500Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:37:06.932500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1507.02351","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":"2026-05-18T01:37:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nQRlo0i7XTPEwvhN3q497+2oTDcILof9Tcil39EEH+T/8qgQjDVvIC3xjsx2LEiqUZvVxWbZrZ02FBjce6IqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T02:51:24.575948Z"},"content_sha256":"d84c7b7cb00b1fa0c68978ae314e1955312d5ff13c59e8f6e9cdd78291938316","schema_version":"1.0","event_id":"sha256:d84c7b7cb00b1fa0c68978ae314e1955312d5ff13c59e8f6e9cdd78291938316"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:DXPTOQ4W6CVUUZDX4N2LFRHRMA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Locally Adaptive Optimization: Adaptive Seeding for Monotone Submodular Functions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.SI","authors_text":"Ashwinkumar Badanidiyuru, Aviad Rubinstein, Christos Papadimitriou, Lior Seeman, Yaron Singer","submitted_at":"2015-07-09T02:31:20Z","abstract_excerpt":"The Adaptive Seeding problem is an algorithmic challenge motivated by influence maximization in social networks: One seeks to select among certain accessible nodes in a network, and then select, adaptively, among neighbors of those nodes as they become accessible in order to maximize a global objective function. More generally, adaptive seeding is a stochastic optimization framework where the choices in the first stage affect the realizations in the second stage, over which we aim to optimize.\n  Our main result is a $(1-1/e)^2$-approximation for the adaptive seeding problem for any monotone su"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.02351","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":""},"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":"2026-05-18T01:37:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XNV/N6YWStrnoIQqNb8SdcGOjdL3JhsbliaFV/tAYur2O/rb4/Wrn+jIi0OJdPjLhumO3ZdBBCyCvJ8A7qknDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T02:51:24.576762Z"},"content_sha256":"c427db87aa1b973a95fcbd551800f485863f08c40b54b619ea6740434fbe76c2","schema_version":"1.0","event_id":"sha256:c427db87aa1b973a95fcbd551800f485863f08c40b54b619ea6740434fbe76c2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DXPTOQ4W6CVUUZDX4N2LFRHRMA/bundle.json","state_url":"https://pith.science/pith/DXPTOQ4W6CVUUZDX4N2LFRHRMA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DXPTOQ4W6CVUUZDX4N2LFRHRMA/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":"2026-05-31T02:51:24Z","links":{"resolver":"https://pith.science/pith/DXPTOQ4W6CVUUZDX4N2LFRHRMA","bundle":"https://pith.science/pith/DXPTOQ4W6CVUUZDX4N2LFRHRMA/bundle.json","state":"https://pith.science/pith/DXPTOQ4W6CVUUZDX4N2LFRHRMA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DXPTOQ4W6CVUUZDX4N2LFRHRMA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:DXPTOQ4W6CVUUZDX4N2LFRHRMA","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":"6f1b925c946fc40c81b27ad3b0d0306a1ad698391c24611f56c658c9072f1276","cross_cats_sorted":["cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-07-09T02:31:20Z","title_canon_sha256":"ce593cdebc4df2bd3e242549bfeba69b6078d9e6e5db5da808090d933090be96"},"schema_version":"1.0","source":{"id":"1507.02351","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1507.02351","created_at":"2026-05-18T01:37:06Z"},{"alias_kind":"arxiv_version","alias_value":"1507.02351v1","created_at":"2026-05-18T01:37:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1507.02351","created_at":"2026-05-18T01:37:06Z"},{"alias_kind":"pith_short_12","alias_value":"DXPTOQ4W6CVU","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_16","alias_value":"DXPTOQ4W6CVUUZDX","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_8","alias_value":"DXPTOQ4W","created_at":"2026-05-18T12:29:17Z"}],"graph_snapshots":[{"event_id":"sha256:c427db87aa1b973a95fcbd551800f485863f08c40b54b619ea6740434fbe76c2","target":"graph","created_at":"2026-05-18T01:37:06Z","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"},"paper":{"abstract_excerpt":"The Adaptive Seeding problem is an algorithmic challenge motivated by influence maximization in social networks: One seeks to select among certain accessible nodes in a network, and then select, adaptively, among neighbors of those nodes as they become accessible in order to maximize a global objective function. More generally, adaptive seeding is a stochastic optimization framework where the choices in the first stage affect the realizations in the second stage, over which we aim to optimize.\n  Our main result is a $(1-1/e)^2$-approximation for the adaptive seeding problem for any monotone su","authors_text":"Ashwinkumar Badanidiyuru, Aviad Rubinstein, Christos Papadimitriou, Lior Seeman, Yaron Singer","cross_cats":["cs.DS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-07-09T02:31:20Z","title":"Locally Adaptive Optimization: Adaptive Seeding for Monotone Submodular Functions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.02351","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:d84c7b7cb00b1fa0c68978ae314e1955312d5ff13c59e8f6e9cdd78291938316","target":"record","created_at":"2026-05-18T01:37:06Z","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":"6f1b925c946fc40c81b27ad3b0d0306a1ad698391c24611f56c658c9072f1276","cross_cats_sorted":["cs.DS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2015-07-09T02:31:20Z","title_canon_sha256":"ce593cdebc4df2bd3e242549bfeba69b6078d9e6e5db5da808090d933090be96"},"schema_version":"1.0","source":{"id":"1507.02351","kind":"arxiv","version":1}},"canonical_sha256":"1ddf374396f0ab4a6477e374b2c4f1603aa4c10810b969cd044d0a3d7bbc6d2b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1ddf374396f0ab4a6477e374b2c4f1603aa4c10810b969cd044d0a3d7bbc6d2b","first_computed_at":"2026-05-18T01:37:06.932500Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:37:06.932500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UDfLxwpYIm4geZpVsSD34FC6xfntxCAu6Oc1kqJVIRZ6c5I6vdsk6PiEgWvM59/pbDmZLIpd1BJxURusBs2lAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:37:06.932946Z","signed_message":"canonical_sha256_bytes"},"source_id":"1507.02351","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d84c7b7cb00b1fa0c68978ae314e1955312d5ff13c59e8f6e9cdd78291938316","sha256:c427db87aa1b973a95fcbd551800f485863f08c40b54b619ea6740434fbe76c2"],"state_sha256":"c2c92c2839ea0a7b8ba4ac24e77b6e809873d9c8e63b8ea909c5b459bffb850e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jtAWDhIFrZRPhNak1naqLMFtDxOSvpeYkJjg7EKhV/tf4FqYuhUntF01MiVUU7Q2yj1zTHzChvSMr9qeSkDcBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T02:51:24.580270Z","bundle_sha256":"be4c15164f31367bea19614ff09d324199697cb6a0c8f069c8ad5f60a67c9adf"}}