{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:EAYPWJ76F3C5Q7OINZ7EXWZFTE","short_pith_number":"pith:EAYPWJ76","canonical_record":{"source":{"id":"1611.09921","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-11-29T22:24:30Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"92c41403737c2aa21a6dce16c6ccea5ddb030f008437d6894ad9b9334393b73e","abstract_canon_sha256":"bc78c7748472422d2bb5a53f3d26794e0f254afba33838feaad1eaeee0aa150a"},"schema_version":"1.0"},"canonical_sha256":"2030fb27fe2ec5d87dc86e7e4bdb25991699197e13b13840fe9050b587711a98","source":{"kind":"arxiv","id":"1611.09921","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.09921","created_at":"2026-05-18T00:56:07Z"},{"alias_kind":"arxiv_version","alias_value":"1611.09921v2","created_at":"2026-05-18T00:56:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.09921","created_at":"2026-05-18T00:56:07Z"},{"alias_kind":"pith_short_12","alias_value":"EAYPWJ76F3C5","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"EAYPWJ76F3C5Q7OI","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"EAYPWJ76","created_at":"2026-05-18T12:30:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:EAYPWJ76F3C5Q7OINZ7EXWZFTE","target":"record","payload":{"canonical_record":{"source":{"id":"1611.09921","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-11-29T22:24:30Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"92c41403737c2aa21a6dce16c6ccea5ddb030f008437d6894ad9b9334393b73e","abstract_canon_sha256":"bc78c7748472422d2bb5a53f3d26794e0f254afba33838feaad1eaeee0aa150a"},"schema_version":"1.0"},"canonical_sha256":"2030fb27fe2ec5d87dc86e7e4bdb25991699197e13b13840fe9050b587711a98","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:56:07.062504Z","signature_b64":"dHwqwVBofMqD1cCgo7lqtZddLxLgL6MM1B7msAPP40MO1/YS2+OFjOCt95EwVGkkZkRfzL+9ufwBRIhkcccbDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2030fb27fe2ec5d87dc86e7e4bdb25991699197e13b13840fe9050b587711a98","last_reissued_at":"2026-05-18T00:56:07.061771Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:56:07.061771Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.09921","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:56:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RbZA4GJVRdnsV4p/hSVexs5ofAWtbciiWLDUKOy3ltD2XGHX5DXuEkWVXedlna0HgtH17UytKSRwd58TC8u8AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:29:33.778928Z"},"content_sha256":"75d90985bff34f10305fcdee6eb00e564999485d1f8be8b278f33a146f21f182","schema_version":"1.0","event_id":"sha256:75d90985bff34f10305fcdee6eb00e564999485d1f8be8b278f33a146f21f182"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:EAYPWJ76F3C5Q7OINZ7EXWZFTE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Less is More: Learning Prominent and Diverse Topics for Data Summarization","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.IR"],"primary_cat":"cs.LG","authors_text":"Cheng Li, Jian Tang, Ming Zhang, Qiaozhu Mei","submitted_at":"2016-11-29T22:24:30Z","abstract_excerpt":"Statistical topic models efficiently facilitate the exploration of large-scale data sets. Many models have been developed and broadly used to summarize the semantic structure in news, science, social media, and digital humanities. However, a common and practical objective in data exploration tasks is not to enumerate all existing topics, but to quickly extract representative ones that broadly cover the content of the corpus, i.e., a few topics that serve as a good summary of the data. Most existing topic models fit exactly the same number of topics as a user specifies, which have imposed an un"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.09921","kind":"arxiv","version":2},"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":"2026-05-18T00:56:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"He/yq9dmx9gsfWOIgWqJuriXfpgo8yHaqTQtLqpsXisr3ICJ2KJkJsl7dQ7cnlao/p8Dnw28zAD/fJlKr4PQBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:29:33.779357Z"},"content_sha256":"7229f7394ead7b24e7aa45d0f6c1f9c913db9620afee0f87c31a8e054f2e68ec","schema_version":"1.0","event_id":"sha256:7229f7394ead7b24e7aa45d0f6c1f9c913db9620afee0f87c31a8e054f2e68ec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EAYPWJ76F3C5Q7OINZ7EXWZFTE/bundle.json","state_url":"https://pith.science/pith/EAYPWJ76F3C5Q7OINZ7EXWZFTE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EAYPWJ76F3C5Q7OINZ7EXWZFTE/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":"2026-05-31T21:29:33Z","links":{"resolver":"https://pith.science/pith/EAYPWJ76F3C5Q7OINZ7EXWZFTE","bundle":"https://pith.science/pith/EAYPWJ76F3C5Q7OINZ7EXWZFTE/bundle.json","state":"https://pith.science/pith/EAYPWJ76F3C5Q7OINZ7EXWZFTE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EAYPWJ76F3C5Q7OINZ7EXWZFTE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:EAYPWJ76F3C5Q7OINZ7EXWZFTE","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":"bc78c7748472422d2bb5a53f3d26794e0f254afba33838feaad1eaeee0aa150a","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-11-29T22:24:30Z","title_canon_sha256":"92c41403737c2aa21a6dce16c6ccea5ddb030f008437d6894ad9b9334393b73e"},"schema_version":"1.0","source":{"id":"1611.09921","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.09921","created_at":"2026-05-18T00:56:07Z"},{"alias_kind":"arxiv_version","alias_value":"1611.09921v2","created_at":"2026-05-18T00:56:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.09921","created_at":"2026-05-18T00:56:07Z"},{"alias_kind":"pith_short_12","alias_value":"EAYPWJ76F3C5","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"EAYPWJ76F3C5Q7OI","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"EAYPWJ76","created_at":"2026-05-18T12:30:12Z"}],"graph_snapshots":[{"event_id":"sha256:7229f7394ead7b24e7aa45d0f6c1f9c913db9620afee0f87c31a8e054f2e68ec","target":"graph","created_at":"2026-05-18T00:56:07Z","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":"Statistical topic models efficiently facilitate the exploration of large-scale data sets. Many models have been developed and broadly used to summarize the semantic structure in news, science, social media, and digital humanities. However, a common and practical objective in data exploration tasks is not to enumerate all existing topics, but to quickly extract representative ones that broadly cover the content of the corpus, i.e., a few topics that serve as a good summary of the data. Most existing topic models fit exactly the same number of topics as a user specifies, which have imposed an un","authors_text":"Cheng Li, Jian Tang, Ming Zhang, Qiaozhu Mei","cross_cats":["cs.CL","cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-11-29T22:24:30Z","title":"Less is More: Learning Prominent and Diverse Topics for Data Summarization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.09921","kind":"arxiv","version":2},"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":"sha256:75d90985bff34f10305fcdee6eb00e564999485d1f8be8b278f33a146f21f182","target":"record","created_at":"2026-05-18T00:56:07Z","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":"bc78c7748472422d2bb5a53f3d26794e0f254afba33838feaad1eaeee0aa150a","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-11-29T22:24:30Z","title_canon_sha256":"92c41403737c2aa21a6dce16c6ccea5ddb030f008437d6894ad9b9334393b73e"},"schema_version":"1.0","source":{"id":"1611.09921","kind":"arxiv","version":2}},"canonical_sha256":"2030fb27fe2ec5d87dc86e7e4bdb25991699197e13b13840fe9050b587711a98","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2030fb27fe2ec5d87dc86e7e4bdb25991699197e13b13840fe9050b587711a98","first_computed_at":"2026-05-18T00:56:07.061771Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:56:07.061771Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dHwqwVBofMqD1cCgo7lqtZddLxLgL6MM1B7msAPP40MO1/YS2+OFjOCt95EwVGkkZkRfzL+9ufwBRIhkcccbDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:56:07.062504Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.09921","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75d90985bff34f10305fcdee6eb00e564999485d1f8be8b278f33a146f21f182","sha256:7229f7394ead7b24e7aa45d0f6c1f9c913db9620afee0f87c31a8e054f2e68ec"],"state_sha256":"0d5a85ca87b347db10dc76700f62325bdd2733266897b176643175703d71acf5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4mMF+jeTCMIXiGEeZ7Z2D8HUKbs9IBrhbHnOZZvzG6y35kPmiKpNJwpaHp5geeWXhq6kbcjMiPg4yQqbRRBeCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T21:29:33.781811Z","bundle_sha256":"e78f483a3c1cc7c2892bcbcaf80210b8e7531958cc29f8a0bdf3d752d3ccdd70"}}