{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:27TIYADU7Z6UCYYOVVDN72GONT","short_pith_number":"pith:27TIYADU","canonical_record":{"source":{"id":"1606.07829","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-24T20:17:44Z","cross_cats_sorted":[],"title_canon_sha256":"eaf2f67bb9519c3d8677ecde730e8c34637639559fb72e4b1057636070aa6664","abstract_canon_sha256":"47ed29ce2caefe6247b832ec482d7161795e067b6e6d5dad47da0aab324bc1f0"},"schema_version":"1.0"},"canonical_sha256":"d7e68c0074fe7d41630ead46dfe8ce6cdaa6b4897315e1b79e09c480e5f93cda","source":{"kind":"arxiv","id":"1606.07829","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.07829","created_at":"2026-05-18T01:11:54Z"},{"alias_kind":"arxiv_version","alias_value":"1606.07829v1","created_at":"2026-05-18T01:11:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.07829","created_at":"2026-05-18T01:11:54Z"},{"alias_kind":"pith_short_12","alias_value":"27TIYADU7Z6U","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_16","alias_value":"27TIYADU7Z6UCYYO","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_8","alias_value":"27TIYADU","created_at":"2026-05-18T12:29:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:27TIYADU7Z6UCYYOVVDN72GONT","target":"record","payload":{"canonical_record":{"source":{"id":"1606.07829","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-24T20:17:44Z","cross_cats_sorted":[],"title_canon_sha256":"eaf2f67bb9519c3d8677ecde730e8c34637639559fb72e4b1057636070aa6664","abstract_canon_sha256":"47ed29ce2caefe6247b832ec482d7161795e067b6e6d5dad47da0aab324bc1f0"},"schema_version":"1.0"},"canonical_sha256":"d7e68c0074fe7d41630ead46dfe8ce6cdaa6b4897315e1b79e09c480e5f93cda","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:54.318115Z","signature_b64":"DZyGv7srqozndjAkBNQSV6AgwyYimW23wWxnDQHBBVjyyYWhroHv5x2snHdsbP3zSgGBBQDq+SlTOgFrI7VuAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d7e68c0074fe7d41630ead46dfe8ce6cdaa6b4897315e1b79e09c480e5f93cda","last_reissued_at":"2026-05-18T01:11:54.317783Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:54.317783Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1606.07829","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":"2026-05-18T01:11:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vHrHWXozqIhBvs5Gu7w38zVnvQKiXPMBsU0y8u2ZJ/s7bhsZTsEGSlzI4+Et/J/kNwJi2R5OWyTvnQ6egmCFAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T02:18:21.985077Z"},"content_sha256":"e9de1772ddf24142d4504085739d2f4cee71d9e3923814ebc081a32522a072b3","schema_version":"1.0","event_id":"sha256:e9de1772ddf24142d4504085739d2f4cee71d9e3923814ebc081a32522a072b3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:27TIYADU7Z6UCYYOVVDN72GONT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Topic Modeling Approaches to Decision Summarization in Spoken Meetings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Claire Cardie, Lu Wang","submitted_at":"2016-06-24T20:17:44Z","abstract_excerpt":"We present a token-level decision summarization framework that utilizes the latent topic structures of utterances to identify \"summary-worthy\" words. Concretely, a series of unsupervised topic models is explored and experimental results show that fine-grained topic models, which discover topics at the utterance-level rather than the document-level, can better identify the gist of the decision-making process. Moreover, our proposed token-level summarization approach, which is able to remove redundancies within utterances, outperforms existing utterance ranking based summarization methods. Final"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.07829","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":"2026-05-18T01:11:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YXeFHhUOOllkIHoScif8Y3rTBmrl79xXXR/dni48X52rPp4zaSfp74JfxLuS2uEBUjs6BDwwQk1QXZeZDbPVBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T02:18:21.985745Z"},"content_sha256":"bd301bb7b2bc2a2e469896c9e45d2d0fdeb1ec50fa01faebd8cf56feb0dac48d","schema_version":"1.0","event_id":"sha256:bd301bb7b2bc2a2e469896c9e45d2d0fdeb1ec50fa01faebd8cf56feb0dac48d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/27TIYADU7Z6UCYYOVVDN72GONT/bundle.json","state_url":"https://pith.science/pith/27TIYADU7Z6UCYYOVVDN72GONT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/27TIYADU7Z6UCYYOVVDN72GONT/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":"2026-05-31T02:18:21Z","links":{"resolver":"https://pith.science/pith/27TIYADU7Z6UCYYOVVDN72GONT","bundle":"https://pith.science/pith/27TIYADU7Z6UCYYOVVDN72GONT/bundle.json","state":"https://pith.science/pith/27TIYADU7Z6UCYYOVVDN72GONT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/27TIYADU7Z6UCYYOVVDN72GONT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:27TIYADU7Z6UCYYOVVDN72GONT","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":"47ed29ce2caefe6247b832ec482d7161795e067b6e6d5dad47da0aab324bc1f0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-24T20:17:44Z","title_canon_sha256":"eaf2f67bb9519c3d8677ecde730e8c34637639559fb72e4b1057636070aa6664"},"schema_version":"1.0","source":{"id":"1606.07829","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.07829","created_at":"2026-05-18T01:11:54Z"},{"alias_kind":"arxiv_version","alias_value":"1606.07829v1","created_at":"2026-05-18T01:11:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.07829","created_at":"2026-05-18T01:11:54Z"},{"alias_kind":"pith_short_12","alias_value":"27TIYADU7Z6U","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_16","alias_value":"27TIYADU7Z6UCYYO","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_8","alias_value":"27TIYADU","created_at":"2026-05-18T12:29:52Z"}],"graph_snapshots":[{"event_id":"sha256:bd301bb7b2bc2a2e469896c9e45d2d0fdeb1ec50fa01faebd8cf56feb0dac48d","target":"graph","created_at":"2026-05-18T01:11:54Z","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":"We present a token-level decision summarization framework that utilizes the latent topic structures of utterances to identify \"summary-worthy\" words. Concretely, a series of unsupervised topic models is explored and experimental results show that fine-grained topic models, which discover topics at the utterance-level rather than the document-level, can better identify the gist of the decision-making process. Moreover, our proposed token-level summarization approach, which is able to remove redundancies within utterances, outperforms existing utterance ranking based summarization methods. Final","authors_text":"Claire Cardie, Lu Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-24T20:17:44Z","title":"Unsupervised Topic Modeling Approaches to Decision Summarization in Spoken Meetings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.07829","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:e9de1772ddf24142d4504085739d2f4cee71d9e3923814ebc081a32522a072b3","target":"record","created_at":"2026-05-18T01:11:54Z","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":"47ed29ce2caefe6247b832ec482d7161795e067b6e6d5dad47da0aab324bc1f0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-24T20:17:44Z","title_canon_sha256":"eaf2f67bb9519c3d8677ecde730e8c34637639559fb72e4b1057636070aa6664"},"schema_version":"1.0","source":{"id":"1606.07829","kind":"arxiv","version":1}},"canonical_sha256":"d7e68c0074fe7d41630ead46dfe8ce6cdaa6b4897315e1b79e09c480e5f93cda","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7e68c0074fe7d41630ead46dfe8ce6cdaa6b4897315e1b79e09c480e5f93cda","first_computed_at":"2026-05-18T01:11:54.317783Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:11:54.317783Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DZyGv7srqozndjAkBNQSV6AgwyYimW23wWxnDQHBBVjyyYWhroHv5x2snHdsbP3zSgGBBQDq+SlTOgFrI7VuAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:11:54.318115Z","signed_message":"canonical_sha256_bytes"},"source_id":"1606.07829","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e9de1772ddf24142d4504085739d2f4cee71d9e3923814ebc081a32522a072b3","sha256:bd301bb7b2bc2a2e469896c9e45d2d0fdeb1ec50fa01faebd8cf56feb0dac48d"],"state_sha256":"a304c04f3ff29c83f7533575cda406d69322e11a79593883cfcb1253200e096e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9v6hSbUNgfc3X/7yuN1/eQhyjJoNCd8Fa2vsTog09VvNm8qbi94oESK1s2hWsieb2Wa3iiTa7eotRVbYO4bjAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T02:18:21.990674Z","bundle_sha256":"fce2a2c5b46c7e8bd4d5c5bd8cf41a5abeef894f7bfbdd0e77485b536cad4c65"}}