{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JRM33VWPSFRX7EYX5343WYEDKB","short_pith_number":"pith:JRM33VWP","canonical_record":{"source":{"id":"2408.00205","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-01T00:18:21Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"3d07660c7fe7352af2cb56978860de708c229fbd04953026dc2bfa9cbbf2269a","abstract_canon_sha256":"61b19d4423117a494a8c86dcd0de639b517eba06757ee8d4944c2d1126f79c5e"},"schema_version":"1.0"},"canonical_sha256":"4c59bdd6cf91637f9317eef9bb6083507d00e7c4032001bb6d87764d5b804358","source":{"kind":"arxiv","id":"2408.00205","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.00205","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"arxiv_version","alias_value":"2408.00205v1","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.00205","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"pith_short_12","alias_value":"JRM33VWPSFRX","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"pith_short_16","alias_value":"JRM33VWPSFRX7EYX","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"pith_short_8","alias_value":"JRM33VWP","created_at":"2026-07-05T08:51:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JRM33VWPSFRX7EYX5343WYEDKB","target":"record","payload":{"canonical_record":{"source":{"id":"2408.00205","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-01T00:18:21Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"3d07660c7fe7352af2cb56978860de708c229fbd04953026dc2bfa9cbbf2269a","abstract_canon_sha256":"61b19d4423117a494a8c86dcd0de639b517eba06757ee8d4944c2d1126f79c5e"},"schema_version":"1.0"},"canonical_sha256":"4c59bdd6cf91637f9317eef9bb6083507d00e7c4032001bb6d87764d5b804358","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:51:00.028079Z","signature_b64":"peTBrccJGUrX+raBiV3aRxIQF6CTtSCw5sBkYrl8wDIHAfVTpY+CkjRJ9JNq5HNIswy1zwdfKMLpQcKFSgUhBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4c59bdd6cf91637f9317eef9bb6083507d00e7c4032001bb6d87764d5b804358","last_reissued_at":"2026-07-05T08:51:00.027618Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:51:00.027618Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.00205","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":"2026-07-05T08:51:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8POQQoC6E4u2BiM2dqJB/yUxP1Ze/nMAiNoQPSFTrUGBkVRXAXOeUIIb0DJUzWmpquizYQiSn0Z1EEXLzELvDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T12:01:51.240212Z"},"content_sha256":"6f210012d36f26dcdebeb90ddd01cdade8611e87d3def6c3fe14c71a0f9833bd","schema_version":"1.0","event_id":"sha256:6f210012d36f26dcdebeb90ddd01cdade8611e87d3def6c3fe14c71a0f9833bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JRM33VWPSFRX7EYX5343WYEDKB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sentence-wise Speech Summarization: Task, Datasets, and End-to-End Modeling with LM Knowledge Distillation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.CL","authors_text":"Atsunori Ogawa, Kohei Matsuura, Marc Delcroix, Masato Mimura, Takafumi Moriya, Takanori Ashihara, Takatomo Kano","submitted_at":"2024-08-01T00:18:21Z","abstract_excerpt":"This paper introduces a novel approach called sentence-wise speech summarization (Sen-SSum), which generates text summaries from a spoken document in a sentence-by-sentence manner. Sen-SSum combines the real-time processing of automatic speech recognition (ASR) with the conciseness of speech summarization. To explore this approach, we present two datasets for Sen-SSum: Mega-SSum and CSJ-SSum. Using these datasets, our study evaluates two types of Transformer-based models: 1) cascade models that combine ASR and strong text summarization models, and 2) end-to-end (E2E) models that directly conve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.00205","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/2408.00205/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":"2026-07-05T08:51:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+K3F1zcFUUAY/R7tKaqYLV4/oY9CvZgE1LtJe+3xOJ5zy0H8bE6TJBxFbC5mPqnHKbhPqYMTXPzTugd9qj5aDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T12:01:51.240592Z"},"content_sha256":"f395399e3fbef5828a7d6c7489c42fd03399ae89a9c0c0fae3d068f2b18b1090","schema_version":"1.0","event_id":"sha256:f395399e3fbef5828a7d6c7489c42fd03399ae89a9c0c0fae3d068f2b18b1090"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JRM33VWPSFRX7EYX5343WYEDKB/bundle.json","state_url":"https://pith.science/pith/JRM33VWPSFRX7EYX5343WYEDKB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JRM33VWPSFRX7EYX5343WYEDKB/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":"2026-07-14T12:01:51Z","links":{"resolver":"https://pith.science/pith/JRM33VWPSFRX7EYX5343WYEDKB","bundle":"https://pith.science/pith/JRM33VWPSFRX7EYX5343WYEDKB/bundle.json","state":"https://pith.science/pith/JRM33VWPSFRX7EYX5343WYEDKB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JRM33VWPSFRX7EYX5343WYEDKB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JRM33VWPSFRX7EYX5343WYEDKB","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":"61b19d4423117a494a8c86dcd0de639b517eba06757ee8d4944c2d1126f79c5e","cross_cats_sorted":["eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-01T00:18:21Z","title_canon_sha256":"3d07660c7fe7352af2cb56978860de708c229fbd04953026dc2bfa9cbbf2269a"},"schema_version":"1.0","source":{"id":"2408.00205","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.00205","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"arxiv_version","alias_value":"2408.00205v1","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.00205","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"pith_short_12","alias_value":"JRM33VWPSFRX","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"pith_short_16","alias_value":"JRM33VWPSFRX7EYX","created_at":"2026-07-05T08:51:00Z"},{"alias_kind":"pith_short_8","alias_value":"JRM33VWP","created_at":"2026-07-05T08:51:00Z"}],"graph_snapshots":[{"event_id":"sha256:f395399e3fbef5828a7d6c7489c42fd03399ae89a9c0c0fae3d068f2b18b1090","target":"graph","created_at":"2026-07-05T08:51:00Z","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/2408.00205/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces a novel approach called sentence-wise speech summarization (Sen-SSum), which generates text summaries from a spoken document in a sentence-by-sentence manner. Sen-SSum combines the real-time processing of automatic speech recognition (ASR) with the conciseness of speech summarization. To explore this approach, we present two datasets for Sen-SSum: Mega-SSum and CSJ-SSum. Using these datasets, our study evaluates two types of Transformer-based models: 1) cascade models that combine ASR and strong text summarization models, and 2) end-to-end (E2E) models that directly conve","authors_text":"Atsunori Ogawa, Kohei Matsuura, Marc Delcroix, Masato Mimura, Takafumi Moriya, Takanori Ashihara, Takatomo Kano","cross_cats":["eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-01T00:18:21Z","title":"Sentence-wise Speech Summarization: Task, Datasets, and End-to-End Modeling with LM Knowledge Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.00205","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":"sha256:6f210012d36f26dcdebeb90ddd01cdade8611e87d3def6c3fe14c71a0f9833bd","target":"record","created_at":"2026-07-05T08:51:00Z","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":"61b19d4423117a494a8c86dcd0de639b517eba06757ee8d4944c2d1126f79c5e","cross_cats_sorted":["eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-01T00:18:21Z","title_canon_sha256":"3d07660c7fe7352af2cb56978860de708c229fbd04953026dc2bfa9cbbf2269a"},"schema_version":"1.0","source":{"id":"2408.00205","kind":"arxiv","version":1}},"canonical_sha256":"4c59bdd6cf91637f9317eef9bb6083507d00e7c4032001bb6d87764d5b804358","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4c59bdd6cf91637f9317eef9bb6083507d00e7c4032001bb6d87764d5b804358","first_computed_at":"2026-07-05T08:51:00.027618Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:51:00.027618Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"peTBrccJGUrX+raBiV3aRxIQF6CTtSCw5sBkYrl8wDIHAfVTpY+CkjRJ9JNq5HNIswy1zwdfKMLpQcKFSgUhBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:51:00.028079Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.00205","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6f210012d36f26dcdebeb90ddd01cdade8611e87d3def6c3fe14c71a0f9833bd","sha256:f395399e3fbef5828a7d6c7489c42fd03399ae89a9c0c0fae3d068f2b18b1090"],"state_sha256":"59c1967cebeaeadeaa2c616007a06a8768745bce308d5dd80c1b8d70a6fc9376"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XSDzdKuP6BPnHAZZkyt/gxRYC1212KqwGn7Ut6lpPv094IAfTwXZU9VrpC+H4XhZ75y+v357ogjGsI8p2DVUAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-14T12:01:51.243095Z","bundle_sha256":"05479193b128c64bd99aa28fd0afe33a046784f524748c253e04ca7caef79398"}}