{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:M7ZYO2XUP7NPKN4YTE3YBV46BU","short_pith_number":"pith:M7ZYO2XU","canonical_record":{"source":{"id":"2409.15869","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-09-24T08:42:31Z","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"title_canon_sha256":"4b98089d881af933871c9ce6c21880e064a9e190877e0ccb71072aa048a3a870","abstract_canon_sha256":"91da191473220bbf80ee03abef2bb53ec436dc3e6b5c04040d277887f1358d61"},"schema_version":"1.0"},"canonical_sha256":"67f3876af47fdaf53798993780d79e0d34fb4666326efdfb1902e75d271cc5ef","source":{"kind":"arxiv","id":"2409.15869","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.15869","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"arxiv_version","alias_value":"2409.15869v1","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.15869","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_12","alias_value":"M7ZYO2XUP7NP","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_16","alias_value":"M7ZYO2XUP7NPKN4Y","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_8","alias_value":"M7ZYO2XU","created_at":"2026-07-05T09:11:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:M7ZYO2XUP7NPKN4YTE3YBV46BU","target":"record","payload":{"canonical_record":{"source":{"id":"2409.15869","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-09-24T08:42:31Z","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"title_canon_sha256":"4b98089d881af933871c9ce6c21880e064a9e190877e0ccb71072aa048a3a870","abstract_canon_sha256":"91da191473220bbf80ee03abef2bb53ec436dc3e6b5c04040d277887f1358d61"},"schema_version":"1.0"},"canonical_sha256":"67f3876af47fdaf53798993780d79e0d34fb4666326efdfb1902e75d271cc5ef","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:11:01.492776Z","signature_b64":"PFqT+8dgA4POZf+cEXcO7wry8DmkYRkX7CQoXGBQxFAWTB3Gn8RL9bwOeKH14eZamGE8v8Zd1l/QBj49Td76Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"67f3876af47fdaf53798993780d79e0d34fb4666326efdfb1902e75d271cc5ef","last_reissued_at":"2026-07-05T09:11:01.492293Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:11:01.492293Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.15869","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":"2026-07-05T09:11:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bbQfkUCuHaHlILW5SjLQkBqd4erag4PtU4ncVLXmth8fVFss+iLIBp7Lf//YYPTQCVO0Xsn0yR63UP+4t/TiBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-29T00:22:57.405388Z"},"content_sha256":"51b09229f3169ede64ed5c8d89cf8eb5b5dbc68c006fedd4198733e06e3a26bb","schema_version":"1.0","event_id":"sha256:51b09229f3169ede64ed5c8d89cf8eb5b5dbc68c006fedd4198733e06e3a26bb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:M7ZYO2XUP7NPKN4YTE3YBV46BU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Whisper in Medusa's Ear: Multi-head Efficient Decoding for Transformer-based ASR","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"Aviv Navon, Aviv Shamsian, Gill Hetz, Joseph Keshet, Yael Segal-Feldman","submitted_at":"2024-09-24T08:42:31Z","abstract_excerpt":"Large transformer-based models have significant potential for speech transcription and translation. Their self-attention mechanisms and parallel processing enable them to capture complex patterns and dependencies in audio sequences. However, this potential comes with challenges, as these large and computationally intensive models lead to slow inference speeds. Various optimization strategies have been proposed to improve performance, including efficient hardware utilization and algorithmic enhancements. In this paper, we introduce Whisper-Medusa, a novel approach designed to enhance processing"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.15869","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/2409.15869/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":"2026-07-05T09:11:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KpxAoxYGiuK3MOrYVi/+kKMnt+1gEEekYhtPxNIz28Ykm18doSUesTioZK19g9o9e8+1+ukBCd8ap5O0XkMGBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-29T00:22:57.405782Z"},"content_sha256":"01200e7113489dd09e9a3241c3bec1e60ab4c80f4796787d053f4a0fc2ab412c","schema_version":"1.0","event_id":"sha256:01200e7113489dd09e9a3241c3bec1e60ab4c80f4796787d053f4a0fc2ab412c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M7ZYO2XUP7NPKN4YTE3YBV46BU/bundle.json","state_url":"https://pith.science/pith/M7ZYO2XUP7NPKN4YTE3YBV46BU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M7ZYO2XUP7NPKN4YTE3YBV46BU/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":"2026-07-29T00:22:57Z","links":{"resolver":"https://pith.science/pith/M7ZYO2XUP7NPKN4YTE3YBV46BU","bundle":"https://pith.science/pith/M7ZYO2XUP7NPKN4YTE3YBV46BU/bundle.json","state":"https://pith.science/pith/M7ZYO2XUP7NPKN4YTE3YBV46BU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M7ZYO2XUP7NPKN4YTE3YBV46BU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:M7ZYO2XUP7NPKN4YTE3YBV46BU","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":"91da191473220bbf80ee03abef2bb53ec436dc3e6b5c04040d277887f1358d61","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-09-24T08:42:31Z","title_canon_sha256":"4b98089d881af933871c9ce6c21880e064a9e190877e0ccb71072aa048a3a870"},"schema_version":"1.0","source":{"id":"2409.15869","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.15869","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"arxiv_version","alias_value":"2409.15869v1","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.15869","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_12","alias_value":"M7ZYO2XUP7NP","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_16","alias_value":"M7ZYO2XUP7NPKN4Y","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_8","alias_value":"M7ZYO2XU","created_at":"2026-07-05T09:11:01Z"}],"graph_snapshots":[{"event_id":"sha256:01200e7113489dd09e9a3241c3bec1e60ab4c80f4796787d053f4a0fc2ab412c","target":"graph","created_at":"2026-07-05T09:11:01Z","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/2409.15869/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large transformer-based models have significant potential for speech transcription and translation. Their self-attention mechanisms and parallel processing enable them to capture complex patterns and dependencies in audio sequences. However, this potential comes with challenges, as these large and computationally intensive models lead to slow inference speeds. Various optimization strategies have been proposed to improve performance, including efficient hardware utilization and algorithmic enhancements. In this paper, we introduce Whisper-Medusa, a novel approach designed to enhance processing","authors_text":"Aviv Navon, Aviv Shamsian, Gill Hetz, Joseph Keshet, Yael Segal-Feldman","cross_cats":["cs.AI","cs.LG","cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-09-24T08:42:31Z","title":"Whisper in Medusa's Ear: Multi-head Efficient Decoding for Transformer-based ASR"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.15869","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":"sha256:51b09229f3169ede64ed5c8d89cf8eb5b5dbc68c006fedd4198733e06e3a26bb","target":"record","created_at":"2026-07-05T09:11:01Z","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":"91da191473220bbf80ee03abef2bb53ec436dc3e6b5c04040d277887f1358d61","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-09-24T08:42:31Z","title_canon_sha256":"4b98089d881af933871c9ce6c21880e064a9e190877e0ccb71072aa048a3a870"},"schema_version":"1.0","source":{"id":"2409.15869","kind":"arxiv","version":1}},"canonical_sha256":"67f3876af47fdaf53798993780d79e0d34fb4666326efdfb1902e75d271cc5ef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"67f3876af47fdaf53798993780d79e0d34fb4666326efdfb1902e75d271cc5ef","first_computed_at":"2026-07-05T09:11:01.492293Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:11:01.492293Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PFqT+8dgA4POZf+cEXcO7wry8DmkYRkX7CQoXGBQxFAWTB3Gn8RL9bwOeKH14eZamGE8v8Zd1l/QBj49Td76Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:11:01.492776Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.15869","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:51b09229f3169ede64ed5c8d89cf8eb5b5dbc68c006fedd4198733e06e3a26bb","sha256:01200e7113489dd09e9a3241c3bec1e60ab4c80f4796787d053f4a0fc2ab412c"],"state_sha256":"d8705705de07b5f001071163a1691737f73383536422396bcd2b988217b3e9f8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MwKXtJwFFaKsETkJI7+Rk2yBN/tlDi3Jf+3PqYHhUtb2xO7268CGhBh1DcKp1lnWhB/wRcPiU/PsTdAmBe4zCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-29T00:22:57.408081Z","bundle_sha256":"d268593cb526b594043bf8db4460828aa81ae058364d915ee1b7c9ace8a8a162"}}