{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:DJELAWLL7AS66PK2IOXD522PA2","short_pith_number":"pith:DJELAWLL","canonical_record":{"source":{"id":"2303.08343","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2023-03-15T03:21:38Z","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"title_canon_sha256":"dd197d439c57f96083d76958898f0995ca515d806612b49402847538b433eed0","abstract_canon_sha256":"4d39bf6c0a2bf52244848ff7ff94aaca695ddf26b6faf5abb0bd0edcb0ff5f7a"},"schema_version":"1.0"},"canonical_sha256":"1a48b0596bf825ef3d5a43ae3eeb4f06b39181a3b778159f9c1834ab72e62a4b","source":{"kind":"arxiv","id":"2303.08343","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.08343","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"arxiv_version","alias_value":"2303.08343v1","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.08343","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"pith_short_12","alias_value":"DJELAWLL7AS6","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"pith_short_16","alias_value":"DJELAWLL7AS66PK2","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"pith_short_8","alias_value":"DJELAWLL","created_at":"2026-07-05T05:51:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:DJELAWLL7AS66PK2IOXD522PA2","target":"record","payload":{"canonical_record":{"source":{"id":"2303.08343","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2023-03-15T03:21:38Z","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"title_canon_sha256":"dd197d439c57f96083d76958898f0995ca515d806612b49402847538b433eed0","abstract_canon_sha256":"4d39bf6c0a2bf52244848ff7ff94aaca695ddf26b6faf5abb0bd0edcb0ff5f7a"},"schema_version":"1.0"},"canonical_sha256":"1a48b0596bf825ef3d5a43ae3eeb4f06b39181a3b778159f9c1834ab72e62a4b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:51:31.802972Z","signature_b64":"U2yvB8gk0I9CYv6A82YkxrJjPVuJtJO7TIZGk3kmGo+kormZwJOQ2/iV9/sLv2bTEvPb8/KbUorSwEossYdrAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a48b0596bf825ef3d5a43ae3eeb4f06b39181a3b778159f9c1834ab72e62a4b","last_reissued_at":"2026-07-05T05:51:31.802559Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:51:31.802559Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.08343","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":"2026-07-05T05:51:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VC+BnAlPV/S9qbuaPhK9AMgX+aXh8aTpiVKKQ6AUyZIhka2UniVr04DuF3TIfTQ4aewH6Qpg078RG5enzA5sCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:59:33.789674Z"},"content_sha256":"eacc5c09c6742aff9059e59fd3adcf3540c294667898d64fcc8e5faa5e284faf","schema_version":"1.0","event_id":"sha256:eacc5c09c6742aff9059e59fd3adcf3540c294667898d64fcc8e5faa5e284faf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:DJELAWLL7AS66PK2IOXD522PA2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"Antoine Bruguier, Ding Zhao, Ian McGraw, Rohit Prabhavalkar, Shaojin Ding, Steven M. Hernandez, Tara N. Sainath, Yanzhang He","submitted_at":"2023-03-15T03:21:38Z","abstract_excerpt":"Continued improvements in machine learning techniques offer exciting new opportunities through the use of larger models and larger training datasets. However, there is a growing need to offer these new capabilities on-board low-powered devices such as smartphones, wearables and other embedded environments where only low memory is available. Towards this, we consider methods to reduce the model size of Conformer-based speech recognition models which typically require models with greater than 100M parameters down to just $5$M parameters while minimizing impact on model quality. Such a model allo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.08343","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/2303.08343/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":"2026-07-05T05:51:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ka6OxSLoEbMExlU1vlcjylORhtiAejOMaIjstU0r0RkLzmsZoUr55hNzBI/hxlDbKH7ffkQyZ2rxpcUwfhhTCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:59:33.790158Z"},"content_sha256":"f4c6f4d4168c5722bfb883fdd1906d8fcd6422c5d636d9ba834c3183a4ad2206","schema_version":"1.0","event_id":"sha256:f4c6f4d4168c5722bfb883fdd1906d8fcd6422c5d636d9ba834c3183a4ad2206"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DJELAWLL7AS66PK2IOXD522PA2/bundle.json","state_url":"https://pith.science/pith/DJELAWLL7AS66PK2IOXD522PA2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DJELAWLL7AS66PK2IOXD522PA2/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":"2026-08-06T00:59:33Z","links":{"resolver":"https://pith.science/pith/DJELAWLL7AS66PK2IOXD522PA2","bundle":"https://pith.science/pith/DJELAWLL7AS66PK2IOXD522PA2/bundle.json","state":"https://pith.science/pith/DJELAWLL7AS66PK2IOXD522PA2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DJELAWLL7AS66PK2IOXD522PA2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:DJELAWLL7AS66PK2IOXD522PA2","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":"4d39bf6c0a2bf52244848ff7ff94aaca695ddf26b6faf5abb0bd0edcb0ff5f7a","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2023-03-15T03:21:38Z","title_canon_sha256":"dd197d439c57f96083d76958898f0995ca515d806612b49402847538b433eed0"},"schema_version":"1.0","source":{"id":"2303.08343","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.08343","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"arxiv_version","alias_value":"2303.08343v1","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.08343","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"pith_short_12","alias_value":"DJELAWLL7AS6","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"pith_short_16","alias_value":"DJELAWLL7AS66PK2","created_at":"2026-07-05T05:51:31Z"},{"alias_kind":"pith_short_8","alias_value":"DJELAWLL","created_at":"2026-07-05T05:51:31Z"}],"graph_snapshots":[{"event_id":"sha256:f4c6f4d4168c5722bfb883fdd1906d8fcd6422c5d636d9ba834c3183a4ad2206","target":"graph","created_at":"2026-07-05T05:51:31Z","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/2303.08343/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Continued improvements in machine learning techniques offer exciting new opportunities through the use of larger models and larger training datasets. However, there is a growing need to offer these new capabilities on-board low-powered devices such as smartphones, wearables and other embedded environments where only low memory is available. Towards this, we consider methods to reduce the model size of Conformer-based speech recognition models which typically require models with greater than 100M parameters down to just $5$M parameters while minimizing impact on model quality. Such a model allo","authors_text":"Antoine Bruguier, Ding Zhao, Ian McGraw, Rohit Prabhavalkar, Shaojin Ding, Steven M. Hernandez, Tara N. Sainath, Yanzhang He","cross_cats":["cs.AI","cs.LG","cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2023-03-15T03:21:38Z","title":"Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.08343","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:eacc5c09c6742aff9059e59fd3adcf3540c294667898d64fcc8e5faa5e284faf","target":"record","created_at":"2026-07-05T05:51:31Z","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":"4d39bf6c0a2bf52244848ff7ff94aaca695ddf26b6faf5abb0bd0edcb0ff5f7a","cross_cats_sorted":["cs.AI","cs.LG","cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2023-03-15T03:21:38Z","title_canon_sha256":"dd197d439c57f96083d76958898f0995ca515d806612b49402847538b433eed0"},"schema_version":"1.0","source":{"id":"2303.08343","kind":"arxiv","version":1}},"canonical_sha256":"1a48b0596bf825ef3d5a43ae3eeb4f06b39181a3b778159f9c1834ab72e62a4b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1a48b0596bf825ef3d5a43ae3eeb4f06b39181a3b778159f9c1834ab72e62a4b","first_computed_at":"2026-07-05T05:51:31.802559Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:51:31.802559Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"U2yvB8gk0I9CYv6A82YkxrJjPVuJtJO7TIZGk3kmGo+kormZwJOQ2/iV9/sLv2bTEvPb8/KbUorSwEossYdrAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:51:31.802972Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.08343","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eacc5c09c6742aff9059e59fd3adcf3540c294667898d64fcc8e5faa5e284faf","sha256:f4c6f4d4168c5722bfb883fdd1906d8fcd6422c5d636d9ba834c3183a4ad2206"],"state_sha256":"926d8f756f7026a9b45978dc619d74cfc17b563f46b49f50ea310494a44e8f06"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5kCHg8NN95gp+YxIi0IbiDsbzY5pu97jdMnVdzA3RSj5xcRe9M99xnFJ7tlL7elwQ9AgaQK6zlvEh0zcspTCDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T00:59:33.793398Z","bundle_sha256":"2e22d1d3c7a6183bbf55a1ecc281b19f18ad14cf4e5bb514030672935679a95a"}}