{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:LCQHOB224GDECUR4JQOTXVI5RH","short_pith_number":"pith:LCQHOB22","canonical_record":{"source":{"id":"2107.04734","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-07-10T02:13:25Z","cross_cats_sorted":["cs.LG","eess.AS"],"title_canon_sha256":"c3970522a4f87e463540296c41fb1b01de1b1ce094b85951c2d22ae17208c900","abstract_canon_sha256":"301399e938c9e2f67cc490c12f0b5e72f094e0e30dd87269561285f229c5c629"},"schema_version":"1.0"},"canonical_sha256":"58a077075ae18641523c4c1d3bd51d89dc17fbfd7f705a99f586b7cf86f029b8","source":{"kind":"arxiv","id":"2107.04734","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04734","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04734v3","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04734","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"pith_short_12","alias_value":"LCQHOB224GDE","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"pith_short_16","alias_value":"LCQHOB224GDECUR4","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"pith_short_8","alias_value":"LCQHOB22","created_at":"2026-07-05T05:21:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:LCQHOB224GDECUR4JQOTXVI5RH","target":"record","payload":{"canonical_record":{"source":{"id":"2107.04734","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-07-10T02:13:25Z","cross_cats_sorted":["cs.LG","eess.AS"],"title_canon_sha256":"c3970522a4f87e463540296c41fb1b01de1b1ce094b85951c2d22ae17208c900","abstract_canon_sha256":"301399e938c9e2f67cc490c12f0b5e72f094e0e30dd87269561285f229c5c629"},"schema_version":"1.0"},"canonical_sha256":"58a077075ae18641523c4c1d3bd51d89dc17fbfd7f705a99f586b7cf86f029b8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:21:53.035730Z","signature_b64":"nTRtfYaXSLErCJhT7OlZXLgRPqYcLvbhlKKVKYHfkZ9Kq3ex6hujPPzDTFmlgj2DfM3eDOEutioGE3ye1RNxCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"58a077075ae18641523c4c1d3bd51d89dc17fbfd7f705a99f586b7cf86f029b8","last_reissued_at":"2026-07-05T05:21:53.035225Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:21:53.035225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.04734","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:21:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SrVcZjyX6APdUtLo4kxGm/KY97Zdax8qFPlsAzEUVYx8OJkqQmO8FvLEnIp2L3bRTTtLcdRRb17QmALl/r2MCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:48:53.823757Z"},"content_sha256":"e4e89437bfebb047c6ef528fb50851cb126103b9e8dc251442bbd4ebba9c429c","schema_version":"1.0","event_id":"sha256:e4e89437bfebb047c6ef528fb50851cb126103b9e8dc251442bbd4ebba9c429c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:LCQHOB224GDECUR4JQOTXVI5RH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Layer-wise Analysis of a Self-supervised Speech Representation Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.AS"],"primary_cat":"cs.CL","authors_text":"Ankita Pasad, Ju-chieh Chou, Karen Livescu","submitted_at":"2021-07-10T02:13:25Z","abstract_excerpt":"Recently proposed self-supervised learning approaches have been successful for pre-training speech representation models. The utility of these learned representations has been observed empirically, but not much has been studied about the type or extent of information encoded in the pre-trained representations themselves. Developing such insights can help understand the capabilities and limits of these models and enable the research community to more efficiently develop their usage for downstream applications. In this work, we begin to fill this gap by examining one recent and successful pre-tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04734","kind":"arxiv","version":3},"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/2107.04734/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":"2026-07-05T05:21:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pPs/Irm/JHXZnJbLoytZKHtvQKAOnRudGrc7A9lRgr+XS5AxGL0D7lkdx3IO24SHKLl5kMA7uyn1hHs/L+L3Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:48:53.824137Z"},"content_sha256":"8bd423219df4385ced5d66379fdcc5685fbc46a6e4a623a2eb6bc829cb95d6c6","schema_version":"1.0","event_id":"sha256:8bd423219df4385ced5d66379fdcc5685fbc46a6e4a623a2eb6bc829cb95d6c6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LCQHOB224GDECUR4JQOTXVI5RH/bundle.json","state_url":"https://pith.science/pith/LCQHOB224GDECUR4JQOTXVI5RH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LCQHOB224GDECUR4JQOTXVI5RH/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":"2026-07-06T18:48:53Z","links":{"resolver":"https://pith.science/pith/LCQHOB224GDECUR4JQOTXVI5RH","bundle":"https://pith.science/pith/LCQHOB224GDECUR4JQOTXVI5RH/bundle.json","state":"https://pith.science/pith/LCQHOB224GDECUR4JQOTXVI5RH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LCQHOB224GDECUR4JQOTXVI5RH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:LCQHOB224GDECUR4JQOTXVI5RH","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":"301399e938c9e2f67cc490c12f0b5e72f094e0e30dd87269561285f229c5c629","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-07-10T02:13:25Z","title_canon_sha256":"c3970522a4f87e463540296c41fb1b01de1b1ce094b85951c2d22ae17208c900"},"schema_version":"1.0","source":{"id":"2107.04734","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04734","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04734v3","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04734","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"pith_short_12","alias_value":"LCQHOB224GDE","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"pith_short_16","alias_value":"LCQHOB224GDECUR4","created_at":"2026-07-05T05:21:53Z"},{"alias_kind":"pith_short_8","alias_value":"LCQHOB22","created_at":"2026-07-05T05:21:53Z"}],"graph_snapshots":[{"event_id":"sha256:8bd423219df4385ced5d66379fdcc5685fbc46a6e4a623a2eb6bc829cb95d6c6","target":"graph","created_at":"2026-07-05T05:21:53Z","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/2107.04734/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently proposed self-supervised learning approaches have been successful for pre-training speech representation models. The utility of these learned representations has been observed empirically, but not much has been studied about the type or extent of information encoded in the pre-trained representations themselves. Developing such insights can help understand the capabilities and limits of these models and enable the research community to more efficiently develop their usage for downstream applications. In this work, we begin to fill this gap by examining one recent and successful pre-tr","authors_text":"Ankita Pasad, Ju-chieh Chou, Karen Livescu","cross_cats":["cs.LG","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-07-10T02:13:25Z","title":"Layer-wise Analysis of a Self-supervised Speech Representation Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04734","kind":"arxiv","version":3},"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:e4e89437bfebb047c6ef528fb50851cb126103b9e8dc251442bbd4ebba9c429c","target":"record","created_at":"2026-07-05T05:21:53Z","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":"301399e938c9e2f67cc490c12f0b5e72f094e0e30dd87269561285f229c5c629","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-07-10T02:13:25Z","title_canon_sha256":"c3970522a4f87e463540296c41fb1b01de1b1ce094b85951c2d22ae17208c900"},"schema_version":"1.0","source":{"id":"2107.04734","kind":"arxiv","version":3}},"canonical_sha256":"58a077075ae18641523c4c1d3bd51d89dc17fbfd7f705a99f586b7cf86f029b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"58a077075ae18641523c4c1d3bd51d89dc17fbfd7f705a99f586b7cf86f029b8","first_computed_at":"2026-07-05T05:21:53.035225Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:21:53.035225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nTRtfYaXSLErCJhT7OlZXLgRPqYcLvbhlKKVKYHfkZ9Kq3ex6hujPPzDTFmlgj2DfM3eDOEutioGE3ye1RNxCA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:21:53.035730Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.04734","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4e89437bfebb047c6ef528fb50851cb126103b9e8dc251442bbd4ebba9c429c","sha256:8bd423219df4385ced5d66379fdcc5685fbc46a6e4a623a2eb6bc829cb95d6c6"],"state_sha256":"c2fe7c5e6804ed17a4dfedc1561e33e40c9a4adcf2d154319ca80d5c5374704d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vl8JZZhZKRrw+sXPwSbJghogFs+P7jDm9pSaqoiVZPa1jupjR07EjEeV1cSzI28TntOUn4sHTH3CzddlxdtdAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:48:53.826118Z","bundle_sha256":"68078d0136199c3d1f4f2f40b81c5104d1378aa0d5f04ea5c7f10c6fff81c735"}}