{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:AN5WNPVVJMJAISWNSZKX55VXB2","short_pith_number":"pith:AN5WNPVV","canonical_record":{"source":{"id":"2008.02897","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-06T22:33:10Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c95d7a36f58474cdbadee2a4b8d9f66c4a6d872aa2fafb790db0f6575aaa1600","abstract_canon_sha256":"245f56d5b36d194656e6b3e2ffa72e214045d7ec96984c0287f39acd4c697e63"},"schema_version":"1.0"},"canonical_sha256":"037b66beb54b12044acd96557ef6b70ea2852fcca9685a535768a6862e508ee6","source":{"kind":"arxiv","id":"2008.02897","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.02897","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"arxiv_version","alias_value":"2008.02897v1","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.02897","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"pith_short_12","alias_value":"AN5WNPVVJMJA","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"pith_short_16","alias_value":"AN5WNPVVJMJAISWN","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"pith_short_8","alias_value":"AN5WNPVV","created_at":"2026-07-05T01:25:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:AN5WNPVVJMJAISWNSZKX55VXB2","target":"record","payload":{"canonical_record":{"source":{"id":"2008.02897","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-06T22:33:10Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"c95d7a36f58474cdbadee2a4b8d9f66c4a6d872aa2fafb790db0f6575aaa1600","abstract_canon_sha256":"245f56d5b36d194656e6b3e2ffa72e214045d7ec96984c0287f39acd4c697e63"},"schema_version":"1.0"},"canonical_sha256":"037b66beb54b12044acd96557ef6b70ea2852fcca9685a535768a6862e508ee6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:25:54.493259Z","signature_b64":"n4QBY0twCYuGLtUX/m24VOF6W9h7ofT6o3RUM7kuETQKSKScyemTTPDgsFqUyH4WO7JPToOqinA85yrcivgNDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"037b66beb54b12044acd96557ef6b70ea2852fcca9685a535768a6862e508ee6","last_reissued_at":"2026-07-05T01:25:54.492788Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:25:54.492788Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.02897","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":"2026-07-05T01:25:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vxpJYYxCXhYB3s/GQ4/omaJgJXr91gNGjj8Xmqo4wzOkMt3KiCqv6N8tLha/QydMFNXUNJhJhyq33gPPsmH3BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:37:47.095121Z"},"content_sha256":"d8b248f2faba1e4f74690c63cbca57ad4f5b1dbd49c209effd381e513dc13414","schema_version":"1.0","event_id":"sha256:d8b248f2faba1e4f74690c63cbca57ad4f5b1dbd49c209effd381e513dc13414"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:AN5WNPVVJMJAISWNSZKX55VXB2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Iterative Compression of End-to-End ASR Model using AutoML","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Abhinav Mehrotra, Alberto Gil C. P. Ramos, Daehyun Kim, Jinsu Yeo, {\\L}ukasz Dudziak, Mohamed S. Abdelfattah, Nicholas D. Lane, Ravichander Vipperla, Samin Ishtiaq, SangJeong Lee, Sourav Bhattacharya, Young-Yoon Lee","submitted_at":"2020-08-06T22:33:10Z","abstract_excerpt":"Increasing demand for on-device Automatic Speech Recognition (ASR) systems has resulted in renewed interests in developing automatic model compression techniques. Past research have shown that AutoML-based Low Rank Factorization (LRF) technique, when applied to an end-to-end Encoder-Attention-Decoder style ASR model, can achieve a speedup of up to 3.7x, outperforming laborious manual rank-selection approaches. However, we show that current AutoML-based search techniques only work up to a certain compression level, beyond which they fail to produce compressed models with acceptable word error r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.02897","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/2008.02897/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":"2026-07-05T01:25:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gTyd41Af9jGFFWKheIyyK+QlVkuhr4qqP4VSJ2Qgw3NKrOaegjmDHxp7FjEUjM/TlvF/ZpY2OBUr4j1o1KDtCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:37:47.095674Z"},"content_sha256":"df4728cd396612718fe11f7324b8d5ba113f3a5434406ffe7379601123e52605","schema_version":"1.0","event_id":"sha256:df4728cd396612718fe11f7324b8d5ba113f3a5434406ffe7379601123e52605"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AN5WNPVVJMJAISWNSZKX55VXB2/bundle.json","state_url":"https://pith.science/pith/AN5WNPVVJMJAISWNSZKX55VXB2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AN5WNPVVJMJAISWNSZKX55VXB2/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":"2026-08-04T08:37:47Z","links":{"resolver":"https://pith.science/pith/AN5WNPVVJMJAISWNSZKX55VXB2","bundle":"https://pith.science/pith/AN5WNPVVJMJAISWNSZKX55VXB2/bundle.json","state":"https://pith.science/pith/AN5WNPVVJMJAISWNSZKX55VXB2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AN5WNPVVJMJAISWNSZKX55VXB2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:AN5WNPVVJMJAISWNSZKX55VXB2","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":"245f56d5b36d194656e6b3e2ffa72e214045d7ec96984c0287f39acd4c697e63","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-06T22:33:10Z","title_canon_sha256":"c95d7a36f58474cdbadee2a4b8d9f66c4a6d872aa2fafb790db0f6575aaa1600"},"schema_version":"1.0","source":{"id":"2008.02897","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.02897","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"arxiv_version","alias_value":"2008.02897v1","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.02897","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"pith_short_12","alias_value":"AN5WNPVVJMJA","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"pith_short_16","alias_value":"AN5WNPVVJMJAISWN","created_at":"2026-07-05T01:25:54Z"},{"alias_kind":"pith_short_8","alias_value":"AN5WNPVV","created_at":"2026-07-05T01:25:54Z"}],"graph_snapshots":[{"event_id":"sha256:df4728cd396612718fe11f7324b8d5ba113f3a5434406ffe7379601123e52605","target":"graph","created_at":"2026-07-05T01:25:54Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2008.02897/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Increasing demand for on-device Automatic Speech Recognition (ASR) systems has resulted in renewed interests in developing automatic model compression techniques. Past research have shown that AutoML-based Low Rank Factorization (LRF) technique, when applied to an end-to-end Encoder-Attention-Decoder style ASR model, can achieve a speedup of up to 3.7x, outperforming laborious manual rank-selection approaches. However, we show that current AutoML-based search techniques only work up to a certain compression level, beyond which they fail to produce compressed models with acceptable word error r","authors_text":"Abhinav Mehrotra, Alberto Gil C. P. Ramos, Daehyun Kim, Jinsu Yeo, {\\L}ukasz Dudziak, Mohamed S. Abdelfattah, Nicholas D. Lane, Ravichander Vipperla, Samin Ishtiaq, SangJeong Lee, Sourav Bhattacharya, Young-Yoon Lee","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-06T22:33:10Z","title":"Iterative Compression of End-to-End ASR Model using AutoML"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.02897","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:d8b248f2faba1e4f74690c63cbca57ad4f5b1dbd49c209effd381e513dc13414","target":"record","created_at":"2026-07-05T01:25:54Z","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":"245f56d5b36d194656e6b3e2ffa72e214045d7ec96984c0287f39acd4c697e63","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-06T22:33:10Z","title_canon_sha256":"c95d7a36f58474cdbadee2a4b8d9f66c4a6d872aa2fafb790db0f6575aaa1600"},"schema_version":"1.0","source":{"id":"2008.02897","kind":"arxiv","version":1}},"canonical_sha256":"037b66beb54b12044acd96557ef6b70ea2852fcca9685a535768a6862e508ee6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"037b66beb54b12044acd96557ef6b70ea2852fcca9685a535768a6862e508ee6","first_computed_at":"2026-07-05T01:25:54.492788Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:25:54.492788Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n4QBY0twCYuGLtUX/m24VOF6W9h7ofT6o3RUM7kuETQKSKScyemTTPDgsFqUyH4WO7JPToOqinA85yrcivgNDg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:25:54.493259Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.02897","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8b248f2faba1e4f74690c63cbca57ad4f5b1dbd49c209effd381e513dc13414","sha256:df4728cd396612718fe11f7324b8d5ba113f3a5434406ffe7379601123e52605"],"state_sha256":"c3eeb2dba85d781baf95ee3fd2e73579c863a6cbced42e539b0b5de1be21f538"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uZ3AE/lX1ROWATvlPzoq91BmVTniUdO0ziQltgyX4YS62qseGsMPh8VKL+1tUzBeo2vovxMTMbjpC72b30AgDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T08:37:47.106112Z","bundle_sha256":"033667afb05f580184e50210740d3730682ea2bf709274cd0ebdda6e975b30c2"}}