{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:OUXXTNHBZH6DS6VQIGYTFLKEB4","short_pith_number":"pith:OUXXTNHB","canonical_record":{"source":{"id":"1511.06433","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-19T22:48:59Z","cross_cats_sorted":[],"title_canon_sha256":"cb2d6fef3d53ea401b98abbb90467589e0475920ebdb41aec37b94a1d856793b","abstract_canon_sha256":"0f95855b946ae50078ea08f001d619b40c6e805190c0e7e10f8c5c41fa512bf7"},"schema_version":"1.0"},"canonical_sha256":"752f79b4e1c9fc397ab041b132ad440f2d55939b284b4db69ec5ff64e66ec4d0","source":{"kind":"arxiv","id":"1511.06433","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.06433","created_at":"2026-05-18T01:04:41Z"},{"alias_kind":"arxiv_version","alias_value":"1511.06433v3","created_at":"2026-05-18T01:04:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.06433","created_at":"2026-05-18T01:04:41Z"},{"alias_kind":"pith_short_12","alias_value":"OUXXTNHBZH6D","created_at":"2026-05-18T12:29:34Z"},{"alias_kind":"pith_short_16","alias_value":"OUXXTNHBZH6DS6VQ","created_at":"2026-05-18T12:29:34Z"},{"alias_kind":"pith_short_8","alias_value":"OUXXTNHB","created_at":"2026-05-18T12:29:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:OUXXTNHBZH6DS6VQIGYTFLKEB4","target":"record","payload":{"canonical_record":{"source":{"id":"1511.06433","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-19T22:48:59Z","cross_cats_sorted":[],"title_canon_sha256":"cb2d6fef3d53ea401b98abbb90467589e0475920ebdb41aec37b94a1d856793b","abstract_canon_sha256":"0f95855b946ae50078ea08f001d619b40c6e805190c0e7e10f8c5c41fa512bf7"},"schema_version":"1.0"},"canonical_sha256":"752f79b4e1c9fc397ab041b132ad440f2d55939b284b4db69ec5ff64e66ec4d0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:41.588368Z","signature_b64":"r2s28vrEZHczLJhFvHLHqE/oiVlAih9cLR8Lpf3ExXf+Ws0FhLqNTXMjx39T/EKdRT6qjtqPPdXLmWWHjv/KDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"752f79b4e1c9fc397ab041b132ad440f2d55939b284b4db69ec5ff64e66ec4d0","last_reissued_at":"2026-05-18T01:04:41.587864Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:41.587864Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1511.06433","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":"2026-05-18T01:04:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ny+Gmrkr/yEhiv0G1BmbZGJN7PzSdTDHDfNLqCmCuRrlh4Ch/seQYE5bFLszf7mlMHIqn3WDettPZN6W2asOBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T16:10:45.200740Z"},"content_sha256":"c47b0039f13c84afd3a31c4b82d95c7273f8130d383cc26e17b54b8af48f1a28","schema_version":"1.0","event_id":"sha256:c47b0039f13c84afd3a31c4b82d95c7273f8130d383cc26e17b54b8af48f1a28"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:OUXXTNHBZH6DS6VQIGYTFLKEB4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Blending LSTMs into CNNs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Abdel-rahman Mohamed, Charles Sutton, Gregor Urban, Krzysztof J. Geras, Matthai Philipose, Matthew Richardson, Ozlem Aslan, Rich Caruana, Shengjie Wang","submitted_at":"2015-11-19T22:48:59Z","abstract_excerpt":"We consider whether deep convolutional networks (CNNs) can represent decision functions with similar accuracy as recurrent networks such as LSTMs. First, we show that a deep CNN with an architecture inspired by the models recently introduced in image recognition can yield better accuracy than previous convolutional and LSTM networks on the standard 309h Switchboard automatic speech recognition task. Then we show that even more accurate CNNs can be trained under the guidance of LSTMs using a variant of model compression, which we call model blending because the teacher and student models are si"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.06433","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":""},"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":"2026-05-18T01:04:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/x2eIqhpMmecHl21u21JP/vLvrbn+oEFMf125bZNJQsAB6dkiK8jEW7E4pzi0EFyvQpe28WVvclTLMjYnijtDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T16:10:45.201398Z"},"content_sha256":"78e9c14c216f8305539e3421d8bab4ff5e1d70d1c2889bcf78549ecd4a2bf757","schema_version":"1.0","event_id":"sha256:78e9c14c216f8305539e3421d8bab4ff5e1d70d1c2889bcf78549ecd4a2bf757"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OUXXTNHBZH6DS6VQIGYTFLKEB4/bundle.json","state_url":"https://pith.science/pith/OUXXTNHBZH6DS6VQIGYTFLKEB4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OUXXTNHBZH6DS6VQIGYTFLKEB4/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":"2026-05-29T16:10:45Z","links":{"resolver":"https://pith.science/pith/OUXXTNHBZH6DS6VQIGYTFLKEB4","bundle":"https://pith.science/pith/OUXXTNHBZH6DS6VQIGYTFLKEB4/bundle.json","state":"https://pith.science/pith/OUXXTNHBZH6DS6VQIGYTFLKEB4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OUXXTNHBZH6DS6VQIGYTFLKEB4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:OUXXTNHBZH6DS6VQIGYTFLKEB4","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":"0f95855b946ae50078ea08f001d619b40c6e805190c0e7e10f8c5c41fa512bf7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-19T22:48:59Z","title_canon_sha256":"cb2d6fef3d53ea401b98abbb90467589e0475920ebdb41aec37b94a1d856793b"},"schema_version":"1.0","source":{"id":"1511.06433","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.06433","created_at":"2026-05-18T01:04:41Z"},{"alias_kind":"arxiv_version","alias_value":"1511.06433v3","created_at":"2026-05-18T01:04:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.06433","created_at":"2026-05-18T01:04:41Z"},{"alias_kind":"pith_short_12","alias_value":"OUXXTNHBZH6D","created_at":"2026-05-18T12:29:34Z"},{"alias_kind":"pith_short_16","alias_value":"OUXXTNHBZH6DS6VQ","created_at":"2026-05-18T12:29:34Z"},{"alias_kind":"pith_short_8","alias_value":"OUXXTNHB","created_at":"2026-05-18T12:29:34Z"}],"graph_snapshots":[{"event_id":"sha256:78e9c14c216f8305539e3421d8bab4ff5e1d70d1c2889bcf78549ecd4a2bf757","target":"graph","created_at":"2026-05-18T01:04:41Z","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"},"paper":{"abstract_excerpt":"We consider whether deep convolutional networks (CNNs) can represent decision functions with similar accuracy as recurrent networks such as LSTMs. First, we show that a deep CNN with an architecture inspired by the models recently introduced in image recognition can yield better accuracy than previous convolutional and LSTM networks on the standard 309h Switchboard automatic speech recognition task. Then we show that even more accurate CNNs can be trained under the guidance of LSTMs using a variant of model compression, which we call model blending because the teacher and student models are si","authors_text":"Abdel-rahman Mohamed, Charles Sutton, Gregor Urban, Krzysztof J. Geras, Matthai Philipose, Matthew Richardson, Ozlem Aslan, Rich Caruana, Shengjie Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-19T22:48:59Z","title":"Blending LSTMs into CNNs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.06433","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:c47b0039f13c84afd3a31c4b82d95c7273f8130d383cc26e17b54b8af48f1a28","target":"record","created_at":"2026-05-18T01:04:41Z","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":"0f95855b946ae50078ea08f001d619b40c6e805190c0e7e10f8c5c41fa512bf7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-11-19T22:48:59Z","title_canon_sha256":"cb2d6fef3d53ea401b98abbb90467589e0475920ebdb41aec37b94a1d856793b"},"schema_version":"1.0","source":{"id":"1511.06433","kind":"arxiv","version":3}},"canonical_sha256":"752f79b4e1c9fc397ab041b132ad440f2d55939b284b4db69ec5ff64e66ec4d0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"752f79b4e1c9fc397ab041b132ad440f2d55939b284b4db69ec5ff64e66ec4d0","first_computed_at":"2026-05-18T01:04:41.587864Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:04:41.587864Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r2s28vrEZHczLJhFvHLHqE/oiVlAih9cLR8Lpf3ExXf+Ws0FhLqNTXMjx39T/EKdRT6qjtqPPdXLmWWHjv/KDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:04:41.588368Z","signed_message":"canonical_sha256_bytes"},"source_id":"1511.06433","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c47b0039f13c84afd3a31c4b82d95c7273f8130d383cc26e17b54b8af48f1a28","sha256:78e9c14c216f8305539e3421d8bab4ff5e1d70d1c2889bcf78549ecd4a2bf757"],"state_sha256":"92e0ae818770586edd9a0a047d65623757c80434b835a3e95e13420b987a7663"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TRAETFifOkCaglLVaBQZaDvir/h8DAIJjgJwcZlssaDw4/Mqn9BSO/ZzBSPlrq6qU3TqWHlPmygAo6OoHmyFAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T16:10:45.204771Z","bundle_sha256":"1f6107a89ef60a7df03ebbc9b0cc397d24738675981a3a64fa5bfa0be80ddf6e"}}