{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:CICCVYLZSZ7GTN7KDG7EAKOIYD","short_pith_number":"pith:CICCVYLZ","canonical_record":{"source":{"id":"2311.08125","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-14T12:41:22Z","cross_cats_sorted":[],"title_canon_sha256":"00ac10d64616a07584cdfe420cca7afa577263f78644e4e2d8d12624cab9e3bb","abstract_canon_sha256":"6ffaa3a1fa289c623f60305e6cfc06fd35dbc620b813126bd639a2453591e68c"},"schema_version":"1.0"},"canonical_sha256":"12042ae179967e69b7ea19be4029c8c0d65fd9e87792fed445622292d434999b","source":{"kind":"arxiv","id":"2311.08125","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.08125","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"arxiv_version","alias_value":"2311.08125v1","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.08125","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"pith_short_12","alias_value":"CICCVYLZSZ7G","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"pith_short_16","alias_value":"CICCVYLZSZ7GTN7K","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"pith_short_8","alias_value":"CICCVYLZ","created_at":"2026-07-05T07:12:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:CICCVYLZSZ7GTN7KDG7EAKOIYD","target":"record","payload":{"canonical_record":{"source":{"id":"2311.08125","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-14T12:41:22Z","cross_cats_sorted":[],"title_canon_sha256":"00ac10d64616a07584cdfe420cca7afa577263f78644e4e2d8d12624cab9e3bb","abstract_canon_sha256":"6ffaa3a1fa289c623f60305e6cfc06fd35dbc620b813126bd639a2453591e68c"},"schema_version":"1.0"},"canonical_sha256":"12042ae179967e69b7ea19be4029c8c0d65fd9e87792fed445622292d434999b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:12:40.497243Z","signature_b64":"5AB3QdO59Pol6nhKw73ZtRB5qpjiQ5/0WbS+t8/TSVqi0Ze//MnwoDiUFAzI66DqOBc4DXuSTKIyBOFScLFICw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"12042ae179967e69b7ea19be4029c8c0d65fd9e87792fed445622292d434999b","last_reissued_at":"2026-07-05T07:12:40.496841Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:12:40.496841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.08125","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":"2026-07-05T07:12:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5a3oJUjA1nYxURjyRYsTjQkU5W43P46cqu15Acw9tJ6jgwKPhGXQsLT3m2S/J4p44JymKkVQfKQglezPGy4MCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T10:52:12.259455Z"},"content_sha256":"211bb889e6d670b3493e659373d59478332837f462af0c7a40a216dea26e511a","schema_version":"1.0","event_id":"sha256:211bb889e6d670b3493e659373d59478332837f462af0c7a40a216dea26e511a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:CICCVYLZSZ7GTN7KDG7EAKOIYD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Lite it fly: An All-Deformable-Butterfly Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Binxiao Huang, Jason Chun Lok Li, Jiajun Zhou, Jie Ran, Ngai Wong, Rui Lin","submitted_at":"2023-11-14T12:41:22Z","abstract_excerpt":"Most deep neural networks (DNNs) consist fundamentally of convolutional and/or fully connected layers, wherein the linear transform can be cast as the product between a filter matrix and a data matrix obtained by arranging feature tensors into columns. The lately proposed deformable butterfly (DeBut) decomposes the filter matrix into generalized, butterflylike factors, thus achieving network compression orthogonal to the traditional ways of pruning or low-rank decomposition. This work reveals an intimate link between DeBut and a systematic hierarchy of depthwise and pointwise convolutions, whi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.08125","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/2311.08125/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":"2026-07-05T07:12:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8MNnL1AajMkpaIFGNojgjHb1cbkPUlns/Q7GZeVgLLFY49b9YVZBGahziS6MmgScXjHeEjauEq55FPeL/ehfCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T10:52:12.259999Z"},"content_sha256":"34c0244955fc1535064ab357029a64ab670f8e91c16b07b928ac62191df93c6a","schema_version":"1.0","event_id":"sha256:34c0244955fc1535064ab357029a64ab670f8e91c16b07b928ac62191df93c6a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CICCVYLZSZ7GTN7KDG7EAKOIYD/bundle.json","state_url":"https://pith.science/pith/CICCVYLZSZ7GTN7KDG7EAKOIYD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CICCVYLZSZ7GTN7KDG7EAKOIYD/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":"2026-08-22T10:52:12Z","links":{"resolver":"https://pith.science/pith/CICCVYLZSZ7GTN7KDG7EAKOIYD","bundle":"https://pith.science/pith/CICCVYLZSZ7GTN7KDG7EAKOIYD/bundle.json","state":"https://pith.science/pith/CICCVYLZSZ7GTN7KDG7EAKOIYD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CICCVYLZSZ7GTN7KDG7EAKOIYD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CICCVYLZSZ7GTN7KDG7EAKOIYD","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":"6ffaa3a1fa289c623f60305e6cfc06fd35dbc620b813126bd639a2453591e68c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-14T12:41:22Z","title_canon_sha256":"00ac10d64616a07584cdfe420cca7afa577263f78644e4e2d8d12624cab9e3bb"},"schema_version":"1.0","source":{"id":"2311.08125","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.08125","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"arxiv_version","alias_value":"2311.08125v1","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.08125","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"pith_short_12","alias_value":"CICCVYLZSZ7G","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"pith_short_16","alias_value":"CICCVYLZSZ7GTN7K","created_at":"2026-07-05T07:12:40Z"},{"alias_kind":"pith_short_8","alias_value":"CICCVYLZ","created_at":"2026-07-05T07:12:40Z"}],"graph_snapshots":[{"event_id":"sha256:34c0244955fc1535064ab357029a64ab670f8e91c16b07b928ac62191df93c6a","target":"graph","created_at":"2026-07-05T07:12:40Z","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/2311.08125/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most deep neural networks (DNNs) consist fundamentally of convolutional and/or fully connected layers, wherein the linear transform can be cast as the product between a filter matrix and a data matrix obtained by arranging feature tensors into columns. The lately proposed deformable butterfly (DeBut) decomposes the filter matrix into generalized, butterflylike factors, thus achieving network compression orthogonal to the traditional ways of pruning or low-rank decomposition. This work reveals an intimate link between DeBut and a systematic hierarchy of depthwise and pointwise convolutions, whi","authors_text":"Binxiao Huang, Jason Chun Lok Li, Jiajun Zhou, Jie Ran, Ngai Wong, Rui Lin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-14T12:41:22Z","title":"Lite it fly: An All-Deformable-Butterfly Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.08125","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":"sha256:211bb889e6d670b3493e659373d59478332837f462af0c7a40a216dea26e511a","target":"record","created_at":"2026-07-05T07:12:40Z","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":"6ffaa3a1fa289c623f60305e6cfc06fd35dbc620b813126bd639a2453591e68c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-14T12:41:22Z","title_canon_sha256":"00ac10d64616a07584cdfe420cca7afa577263f78644e4e2d8d12624cab9e3bb"},"schema_version":"1.0","source":{"id":"2311.08125","kind":"arxiv","version":1}},"canonical_sha256":"12042ae179967e69b7ea19be4029c8c0d65fd9e87792fed445622292d434999b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"12042ae179967e69b7ea19be4029c8c0d65fd9e87792fed445622292d434999b","first_computed_at":"2026-07-05T07:12:40.496841Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:12:40.496841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5AB3QdO59Pol6nhKw73ZtRB5qpjiQ5/0WbS+t8/TSVqi0Ze//MnwoDiUFAzI66DqOBc4DXuSTKIyBOFScLFICw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:12:40.497243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.08125","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:211bb889e6d670b3493e659373d59478332837f462af0c7a40a216dea26e511a","sha256:34c0244955fc1535064ab357029a64ab670f8e91c16b07b928ac62191df93c6a"],"state_sha256":"fcfec0f61e6aa026864f5972dea0caf329ddd8d3e46a20acc5c106f8b12d1141"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OpJ/2aexeAk7tC7I4bTPAgRAWKtohqM4eZVqkhDWlOaGwpKv22qtGvpoqSbAtRhBlYUgHZfh857dyUH3JfaHAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T10:52:12.264633Z","bundle_sha256":"be412f298085448bf06422caa5ea4ef6b3eddceb9b4833846b7425305091ce8f"}}