{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:CSUZNDJVZNOPQU7NBQM6PZZHMJ","short_pith_number":"pith:CSUZNDJV","canonical_record":{"source":{"id":"2210.11114","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-20T09:17:02Z","cross_cats_sorted":["cs.AI","cs.LG","cs.NE"],"title_canon_sha256":"1dfe75af4c4738311efb45ed76711b561d70b9291edb839c6346b2fc6f9b22a9","abstract_canon_sha256":"0f692d6a16661c6121ef009a08cf520b078fa99cecc6cb5a150f6106f317eefa"},"schema_version":"1.0"},"canonical_sha256":"14a9968d35cb5cf853ed0c19e7e72762600407406edc7d28514d955832c32b3e","source":{"kind":"arxiv","id":"2210.11114","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.11114","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"arxiv_version","alias_value":"2210.11114v1","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.11114","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_12","alias_value":"CSUZNDJVZNOP","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_16","alias_value":"CSUZNDJVZNOPQU7N","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_8","alias_value":"CSUZNDJV","created_at":"2026-07-05T05:08:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:CSUZNDJVZNOPQU7NBQM6PZZHMJ","target":"record","payload":{"canonical_record":{"source":{"id":"2210.11114","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-20T09:17:02Z","cross_cats_sorted":["cs.AI","cs.LG","cs.NE"],"title_canon_sha256":"1dfe75af4c4738311efb45ed76711b561d70b9291edb839c6346b2fc6f9b22a9","abstract_canon_sha256":"0f692d6a16661c6121ef009a08cf520b078fa99cecc6cb5a150f6106f317eefa"},"schema_version":"1.0"},"canonical_sha256":"14a9968d35cb5cf853ed0c19e7e72762600407406edc7d28514d955832c32b3e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:08:44.316856Z","signature_b64":"YmXD/MKcaTfB3Wixw4zmNlWQHI+3vYwqODvPq/2cQbMSQgmW2mmq6xMUGmY8tDgIfAjZxhI7cZpSW3NgxQZsDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"14a9968d35cb5cf853ed0c19e7e72762600407406edc7d28514d955832c32b3e","last_reissued_at":"2026-07-05T05:08:44.316309Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:08:44.316309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.11114","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":"2026-07-05T05:08:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y/Y+zE42dS9on5PM3/REJhe5YPpa0F7zMqsbEEfZftJDqkGMpmy2ok2ovTG2flA0c7/zmH7nxrN+idQW68iDAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T09:33:45.370870Z"},"content_sha256":"4558ae712eb31a093c3a3aace38fe86a4c1018d7564b664e29996c8d731c5276","schema_version":"1.0","event_id":"sha256:4558ae712eb31a093c3a3aace38fe86a4c1018d7564b664e29996c8d731c5276"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:CSUZNDJVZNOPQU7NBQM6PZZHMJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pruning by Active Attention Manipulation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.NE"],"primary_cat":"cs.CV","authors_text":"Daniela Rus, Lucas Liebenwein, Radu Grosu, Ramin Hasani, Zahra Babaiee","submitted_at":"2022-10-20T09:17:02Z","abstract_excerpt":"Filter pruning of a CNN is typically achieved by applying discrete masks on the CNN's filter weights or activation maps, post-training. Here, we present a new filter-importance-scoring concept named pruning by active attention manipulation (PAAM), that sparsifies the CNN's set of filters through a particular attention mechanism, during-training. PAAM learns analog filter scores from the filter weights by optimizing a cost function regularized by an additive term in the scores. As the filters are not independent, we use attention to dynamically learn their correlations. Moreover, by training th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.11114","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/2210.11114/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":"2026-07-05T05:08:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0TCx0hQjL29t5nT5QtVETNnfOChjy5Lg9OQqu1pN8mFgkW1dTsXjA9wBDhP29XS1SYXHUB8lLGtB+hGU6cfjDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T09:33:45.371395Z"},"content_sha256":"8e441cbf1e409a0b3c2f3d4944f437160bb2d377d49f89754c085d5db4cc87ed","schema_version":"1.0","event_id":"sha256:8e441cbf1e409a0b3c2f3d4944f437160bb2d377d49f89754c085d5db4cc87ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CSUZNDJVZNOPQU7NBQM6PZZHMJ/bundle.json","state_url":"https://pith.science/pith/CSUZNDJVZNOPQU7NBQM6PZZHMJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CSUZNDJVZNOPQU7NBQM6PZZHMJ/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":"2026-08-22T09:33:45Z","links":{"resolver":"https://pith.science/pith/CSUZNDJVZNOPQU7NBQM6PZZHMJ","bundle":"https://pith.science/pith/CSUZNDJVZNOPQU7NBQM6PZZHMJ/bundle.json","state":"https://pith.science/pith/CSUZNDJVZNOPQU7NBQM6PZZHMJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CSUZNDJVZNOPQU7NBQM6PZZHMJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:CSUZNDJVZNOPQU7NBQM6PZZHMJ","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":"0f692d6a16661c6121ef009a08cf520b078fa99cecc6cb5a150f6106f317eefa","cross_cats_sorted":["cs.AI","cs.LG","cs.NE"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-20T09:17:02Z","title_canon_sha256":"1dfe75af4c4738311efb45ed76711b561d70b9291edb839c6346b2fc6f9b22a9"},"schema_version":"1.0","source":{"id":"2210.11114","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.11114","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"arxiv_version","alias_value":"2210.11114v1","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.11114","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_12","alias_value":"CSUZNDJVZNOP","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_16","alias_value":"CSUZNDJVZNOPQU7N","created_at":"2026-07-05T05:08:44Z"},{"alias_kind":"pith_short_8","alias_value":"CSUZNDJV","created_at":"2026-07-05T05:08:44Z"}],"graph_snapshots":[{"event_id":"sha256:8e441cbf1e409a0b3c2f3d4944f437160bb2d377d49f89754c085d5db4cc87ed","target":"graph","created_at":"2026-07-05T05:08:44Z","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/2210.11114/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Filter pruning of a CNN is typically achieved by applying discrete masks on the CNN's filter weights or activation maps, post-training. Here, we present a new filter-importance-scoring concept named pruning by active attention manipulation (PAAM), that sparsifies the CNN's set of filters through a particular attention mechanism, during-training. PAAM learns analog filter scores from the filter weights by optimizing a cost function regularized by an additive term in the scores. As the filters are not independent, we use attention to dynamically learn their correlations. Moreover, by training th","authors_text":"Daniela Rus, Lucas Liebenwein, Radu Grosu, Ramin Hasani, Zahra Babaiee","cross_cats":["cs.AI","cs.LG","cs.NE"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-20T09:17:02Z","title":"Pruning by Active Attention Manipulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.11114","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":"sha256:4558ae712eb31a093c3a3aace38fe86a4c1018d7564b664e29996c8d731c5276","target":"record","created_at":"2026-07-05T05:08:44Z","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":"0f692d6a16661c6121ef009a08cf520b078fa99cecc6cb5a150f6106f317eefa","cross_cats_sorted":["cs.AI","cs.LG","cs.NE"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-20T09:17:02Z","title_canon_sha256":"1dfe75af4c4738311efb45ed76711b561d70b9291edb839c6346b2fc6f9b22a9"},"schema_version":"1.0","source":{"id":"2210.11114","kind":"arxiv","version":1}},"canonical_sha256":"14a9968d35cb5cf853ed0c19e7e72762600407406edc7d28514d955832c32b3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"14a9968d35cb5cf853ed0c19e7e72762600407406edc7d28514d955832c32b3e","first_computed_at":"2026-07-05T05:08:44.316309Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:08:44.316309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YmXD/MKcaTfB3Wixw4zmNlWQHI+3vYwqODvPq/2cQbMSQgmW2mmq6xMUGmY8tDgIfAjZxhI7cZpSW3NgxQZsDg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:08:44.316856Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.11114","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4558ae712eb31a093c3a3aace38fe86a4c1018d7564b664e29996c8d731c5276","sha256:8e441cbf1e409a0b3c2f3d4944f437160bb2d377d49f89754c085d5db4cc87ed"],"state_sha256":"70c48485180a4f12bce04e5d8af3f1052e7c42abdaa68af29332695318861f92"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cwiYivMHCOz1lPxqXHKmtuqXlUpwDLfiqyfRI3MZhQK3RyFJ7toak1+yJGUxePecLW1vxouazUEKpl4nctoFBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T09:33:45.376563Z","bundle_sha256":"a64e299ce82b45d154ea57cf4053d91345dceccbf3f4ecba59d1d4a145cde817"}}