{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:INJDJOVVZJOLDJKLEVYF2PRXEE","short_pith_number":"pith:INJDJOVV","canonical_record":{"source":{"id":"2105.07085","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-14T22:30:13Z","cross_cats_sorted":[],"title_canon_sha256":"be73834ff3f4eb7d555a162597e8801794fdf8721fbe1035c8957e5f91576471","abstract_canon_sha256":"69e6d7e8c2577a018ecb21ac085b01cc3aad03cc44d0c81de7f3a6aea9354137"},"schema_version":"1.0"},"canonical_sha256":"435234bab5ca5cb1a54b25705d3e37211b582df6b1146806368e80a0e7319564","source":{"kind":"arxiv","id":"2105.07085","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.07085","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"arxiv_version","alias_value":"2105.07085v2","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.07085","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"pith_short_12","alias_value":"INJDJOVVZJOL","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"pith_short_16","alias_value":"INJDJOVVZJOLDJKL","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"pith_short_8","alias_value":"INJDJOVV","created_at":"2026-07-05T03:44:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:INJDJOVVZJOLDJKLEVYF2PRXEE","target":"record","payload":{"canonical_record":{"source":{"id":"2105.07085","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-14T22:30:13Z","cross_cats_sorted":[],"title_canon_sha256":"be73834ff3f4eb7d555a162597e8801794fdf8721fbe1035c8957e5f91576471","abstract_canon_sha256":"69e6d7e8c2577a018ecb21ac085b01cc3aad03cc44d0c81de7f3a6aea9354137"},"schema_version":"1.0"},"canonical_sha256":"435234bab5ca5cb1a54b25705d3e37211b582df6b1146806368e80a0e7319564","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:44:29.409946Z","signature_b64":"HM4KWO7E6766rsDUeLn9RyKjtZ4IPZBi4BEf7dPBACATrZIzMqK50WlVdoy1/JCsdRFqK40n7RhCznX1iBnZBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"435234bab5ca5cb1a54b25705d3e37211b582df6b1146806368e80a0e7319564","last_reissued_at":"2026-07-05T03:44:29.409569Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:44:29.409569Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2105.07085","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:44:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FzJi/27aA1NhASwuvtiWNL0mkixuvIThBTnLPnXXKRhOIGnrDDrJsTb8W00lNLpQ/NMq1bcIVOtDK/j9NVIDCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T02:57:05.222444Z"},"content_sha256":"67cfa082ff2991bba5add38a7d4aeba2e41829c6012f7a333996c67af33013dc","schema_version":"1.0","event_id":"sha256:67cfa082ff2991bba5add38a7d4aeba2e41829c6012f7a333996c67af33013dc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:INJDJOVVZJOLDJKLEVYF2PRXEE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MutualNet: Adaptive ConvNet via Mutual Learning from Different Model Configurations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Chen, Matias Mendieta, Minwoo Lee, Mubarak Shah, Pu Wang, Ravikumar Balakrishnan, Sijie Zhu, Tao Han, Taojiannan Yang","submitted_at":"2021-05-14T22:30:13Z","abstract_excerpt":"Most existing deep neural networks are static, which means they can only do inference at a fixed complexity. But the resource budget can vary substantially across different devices. Even on a single device, the affordable budget can change with different scenarios, and repeatedly training networks for each required budget would be incredibly expensive. Therefore, in this work, we propose a general method called MutualNet to train a single network that can run at a diverse set of resource constraints. Our method trains a cohort of model configurations with various network widths and input resol"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.07085","kind":"arxiv","version":2},"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/2105.07085/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":"2026-07-05T03:44:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kj31levKVTV2HcLog3MsYJ5tyEZ+hrvJS+wMnleqB9e0P07nNyQJMcvB8TrxySwCkKtYju6N04TwZoG7w+klCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T02:57:05.223039Z"},"content_sha256":"6fbe4d316b089d945c51196e2408c437a46e6e81ed647f620b9d3f8c59fe9c37","schema_version":"1.0","event_id":"sha256:6fbe4d316b089d945c51196e2408c437a46e6e81ed647f620b9d3f8c59fe9c37"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/INJDJOVVZJOLDJKLEVYF2PRXEE/bundle.json","state_url":"https://pith.science/pith/INJDJOVVZJOLDJKLEVYF2PRXEE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/INJDJOVVZJOLDJKLEVYF2PRXEE/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":"2026-07-07T02:57:05Z","links":{"resolver":"https://pith.science/pith/INJDJOVVZJOLDJKLEVYF2PRXEE","bundle":"https://pith.science/pith/INJDJOVVZJOLDJKLEVYF2PRXEE/bundle.json","state":"https://pith.science/pith/INJDJOVVZJOLDJKLEVYF2PRXEE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/INJDJOVVZJOLDJKLEVYF2PRXEE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:INJDJOVVZJOLDJKLEVYF2PRXEE","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":"69e6d7e8c2577a018ecb21ac085b01cc3aad03cc44d0c81de7f3a6aea9354137","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-14T22:30:13Z","title_canon_sha256":"be73834ff3f4eb7d555a162597e8801794fdf8721fbe1035c8957e5f91576471"},"schema_version":"1.0","source":{"id":"2105.07085","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.07085","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"arxiv_version","alias_value":"2105.07085v2","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.07085","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"pith_short_12","alias_value":"INJDJOVVZJOL","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"pith_short_16","alias_value":"INJDJOVVZJOLDJKL","created_at":"2026-07-05T03:44:29Z"},{"alias_kind":"pith_short_8","alias_value":"INJDJOVV","created_at":"2026-07-05T03:44:29Z"}],"graph_snapshots":[{"event_id":"sha256:6fbe4d316b089d945c51196e2408c437a46e6e81ed647f620b9d3f8c59fe9c37","target":"graph","created_at":"2026-07-05T03:44:29Z","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/2105.07085/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most existing deep neural networks are static, which means they can only do inference at a fixed complexity. But the resource budget can vary substantially across different devices. Even on a single device, the affordable budget can change with different scenarios, and repeatedly training networks for each required budget would be incredibly expensive. Therefore, in this work, we propose a general method called MutualNet to train a single network that can run at a diverse set of resource constraints. Our method trains a cohort of model configurations with various network widths and input resol","authors_text":"Chen Chen, Matias Mendieta, Minwoo Lee, Mubarak Shah, Pu Wang, Ravikumar Balakrishnan, Sijie Zhu, Tao Han, Taojiannan Yang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-14T22:30:13Z","title":"MutualNet: Adaptive ConvNet via Mutual Learning from Different Model Configurations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.07085","kind":"arxiv","version":2},"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":"sha256:67cfa082ff2991bba5add38a7d4aeba2e41829c6012f7a333996c67af33013dc","target":"record","created_at":"2026-07-05T03:44:29Z","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":"69e6d7e8c2577a018ecb21ac085b01cc3aad03cc44d0c81de7f3a6aea9354137","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-14T22:30:13Z","title_canon_sha256":"be73834ff3f4eb7d555a162597e8801794fdf8721fbe1035c8957e5f91576471"},"schema_version":"1.0","source":{"id":"2105.07085","kind":"arxiv","version":2}},"canonical_sha256":"435234bab5ca5cb1a54b25705d3e37211b582df6b1146806368e80a0e7319564","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"435234bab5ca5cb1a54b25705d3e37211b582df6b1146806368e80a0e7319564","first_computed_at":"2026-07-05T03:44:29.409569Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:44:29.409569Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HM4KWO7E6766rsDUeLn9RyKjtZ4IPZBi4BEf7dPBACATrZIzMqK50WlVdoy1/JCsdRFqK40n7RhCznX1iBnZBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:44:29.409946Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.07085","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:67cfa082ff2991bba5add38a7d4aeba2e41829c6012f7a333996c67af33013dc","sha256:6fbe4d316b089d945c51196e2408c437a46e6e81ed647f620b9d3f8c59fe9c37"],"state_sha256":"5cf519d07e176df2c6d6bbfbf47fdd2968d2c2e2ef4c7a7727c183ba1d6440b9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kWNAD1ei9ZqPOJYc3qn5jGKaPFKEXbQM7RWzE0QmqBWHk//KuzKXYBVgtExs8ov/UxF6gweYbMxyJWEDWfEQCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T02:57:05.226729Z","bundle_sha256":"acab38927e7b58bf5c62ccf01ed513f1e66ffae7ca3cc623bb6dce7ac7b5a46c"}}