{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:K6YBUQVE7KCJOV3BRUQQVPY4EC","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":"59d5a62394b4774524684e0019a327d713d14140d0926225fcdefc97ca7bb774","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-26T15:00:42Z","title_canon_sha256":"37deb40d960c11e0ede38fb0fb530d46c86efeeec6b5464844cbdb111af5918e"},"schema_version":"1.0","source":{"id":"2212.13180","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.13180","created_at":"2026-07-05T05:28:17Z"},{"alias_kind":"arxiv_version","alias_value":"2212.13180v1","created_at":"2026-07-05T05:28:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.13180","created_at":"2026-07-05T05:28:17Z"},{"alias_kind":"pith_short_12","alias_value":"K6YBUQVE7KCJ","created_at":"2026-07-05T05:28:17Z"},{"alias_kind":"pith_short_16","alias_value":"K6YBUQVE7KCJOV3B","created_at":"2026-07-05T05:28:17Z"},{"alias_kind":"pith_short_8","alias_value":"K6YBUQVE","created_at":"2026-07-05T05:28:17Z"}],"graph_snapshots":[{"event_id":"sha256:5670be1bfde1a68ac2638efc59c380a86336ca1449d5d7d7b0fa17674d08c9c2","target":"graph","created_at":"2026-07-05T05:28:17Z","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/2212.13180/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, large-scale pre-trained models have shown their advantages in many tasks. However, due to the huge computational complexity and storage requirements, it is challenging to apply the large-scale model to real scenes. A common solution is knowledge distillation which regards the large-scale model as a teacher model and helps to train a small student model to obtain a competitive performance. Cross-task Knowledge distillation expands the application scenarios of the large-scale pre-trained model. Existing knowledge distillation works focus on directly mimicking the final prediction or th","authors_text":"Aming Wu, Deng Li, Qi Tian, Yahong Han","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-26T15:00:42Z","title":"Prototype-guided Cross-task Knowledge Distillation for Large-scale Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.13180","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:af7436549e6410c2159e17a640f89b9e1fc584940bf25f8858f30322a65f3997","target":"record","created_at":"2026-07-05T05:28:17Z","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":"59d5a62394b4774524684e0019a327d713d14140d0926225fcdefc97ca7bb774","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-12-26T15:00:42Z","title_canon_sha256":"37deb40d960c11e0ede38fb0fb530d46c86efeeec6b5464844cbdb111af5918e"},"schema_version":"1.0","source":{"id":"2212.13180","kind":"arxiv","version":1}},"canonical_sha256":"57b01a42a4fa849757618d210abf1c20835c01c7e29bd1caf39b5537fd36314b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"57b01a42a4fa849757618d210abf1c20835c01c7e29bd1caf39b5537fd36314b","first_computed_at":"2026-07-05T05:28:17.725653Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:28:17.725653Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1G+BLUSn2VBwGgLMS8EcPj2SF6zbL3ZlaM40ebR+ltGZc2kyddsTPsgODbRRqwWE1wUwBAbkTg5SZAucLODyBA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:28:17.726128Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.13180","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af7436549e6410c2159e17a640f89b9e1fc584940bf25f8858f30322a65f3997","sha256:5670be1bfde1a68ac2638efc59c380a86336ca1449d5d7d7b0fa17674d08c9c2"],"state_sha256":"10b6c6f6bdfa80bf52ef982b52c0096ad91c23b5ebfbae16079e936e9bdbdf9a"}