{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:W7DAV6ZOJ7BFIREATT3NZXHFFH","short_pith_number":"pith:W7DAV6ZO","canonical_record":{"source":{"id":"2008.12094","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-27T13:04:27Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ebbc2f92b26eb36303c3f1209c4bed62eb4ff471bdccecf15383b87eb254a610","abstract_canon_sha256":"31b89c83882d6c171899b6ef252c36dbba50dbe19d5e8420db707a9cf51a094f"},"schema_version":"1.0"},"canonical_sha256":"b7c60afb2e4fc25444809cf6dcdce529de6f1dac133777eb4ca07c2d3ade4d96","source":{"kind":"arxiv","id":"2008.12094","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.12094","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"arxiv_version","alias_value":"2008.12094v1","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.12094","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"pith_short_12","alias_value":"W7DAV6ZOJ7BF","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"pith_short_16","alias_value":"W7DAV6ZOJ7BFIREA","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"pith_short_8","alias_value":"W7DAV6ZO","created_at":"2026-07-05T01:30:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:W7DAV6ZOJ7BFIREATT3NZXHFFH","target":"record","payload":{"canonical_record":{"source":{"id":"2008.12094","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-27T13:04:27Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ebbc2f92b26eb36303c3f1209c4bed62eb4ff471bdccecf15383b87eb254a610","abstract_canon_sha256":"31b89c83882d6c171899b6ef252c36dbba50dbe19d5e8420db707a9cf51a094f"},"schema_version":"1.0"},"canonical_sha256":"b7c60afb2e4fc25444809cf6dcdce529de6f1dac133777eb4ca07c2d3ade4d96","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:30:56.771488Z","signature_b64":"soGGLVESl5+/p9UJ9R4ZqcehNIpg3zcmfXfLKY4U8aIxr7hLiaoDuIe2TqeTSw+AUbK+4c7L5GIffwELk1nqBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7c60afb2e4fc25444809cf6dcdce529de6f1dac133777eb4ca07c2d3ade4d96","last_reissued_at":"2026-07-05T01:30:56.771138Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:30:56.771138Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.12094","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":"2026-07-05T01:30:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WIfeR/ujNzUAOAw6WyrKo7HQ8eald/13Nr/Y7tANltKzvF9xeFeKXPvR+O/Or06wtzthANGjfvvF5EnVsXW8CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T06:21:58.739960Z"},"content_sha256":"68eadd6db017bf76970ec51e155745bb4d49f028e81f3b2f060b619e391a98a3","schema_version":"1.0","event_id":"sha256:68eadd6db017bf76970ec51e155745bb4d49f028e81f3b2f060b619e391a98a3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:W7DAV6ZOJ7BFIREATT3NZXHFFH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Benlin Liu, Cho-Jui Hsieh, Jie Zhou, Jiwen Lu, Yongming Rao","submitted_at":"2020-08-27T13:04:27Z","abstract_excerpt":"Knowledge Distillation (KD) has been one of the most popu-lar methods to learn a compact model. However, it still suffers from highdemand in time and computational resources caused by sequential train-ing pipeline. Furthermore, the soft targets from deeper models do notoften serve as good cues for the shallower models due to the gap of com-patibility. In this work, we consider these two problems at the same time.Specifically, we propose that better soft targets with higher compatibil-ity can be generated by using a label generator to fuse the feature mapsfrom deeper stages in a top-down manner"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.12094","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/2008.12094/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":"2026-07-05T01:30:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GqcebSfPjlFT3PZSNIMF0xhFw7cPGjs7yAral8+pmF9Wngxl8E3d3SS6lSc3dOpr7ic11aMeRnzsYPoRUt9cDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T06:21:58.742015Z"},"content_sha256":"bd5e55c0a8ddd44ccb339487ce0fc64da89bb194f33e3017ef5b7699bc73b211","schema_version":"1.0","event_id":"sha256:bd5e55c0a8ddd44ccb339487ce0fc64da89bb194f33e3017ef5b7699bc73b211"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W7DAV6ZOJ7BFIREATT3NZXHFFH/bundle.json","state_url":"https://pith.science/pith/W7DAV6ZOJ7BFIREATT3NZXHFFH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W7DAV6ZOJ7BFIREATT3NZXHFFH/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":"2026-08-15T06:21:58Z","links":{"resolver":"https://pith.science/pith/W7DAV6ZOJ7BFIREATT3NZXHFFH","bundle":"https://pith.science/pith/W7DAV6ZOJ7BFIREATT3NZXHFFH/bundle.json","state":"https://pith.science/pith/W7DAV6ZOJ7BFIREATT3NZXHFFH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W7DAV6ZOJ7BFIREATT3NZXHFFH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:W7DAV6ZOJ7BFIREATT3NZXHFFH","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":"31b89c83882d6c171899b6ef252c36dbba50dbe19d5e8420db707a9cf51a094f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-27T13:04:27Z","title_canon_sha256":"ebbc2f92b26eb36303c3f1209c4bed62eb4ff471bdccecf15383b87eb254a610"},"schema_version":"1.0","source":{"id":"2008.12094","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.12094","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"arxiv_version","alias_value":"2008.12094v1","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.12094","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"pith_short_12","alias_value":"W7DAV6ZOJ7BF","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"pith_short_16","alias_value":"W7DAV6ZOJ7BFIREA","created_at":"2026-07-05T01:30:56Z"},{"alias_kind":"pith_short_8","alias_value":"W7DAV6ZO","created_at":"2026-07-05T01:30:56Z"}],"graph_snapshots":[{"event_id":"sha256:bd5e55c0a8ddd44ccb339487ce0fc64da89bb194f33e3017ef5b7699bc73b211","target":"graph","created_at":"2026-07-05T01:30:56Z","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/2008.12094/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge Distillation (KD) has been one of the most popu-lar methods to learn a compact model. However, it still suffers from highdemand in time and computational resources caused by sequential train-ing pipeline. Furthermore, the soft targets from deeper models do notoften serve as good cues for the shallower models due to the gap of com-patibility. In this work, we consider these two problems at the same time.Specifically, we propose that better soft targets with higher compatibil-ity can be generated by using a label generator to fuse the feature mapsfrom deeper stages in a top-down manner","authors_text":"Benlin Liu, Cho-Jui Hsieh, Jie Zhou, Jiwen Lu, Yongming Rao","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-27T13:04:27Z","title":"MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.12094","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":"sha256:68eadd6db017bf76970ec51e155745bb4d49f028e81f3b2f060b619e391a98a3","target":"record","created_at":"2026-07-05T01:30:56Z","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":"31b89c83882d6c171899b6ef252c36dbba50dbe19d5e8420db707a9cf51a094f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-27T13:04:27Z","title_canon_sha256":"ebbc2f92b26eb36303c3f1209c4bed62eb4ff471bdccecf15383b87eb254a610"},"schema_version":"1.0","source":{"id":"2008.12094","kind":"arxiv","version":1}},"canonical_sha256":"b7c60afb2e4fc25444809cf6dcdce529de6f1dac133777eb4ca07c2d3ade4d96","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7c60afb2e4fc25444809cf6dcdce529de6f1dac133777eb4ca07c2d3ade4d96","first_computed_at":"2026-07-05T01:30:56.771138Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:30:56.771138Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"soGGLVESl5+/p9UJ9R4ZqcehNIpg3zcmfXfLKY4U8aIxr7hLiaoDuIe2TqeTSw+AUbK+4c7L5GIffwELk1nqBg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:30:56.771488Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.12094","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68eadd6db017bf76970ec51e155745bb4d49f028e81f3b2f060b619e391a98a3","sha256:bd5e55c0a8ddd44ccb339487ce0fc64da89bb194f33e3017ef5b7699bc73b211"],"state_sha256":"74f5c26d4829a110f912ea3befc330ee1aa10e9c62dbb3464555069c1cdf47aa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vn7fIpNh6E/5OHrgHgs5wgEFNIwa82K3Wg4coWwwvy6HXKlhf0QPo4VfAx31Qj1ejEv0TqNefxIQCHGitRHgBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T06:21:58.804885Z","bundle_sha256":"5f843a774347a63ddbf4ecc1a217b7db5e2ffc751ad9cf9e25f8707c6323456f"}}