{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:H7EOTPDQRD22LU4MEXZSWW5DNA","short_pith_number":"pith:H7EOTPDQ","canonical_record":{"source":{"id":"2004.02757","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-19T22:17:02Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"98db53abeb28466586a019b6960a8598a94881943a0610ce75e92990ce8f4e03","abstract_canon_sha256":"9d0afcbb91ddfdd169e26db1e5d909800f7655ea8f49ab126e138bdf15513f97"},"schema_version":"1.0"},"canonical_sha256":"3fc8e9bc7088f5a5d38c25f32b5ba36809d5c465335f3b4964b4e378043a6963","source":{"kind":"arxiv","id":"2004.02757","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.02757","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"2004.02757v2","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.02757","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"H7EOTPDQRD22","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"pith_short_16","alias_value":"H7EOTPDQRD22LU4M","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"pith_short_8","alias_value":"H7EOTPDQ","created_at":"2026-07-05T00:54:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:H7EOTPDQRD22LU4MEXZSWW5DNA","target":"record","payload":{"canonical_record":{"source":{"id":"2004.02757","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-19T22:17:02Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"98db53abeb28466586a019b6960a8598a94881943a0610ce75e92990ce8f4e03","abstract_canon_sha256":"9d0afcbb91ddfdd169e26db1e5d909800f7655ea8f49ab126e138bdf15513f97"},"schema_version":"1.0"},"canonical_sha256":"3fc8e9bc7088f5a5d38c25f32b5ba36809d5c465335f3b4964b4e378043a6963","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:54:33.787530Z","signature_b64":"FaVo3+8aJh9xZWEi4uxiz72kYj1TYu/MTc/Ecit9kMC0Bs3nIA2dkUSyx/O1sQrB7CdLzMZprWy0RY31HoB4DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3fc8e9bc7088f5a5d38c25f32b5ba36809d5c465335f3b4964b4e378043a6963","last_reissued_at":"2026-07-05T00:54:33.787085Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:54:33.787085Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.02757","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":"2026-07-05T00:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EZ/Ll1xyibX72rHyZJCmLXMxlFhYKtA+5yjFjqoDf7S9e1d+PBkbs8pKdvkMc/jXrHYHfdjv5WK2XACOqqBzCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T12:12:52.426676Z"},"content_sha256":"73130d9e2227f214826bacff5b1d615f94f3abafdbce16ce099d735c6179d229","schema_version":"1.0","event_id":"sha256:73130d9e2227f214826bacff5b1d615f94f3abafdbce16ce099d735c6179d229"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:H7EOTPDQRD22LU4MEXZSWW5DNA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Deep Representation Learning by Adaptive Latent Space Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CV","authors_text":"Chengliang Dai, Rui Zhou, Shuo Wang, Wenjia Bai, Yike Guo, Yuanhan Mo, Zhongzhao Teng","submitted_at":"2020-03-19T22:17:02Z","abstract_excerpt":"Supervised deep learning requires a large amount of training samples with annotations (e.g. label class for classification task, pixel- or voxel-wised label map for segmentation tasks), which are expensive and time-consuming to obtain. During the training of a deep neural network, the annotated samples are fed into the network in a mini-batch way, where they are often regarded of equal importance. However, some of the samples may become less informative during training, as the magnitude of the gradient start to vanish for these samples. In the meantime, other samples of higher utility or hardn"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.02757","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/2004.02757/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":"2026-07-05T00:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nhaq6KBvPhbV1XfRBToB7ANtFvG1zNrhFEEwuGM7Q5zfCl3MCWB1S8gfevVBWDPQPSk0p+KQUTvPIAKHwq9uBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T12:12:52.427063Z"},"content_sha256":"61c05d26b2b5f8e509d52cc1a5324b1621534e0c95441f24ddcbfc069e98a31d","schema_version":"1.0","event_id":"sha256:61c05d26b2b5f8e509d52cc1a5324b1621534e0c95441f24ddcbfc069e98a31d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H7EOTPDQRD22LU4MEXZSWW5DNA/bundle.json","state_url":"https://pith.science/pith/H7EOTPDQRD22LU4MEXZSWW5DNA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H7EOTPDQRD22LU4MEXZSWW5DNA/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":"2026-07-05T12:12:52Z","links":{"resolver":"https://pith.science/pith/H7EOTPDQRD22LU4MEXZSWW5DNA","bundle":"https://pith.science/pith/H7EOTPDQRD22LU4MEXZSWW5DNA/bundle.json","state":"https://pith.science/pith/H7EOTPDQRD22LU4MEXZSWW5DNA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H7EOTPDQRD22LU4MEXZSWW5DNA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:H7EOTPDQRD22LU4MEXZSWW5DNA","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":"9d0afcbb91ddfdd169e26db1e5d909800f7655ea8f49ab126e138bdf15513f97","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-19T22:17:02Z","title_canon_sha256":"98db53abeb28466586a019b6960a8598a94881943a0610ce75e92990ce8f4e03"},"schema_version":"1.0","source":{"id":"2004.02757","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.02757","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"2004.02757v2","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.02757","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"H7EOTPDQRD22","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"pith_short_16","alias_value":"H7EOTPDQRD22LU4M","created_at":"2026-07-05T00:54:33Z"},{"alias_kind":"pith_short_8","alias_value":"H7EOTPDQ","created_at":"2026-07-05T00:54:33Z"}],"graph_snapshots":[{"event_id":"sha256:61c05d26b2b5f8e509d52cc1a5324b1621534e0c95441f24ddcbfc069e98a31d","target":"graph","created_at":"2026-07-05T00:54:33Z","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/2004.02757/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Supervised deep learning requires a large amount of training samples with annotations (e.g. label class for classification task, pixel- or voxel-wised label map for segmentation tasks), which are expensive and time-consuming to obtain. During the training of a deep neural network, the annotated samples are fed into the network in a mini-batch way, where they are often regarded of equal importance. However, some of the samples may become less informative during training, as the magnitude of the gradient start to vanish for these samples. In the meantime, other samples of higher utility or hardn","authors_text":"Chengliang Dai, Rui Zhou, Shuo Wang, Wenjia Bai, Yike Guo, Yuanhan Mo, Zhongzhao Teng","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-19T22:17:02Z","title":"Efficient Deep Representation Learning by Adaptive Latent Space Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.02757","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":"sha256:73130d9e2227f214826bacff5b1d615f94f3abafdbce16ce099d735c6179d229","target":"record","created_at":"2026-07-05T00:54:33Z","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":"9d0afcbb91ddfdd169e26db1e5d909800f7655ea8f49ab126e138bdf15513f97","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-19T22:17:02Z","title_canon_sha256":"98db53abeb28466586a019b6960a8598a94881943a0610ce75e92990ce8f4e03"},"schema_version":"1.0","source":{"id":"2004.02757","kind":"arxiv","version":2}},"canonical_sha256":"3fc8e9bc7088f5a5d38c25f32b5ba36809d5c465335f3b4964b4e378043a6963","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3fc8e9bc7088f5a5d38c25f32b5ba36809d5c465335f3b4964b4e378043a6963","first_computed_at":"2026-07-05T00:54:33.787085Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:54:33.787085Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FaVo3+8aJh9xZWEi4uxiz72kYj1TYu/MTc/Ecit9kMC0Bs3nIA2dkUSyx/O1sQrB7CdLzMZprWy0RY31HoB4DA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:54:33.787530Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.02757","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73130d9e2227f214826bacff5b1d615f94f3abafdbce16ce099d735c6179d229","sha256:61c05d26b2b5f8e509d52cc1a5324b1621534e0c95441f24ddcbfc069e98a31d"],"state_sha256":"19f17b2c8f5308fc1db9b07d152beb638adde507a659f5bd566e9a9ae61f602c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"znaR+/85lgjGIE+7ZslIN9LRMWVkSSj+iDLbUnHFrX59vGWaj20kbhVStuZtYnspQePU1nOwguXPr7XIpLC6Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T12:12:52.428950Z","bundle_sha256":"1e35814628355b3e47a3a6f6a9e6378c53aa84d6ac84f88bfd5a797cdfe1cf4d"}}