{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4ERL5CVPBPXZTFS6T2THJT2UBM","short_pith_number":"pith:4ERL5CVP","canonical_record":{"source":{"id":"2411.11954","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2024-11-18T19:00:01Z","cross_cats_sorted":["cond-mat.quant-gas","cond-mat.stat-mech"],"title_canon_sha256":"bd7d4364a816e52aea694da60c50ee4a00e7298bef9936e229202b2bb0a0a32e","abstract_canon_sha256":"a3b0c29ee873f8b50c9488036fed41f3ea5f6a8befa921df9777c3eeac5e8126"},"schema_version":"1.0"},"canonical_sha256":"e122be8aaf0bef99965e9ea674cf540b284a4521855a08d3e004c608321798ae","source":{"kind":"arxiv","id":"2411.11954","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.11954","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"arxiv_version","alias_value":"2411.11954v1","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.11954","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"pith_short_12","alias_value":"4ERL5CVPBPXZ","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"pith_short_16","alias_value":"4ERL5CVPBPXZTFS6","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"pith_short_8","alias_value":"4ERL5CVP","created_at":"2026-07-05T09:37:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4ERL5CVPBPXZTFS6T2THJT2UBM","target":"record","payload":{"canonical_record":{"source":{"id":"2411.11954","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2024-11-18T19:00:01Z","cross_cats_sorted":["cond-mat.quant-gas","cond-mat.stat-mech"],"title_canon_sha256":"bd7d4364a816e52aea694da60c50ee4a00e7298bef9936e229202b2bb0a0a32e","abstract_canon_sha256":"a3b0c29ee873f8b50c9488036fed41f3ea5f6a8befa921df9777c3eeac5e8126"},"schema_version":"1.0"},"canonical_sha256":"e122be8aaf0bef99965e9ea674cf540b284a4521855a08d3e004c608321798ae","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:37:14.440810Z","signature_b64":"+AKNxGfeBwPFlz+Fb6C1mOjOKVvehCCqvyIqhDzeGdUIVIf8PqFCNKjM44P07U6nFuvVbZu/y2ymlfbXWL7zBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e122be8aaf0bef99965e9ea674cf540b284a4521855a08d3e004c608321798ae","last_reissued_at":"2026-07-05T09:37:14.440382Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:37:14.440382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.11954","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":"2026-07-05T09:37:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CQ01f7P8p3j6z/qRaYzPe+xbCWWmfShV8genkZsTWhgTs3IQvba9F/kj8nm4Oni+EqJLHDa5lp+KUhxRG179Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T01:10:46.886466Z"},"content_sha256":"044a1fd37f5322be2c51c2ee38fa8e0b050cd30b4aedf321c5b42a98bd4546d2","schema_version":"1.0","event_id":"sha256:044a1fd37f5322be2c51c2ee38fa8e0b050cd30b4aedf321c5b42a98bd4546d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4ERL5CVPBPXZTFS6T2THJT2UBM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning complexity gradually in quantum machine learning models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cond-mat.quant-gas","cond-mat.stat-mech"],"primary_cat":"quant-ph","authors_text":"Carlos Bravo-Prieto, Erik Recio-Armengol, Franz J. Schreiber, Jens Eisert","submitted_at":"2024-11-18T19:00:01Z","abstract_excerpt":"Quantum machine learning is an emergent field that continues to draw significant interest for its potential to offer improvements over classical algorithms in certain areas. However, training quantum models remains a challenging task, largely because of the difficulty in establishing an effective inductive bias when solving high-dimensional problems. In this work, we propose a training framework that prioritizes informative data points over the entire training set. This approach draws inspiration from classical techniques such as curriculum learning and hard example mining to introduce an addi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.11954","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/2411.11954/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":"2026-07-05T09:37:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FWY69QzDrdCwN+qjEmQiuu7J0QLnJRcIYq8Lg0Ja/b8mBGqIKNFig9uLerMvc0ejzKneHBQwcDaO7GvV281SBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T01:10:46.887071Z"},"content_sha256":"a4f4367594d1e1a01720af1df22db0118e6463fcf00a2186279696f167df88b0","schema_version":"1.0","event_id":"sha256:a4f4367594d1e1a01720af1df22db0118e6463fcf00a2186279696f167df88b0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4ERL5CVPBPXZTFS6T2THJT2UBM/bundle.json","state_url":"https://pith.science/pith/4ERL5CVPBPXZTFS6T2THJT2UBM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4ERL5CVPBPXZTFS6T2THJT2UBM/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":"2026-08-07T01:10:46Z","links":{"resolver":"https://pith.science/pith/4ERL5CVPBPXZTFS6T2THJT2UBM","bundle":"https://pith.science/pith/4ERL5CVPBPXZTFS6T2THJT2UBM/bundle.json","state":"https://pith.science/pith/4ERL5CVPBPXZTFS6T2THJT2UBM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4ERL5CVPBPXZTFS6T2THJT2UBM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4ERL5CVPBPXZTFS6T2THJT2UBM","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":"a3b0c29ee873f8b50c9488036fed41f3ea5f6a8befa921df9777c3eeac5e8126","cross_cats_sorted":["cond-mat.quant-gas","cond-mat.stat-mech"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2024-11-18T19:00:01Z","title_canon_sha256":"bd7d4364a816e52aea694da60c50ee4a00e7298bef9936e229202b2bb0a0a32e"},"schema_version":"1.0","source":{"id":"2411.11954","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.11954","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"arxiv_version","alias_value":"2411.11954v1","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.11954","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"pith_short_12","alias_value":"4ERL5CVPBPXZ","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"pith_short_16","alias_value":"4ERL5CVPBPXZTFS6","created_at":"2026-07-05T09:37:14Z"},{"alias_kind":"pith_short_8","alias_value":"4ERL5CVP","created_at":"2026-07-05T09:37:14Z"}],"graph_snapshots":[{"event_id":"sha256:a4f4367594d1e1a01720af1df22db0118e6463fcf00a2186279696f167df88b0","target":"graph","created_at":"2026-07-05T09:37:14Z","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/2411.11954/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quantum machine learning is an emergent field that continues to draw significant interest for its potential to offer improvements over classical algorithms in certain areas. However, training quantum models remains a challenging task, largely because of the difficulty in establishing an effective inductive bias when solving high-dimensional problems. In this work, we propose a training framework that prioritizes informative data points over the entire training set. This approach draws inspiration from classical techniques such as curriculum learning and hard example mining to introduce an addi","authors_text":"Carlos Bravo-Prieto, Erik Recio-Armengol, Franz J. Schreiber, Jens Eisert","cross_cats":["cond-mat.quant-gas","cond-mat.stat-mech"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2024-11-18T19:00:01Z","title":"Learning complexity gradually in quantum machine learning models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.11954","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":"sha256:044a1fd37f5322be2c51c2ee38fa8e0b050cd30b4aedf321c5b42a98bd4546d2","target":"record","created_at":"2026-07-05T09:37:14Z","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":"a3b0c29ee873f8b50c9488036fed41f3ea5f6a8befa921df9777c3eeac5e8126","cross_cats_sorted":["cond-mat.quant-gas","cond-mat.stat-mech"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2024-11-18T19:00:01Z","title_canon_sha256":"bd7d4364a816e52aea694da60c50ee4a00e7298bef9936e229202b2bb0a0a32e"},"schema_version":"1.0","source":{"id":"2411.11954","kind":"arxiv","version":1}},"canonical_sha256":"e122be8aaf0bef99965e9ea674cf540b284a4521855a08d3e004c608321798ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e122be8aaf0bef99965e9ea674cf540b284a4521855a08d3e004c608321798ae","first_computed_at":"2026-07-05T09:37:14.440382Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:37:14.440382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+AKNxGfeBwPFlz+Fb6C1mOjOKVvehCCqvyIqhDzeGdUIVIf8PqFCNKjM44P07U6nFuvVbZu/y2ymlfbXWL7zBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:37:14.440810Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.11954","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:044a1fd37f5322be2c51c2ee38fa8e0b050cd30b4aedf321c5b42a98bd4546d2","sha256:a4f4367594d1e1a01720af1df22db0118e6463fcf00a2186279696f167df88b0"],"state_sha256":"78d26ed67624e6e6078b70e619a61203980677d455923ae3919ca935f768a1d2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EXmuu7RC0IBCwp8DqWKn1/L6E+tG980af0s82DOrofs38zocz958PrSaeh0r8Wm3uYcFfbU2yyPrvB/ZFpOgCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T01:10:46.891799Z","bundle_sha256":"372bf82b8dcedc1882bcab684ee63a0b12f1d153aa5704d07361798707c68c7c"}}