{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:2TPL4FPZAASGLQXSJOKTSYOKOC","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":"1e7cb2afb5502bc9df423ba2802cad84763cc4a11532bb973ec9ceef1f0b61af","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-07-07T08:46:17Z","title_canon_sha256":"0988960de77fc07d230408e44ece23abb3aa5b15d04c315886ea0daf6d201386"},"schema_version":"1.0","source":{"id":"2207.03160","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.03160","created_at":"2026-07-05T04:43:21Z"},{"alias_kind":"arxiv_version","alias_value":"2207.03160v2","created_at":"2026-07-05T04:43:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.03160","created_at":"2026-07-05T04:43:21Z"},{"alias_kind":"pith_short_12","alias_value":"2TPL4FPZAASG","created_at":"2026-07-05T04:43:21Z"},{"alias_kind":"pith_short_16","alias_value":"2TPL4FPZAASGLQXS","created_at":"2026-07-05T04:43:21Z"},{"alias_kind":"pith_short_8","alias_value":"2TPL4FPZ","created_at":"2026-07-05T04:43:21Z"}],"graph_snapshots":[{"event_id":"sha256:c63e2d25ed469cfded4ed5bd00064bd2af489be6f54208b7e74715075f41c0d6","target":"graph","created_at":"2026-07-05T04:43:21Z","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/2207.03160/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Manifold learning (ML) aims to seek low-dimensional embedding from high-dimensional data. The problem is challenging on real-world datasets, especially with under-sampling data, and we find that previous methods perform poorly in this case. Generally, ML methods first transform input data into a low-dimensional embedding space to maintain the data's geometric structure and subsequently perform downstream tasks therein. The poor local connectivity of under-sampling data in the former step and inappropriate optimization objectives in the latter step leads to two problems: structural distortion a","authors_text":"Baigui Sun, Di Wu, Ge Wang, Hao Li, Lei Shang, Siyuan Li, Stan Z. Li, Zelin Zang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-07-07T08:46:17Z","title":"DLME: Deep Local-flatness Manifold Embedding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.03160","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:b1fa4e3b6a7183d9392f68293e624ab6a314de98b5b10603b7e4b13ff113a00a","target":"record","created_at":"2026-07-05T04:43:21Z","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":"1e7cb2afb5502bc9df423ba2802cad84763cc4a11532bb973ec9ceef1f0b61af","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-07-07T08:46:17Z","title_canon_sha256":"0988960de77fc07d230408e44ece23abb3aa5b15d04c315886ea0daf6d201386"},"schema_version":"1.0","source":{"id":"2207.03160","kind":"arxiv","version":2}},"canonical_sha256":"d4debe15f9002465c2f24b953961ca7090b6a9b1f81e7fa4367f438dd5caf1e7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d4debe15f9002465c2f24b953961ca7090b6a9b1f81e7fa4367f438dd5caf1e7","first_computed_at":"2026-07-05T04:43:21.151729Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:43:21.151729Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iIA+qj0sIfpDQ1OAx70A9swWRgWUCAREnbm3+cfFK6yqsJ1lqrP7nOhKDnHAhkIc40clM2kI7D/1As7y6XeEDw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:43:21.152137Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.03160","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b1fa4e3b6a7183d9392f68293e624ab6a314de98b5b10603b7e4b13ff113a00a","sha256:c63e2d25ed469cfded4ed5bd00064bd2af489be6f54208b7e74715075f41c0d6"],"state_sha256":"de2fdd7954b1e2738725b89f206bc48c9176b9a3255e7f173cda643cd9a4a851"}