{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:6FCE5PEHVVCTSDYM6QIBSA2IMZ","short_pith_number":"pith:6FCE5PEH","canonical_record":{"source":{"id":"2608.10857","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-11T12:30:19Z","cross_cats_sorted":[],"title_canon_sha256":"5b2672365184dfb99481041752d1b0c6fa3e95be8e08fd6b71cdec072b4d82f8","abstract_canon_sha256":"cab8120770e69ba0a095428ec34bfa3a6168da657c011ce6fa27519bfbb49857"},"schema_version":"1.0"},"canonical_sha256":"f1444ebc87ad45390f0cf410190348665838dbea3aa8bfda162f51bf6be20ee5","source":{"kind":"arxiv","id":"2608.10857","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.10857","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"arxiv_version","alias_value":"2608.10857v1","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.10857","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"pith_short_12","alias_value":"6FCE5PEHVVCT","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"pith_short_16","alias_value":"6FCE5PEHVVCTSDYM","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"pith_short_8","alias_value":"6FCE5PEH","created_at":"2026-08-12T01:23:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:6FCE5PEHVVCTSDYM6QIBSA2IMZ","target":"record","payload":{"canonical_record":{"source":{"id":"2608.10857","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-11T12:30:19Z","cross_cats_sorted":[],"title_canon_sha256":"5b2672365184dfb99481041752d1b0c6fa3e95be8e08fd6b71cdec072b4d82f8","abstract_canon_sha256":"cab8120770e69ba0a095428ec34bfa3a6168da657c011ce6fa27519bfbb49857"},"schema_version":"1.0"},"canonical_sha256":"f1444ebc87ad45390f0cf410190348665838dbea3aa8bfda162f51bf6be20ee5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-12T01:23:34.797028Z","signature_b64":"y5faE8ROgXEos38jIItekm+E8qp4RsHWxV6d4WJQkfeiCFoIsSZ6BXINJPWE7rDq5BG+nSj1mnSwpyOas3NECw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f1444ebc87ad45390f0cf410190348665838dbea3aa8bfda162f51bf6be20ee5","last_reissued_at":"2026-08-12T01:23:34.795262Z","signature_status":"signed_v1","first_computed_at":"2026-08-12T01:23:34.795262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.10857","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":"2026-08-12T01:23:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IU6HegUCAmHyWPPTpzniB4vkUCtjWyu926bDzmcNnpVA3GNVz86Kcjap8CnZbmA7M0NjkiHYhT20mdtYmeo4CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T04:20:48.971315Z"},"content_sha256":"5ffb6db9991dd9bc94d2bcfa5a0651ee015436598ec375d2d97138f3a450c18b","schema_version":"1.0","event_id":"sha256:5ffb6db9991dd9bc94d2bcfa5a0651ee015436598ec375d2d97138f3a450c18b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:6FCE5PEHVVCTSDYM6QIBSA2IMZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FiGuRO: Intrinsic Dimension Estimation for Multi-Modal Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Caroline Uhler, Sana Tonekaboni, Viktoria Schuster","submitted_at":"2026-08-11T12:30:19Z","abstract_excerpt":"Determining the complexity, or Intrinsic Dimension (ID), of data is fundamental to efficient and interpretable representation learning. This is particularly challenging in multi-modal settings when trying to learn disentangled representations for shared and private information. Existing techniques leave a critical gap: they are often static, uni-modal, or in the case of contrastive methods, adapt only to the shared ID implicitly. We introduce Fidelity-Guided Rank Optimization (FiGuRO), a framework for approximating the ID of uni- and multi-modal data under constraints of model capacity and hyp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.10857","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/2608.10857/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":"2026-08-12T01:23:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UMru2/iQaaYIPispgh9jpq4ZDNKcmhh4sgzqSz7lD1G4UVctunhSSYw6/yWhomdd30stVybQAM1RaqG38NhVBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T04:20:48.971799Z"},"content_sha256":"5cb5ce2611ac9bba44503d77cc0a3b329f2ac4a416e692452e9142498022a2e9","schema_version":"1.0","event_id":"sha256:5cb5ce2611ac9bba44503d77cc0a3b329f2ac4a416e692452e9142498022a2e9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6FCE5PEHVVCTSDYM6QIBSA2IMZ/bundle.json","state_url":"https://pith.science/pith/6FCE5PEHVVCTSDYM6QIBSA2IMZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6FCE5PEHVVCTSDYM6QIBSA2IMZ/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":"2026-08-13T04:20:48Z","links":{"resolver":"https://pith.science/pith/6FCE5PEHVVCTSDYM6QIBSA2IMZ","bundle":"https://pith.science/pith/6FCE5PEHVVCTSDYM6QIBSA2IMZ/bundle.json","state":"https://pith.science/pith/6FCE5PEHVVCTSDYM6QIBSA2IMZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6FCE5PEHVVCTSDYM6QIBSA2IMZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:6FCE5PEHVVCTSDYM6QIBSA2IMZ","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":"cab8120770e69ba0a095428ec34bfa3a6168da657c011ce6fa27519bfbb49857","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-11T12:30:19Z","title_canon_sha256":"5b2672365184dfb99481041752d1b0c6fa3e95be8e08fd6b71cdec072b4d82f8"},"schema_version":"1.0","source":{"id":"2608.10857","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.10857","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"arxiv_version","alias_value":"2608.10857v1","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.10857","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"pith_short_12","alias_value":"6FCE5PEHVVCT","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"pith_short_16","alias_value":"6FCE5PEHVVCTSDYM","created_at":"2026-08-12T01:23:34Z"},{"alias_kind":"pith_short_8","alias_value":"6FCE5PEH","created_at":"2026-08-12T01:23:34Z"}],"graph_snapshots":[{"event_id":"sha256:5cb5ce2611ac9bba44503d77cc0a3b329f2ac4a416e692452e9142498022a2e9","target":"graph","created_at":"2026-08-12T01:23:34Z","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/2608.10857/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Determining the complexity, or Intrinsic Dimension (ID), of data is fundamental to efficient and interpretable representation learning. This is particularly challenging in multi-modal settings when trying to learn disentangled representations for shared and private information. Existing techniques leave a critical gap: they are often static, uni-modal, or in the case of contrastive methods, adapt only to the shared ID implicitly. We introduce Fidelity-Guided Rank Optimization (FiGuRO), a framework for approximating the ID of uni- and multi-modal data under constraints of model capacity and hyp","authors_text":"Caroline Uhler, Sana Tonekaboni, Viktoria Schuster","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-11T12:30:19Z","title":"FiGuRO: Intrinsic Dimension Estimation for Multi-Modal Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.10857","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":"sha256:5ffb6db9991dd9bc94d2bcfa5a0651ee015436598ec375d2d97138f3a450c18b","target":"record","created_at":"2026-08-12T01:23:34Z","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":"cab8120770e69ba0a095428ec34bfa3a6168da657c011ce6fa27519bfbb49857","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-11T12:30:19Z","title_canon_sha256":"5b2672365184dfb99481041752d1b0c6fa3e95be8e08fd6b71cdec072b4d82f8"},"schema_version":"1.0","source":{"id":"2608.10857","kind":"arxiv","version":1}},"canonical_sha256":"f1444ebc87ad45390f0cf410190348665838dbea3aa8bfda162f51bf6be20ee5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f1444ebc87ad45390f0cf410190348665838dbea3aa8bfda162f51bf6be20ee5","first_computed_at":"2026-08-12T01:23:34.795262Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-12T01:23:34.795262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"y5faE8ROgXEos38jIItekm+E8qp4RsHWxV6d4WJQkfeiCFoIsSZ6BXINJPWE7rDq5BG+nSj1mnSwpyOas3NECw==","signature_status":"signed_v1","signed_at":"2026-08-12T01:23:34.797028Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.10857","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5ffb6db9991dd9bc94d2bcfa5a0651ee015436598ec375d2d97138f3a450c18b","sha256:5cb5ce2611ac9bba44503d77cc0a3b329f2ac4a416e692452e9142498022a2e9"],"state_sha256":"29703ce4966e5c32defefd541614b80418c4fdbe3c5cf0f9d9e4b167cd2e6378"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+N1BcVMS7JLvF7fnjzpdg2Db9dpFcNOvAIRPUquAomvRjRtpBUf+v3Zh1r9rT1zNmDJePW96cE7HPkrMl8SjDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T04:20:48.975265Z","bundle_sha256":"f2696025e7c5f5fcb56ac1fadc01bf3d2c6965af49f029e07adc65f9d539fa0a"}}