{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:FYWH4DCOCFM6ASI5U4GW267DXA","short_pith_number":"pith:FYWH4DCO","schema_version":"1.0","canonical_sha256":"2e2c7e0c4e1159e0491da70d6d7be3b81de540382f08b5f07a95663c3e5ff0f6","source":{"kind":"arxiv","id":"2602.14486","version":2},"attestation_state":"computed","paper":{"title":"Revisiting the Platonic Representation Hypothesis: An Aristotelian View","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.NE"],"primary_cat":"cs.LG","authors_text":"Fabian Gr\\\"oger, Maria Brbi\\'c, Shuo Wen","submitted_at":"2026-02-16T06:01:23Z","abstract_excerpt":"The Platonic Representation Hypothesis suggests that representations from neural networks are converging to a common statistical model of reality. We show that the existing metrics used to measure representational similarity are confounded by network scale: increasing model depth or width can systematically inflate representational similarity scores. To correct these effects, we introduce a permutation-based null-calibration framework that transforms any representational similarity metric into a calibrated score with statistical guarantees. We revisit the Platonic Representation Hypothesis wit"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2602.14486","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-02-16T06:01:23Z","cross_cats_sorted":["cs.AI","cs.CV","cs.NE"],"title_canon_sha256":"b03d45e3b885120a788efb458350bbb9d36035d97b5e27e218df9058b739c07b","abstract_canon_sha256":"6d44ccd64f20a6ca3cd4679f1edf4c04cace7e8c0b160b04cb738ec5ee53ca35"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-26T01:15:49.460901Z","signature_b64":"O9JdEANM7fzwHYI8RGJnaj5dTMMymLl4XpP+UQYA5tCBxHUQGahP2zGl23d3GIVdQwllQStbVKKindMgdxarCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2e2c7e0c4e1159e0491da70d6d7be3b81de540382f08b5f07a95663c3e5ff0f6","last_reissued_at":"2026-06-26T01:15:49.460390Z","signature_status":"signed_v1","first_computed_at":"2026-06-26T01:15:49.460390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Revisiting the Platonic Representation Hypothesis: An Aristotelian View","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.NE"],"primary_cat":"cs.LG","authors_text":"Fabian Gr\\\"oger, Maria Brbi\\'c, Shuo Wen","submitted_at":"2026-02-16T06:01:23Z","abstract_excerpt":"The Platonic Representation Hypothesis suggests that representations from neural networks are converging to a common statistical model of reality. We show that the existing metrics used to measure representational similarity are confounded by network scale: increasing model depth or width can systematically inflate representational similarity scores. To correct these effects, we introduce a permutation-based null-calibration framework that transforms any representational similarity metric into a calibrated score with statistical guarantees. We revisit the Platonic Representation Hypothesis wit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.14486","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/2602.14486/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2602.14486","created_at":"2026-06-26T01:15:49.460449+00:00"},{"alias_kind":"arxiv_version","alias_value":"2602.14486v2","created_at":"2026-06-26T01:15:49.460449+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.14486","created_at":"2026-06-26T01:15:49.460449+00:00"},{"alias_kind":"pith_short_12","alias_value":"FYWH4DCOCFM6","created_at":"2026-06-26T01:15:49.460449+00:00"},{"alias_kind":"pith_short_16","alias_value":"FYWH4DCOCFM6ASI5","created_at":"2026-06-26T01:15:49.460449+00:00"},{"alias_kind":"pith_short_8","alias_value":"FYWH4DCO","created_at":"2026-06-26T01:15:49.460449+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":8,"internal_anchor_count":8,"sample":[{"citing_arxiv_id":"2605.23315","citing_title":"Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning","ref_index":8,"is_internal_anchor":true},{"citing_arxiv_id":"2505.17101","citing_title":"A quantitative analysis of semantic information in deep representations of text and images","ref_index":3,"is_internal_anchor":true},{"citing_arxiv_id":"2605.20337","citing_title":"Capability $\\neq$ Interpretability: Human Interpretability of Vision Foundation Models","ref_index":46,"is_internal_anchor":true},{"citing_arxiv_id":"2605.18667","citing_title":"Better Together: Evaluating the Complementarity of Earth Embedding Models","ref_index":8,"is_internal_anchor":true},{"citing_arxiv_id":"2605.13675","citing_title":"Characterizing Universal Object Representations Across Vision Models","ref_index":18,"is_internal_anchor":true},{"citing_arxiv_id":"2604.21691","citing_title":"There Will Be a Scientific Theory of Deep Learning","ref_index":251,"is_internal_anchor":true},{"citing_arxiv_id":"2604.16487","citing_title":"Geometry-Aware CLIP Retrieval via Local Cross-Modal Alignment and Steering","ref_index":4,"is_internal_anchor":true},{"citing_arxiv_id":"2604.18572","citing_title":"Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale","ref_index":29,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA","json":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA.json","graph_json":"https://pith.science/api/pith-number/FYWH4DCOCFM6ASI5U4GW267DXA/graph.json","events_json":"https://pith.science/api/pith-number/FYWH4DCOCFM6ASI5U4GW267DXA/events.json","paper":"https://pith.science/paper/FYWH4DCO"},"agent_actions":{"view_html":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA","download_json":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA.json","view_paper":"https://pith.science/paper/FYWH4DCO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2602.14486&json=true","fetch_graph":"https://pith.science/api/pith-number/FYWH4DCOCFM6ASI5U4GW267DXA/graph.json","fetch_events":"https://pith.science/api/pith-number/FYWH4DCOCFM6ASI5U4GW267DXA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA/action/storage_attestation","attest_author":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA/action/author_attestation","sign_citation":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA/action/citation_signature","submit_replication":"https://pith.science/pith/FYWH4DCOCFM6ASI5U4GW267DXA/action/replication_record"}},"created_at":"2026-06-26T01:15:49.460449+00:00","updated_at":"2026-06-26T01:15:49.460449+00:00"}