{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5RYRRAWLMTW65JLSLSXHVCA3NE","short_pith_number":"pith:5RYRRAWL","canonical_record":{"source":{"id":"2308.15513","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-29T16:24:11Z","cross_cats_sorted":["cs.AI","q-bio.QM","stat.ML"],"title_canon_sha256":"978cfb10d07ffbc32e90f4e55ab1968ef8b111c2a3c065c34d5bc24a3c5f1986","abstract_canon_sha256":"157bc13faecb828ec6d1a3449ad51f72dd8853324b80d80de59a87de015cac72"},"schema_version":"1.0"},"canonical_sha256":"ec711882cb64edeea5725cae7a881b6934c200e422f6dcbe4296be6b310f3027","source":{"kind":"arxiv","id":"2308.15513","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.15513","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"arxiv_version","alias_value":"2308.15513v2","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.15513","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"pith_short_12","alias_value":"5RYRRAWLMTW6","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"pith_short_16","alias_value":"5RYRRAWLMTW65JLS","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"pith_short_8","alias_value":"5RYRRAWL","created_at":"2026-07-05T09:44:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5RYRRAWLMTW65JLSLSXHVCA3NE","target":"record","payload":{"canonical_record":{"source":{"id":"2308.15513","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-29T16:24:11Z","cross_cats_sorted":["cs.AI","q-bio.QM","stat.ML"],"title_canon_sha256":"978cfb10d07ffbc32e90f4e55ab1968ef8b111c2a3c065c34d5bc24a3c5f1986","abstract_canon_sha256":"157bc13faecb828ec6d1a3449ad51f72dd8853324b80d80de59a87de015cac72"},"schema_version":"1.0"},"canonical_sha256":"ec711882cb64edeea5725cae7a881b6934c200e422f6dcbe4296be6b310f3027","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:44:32.707267Z","signature_b64":"ED875SfXLh8zMwqBZXgaWjy9h+qr4LJ6qfw0LWbZDiVNf/3IBDru1XfzwooHwVExYPF2lso0XFIiKXcSOnptCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ec711882cb64edeea5725cae7a881b6934c200e422f6dcbe4296be6b310f3027","last_reissued_at":"2026-07-05T09:44:32.706756Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:44:32.706756Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.15513","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":"2026-07-05T09:44:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ovzEvEnI2IDzRJC36AjYuthiOscM8XYICeMnJtA6+ofJ5jVR1BwskP00ZL5rkS0Pbfd5Rgq8BAk2PSf1+qgHCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:03:24.814327Z"},"content_sha256":"1022f03709f22e53ad8d9a9fd55a4f1efd7b34013381f210c62ba66d39baa09b","schema_version":"1.0","event_id":"sha256:1022f03709f22e53ad8d9a9fd55a4f1efd7b34013381f210c62ba66d39baa09b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5RYRRAWLMTW65JLSLSXHVCA3NE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Navigating Perplexity: A linear relationship with the data set size in t-SNE embeddings","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","q-bio.QM","stat.ML"],"primary_cat":"cs.LG","authors_text":"Elmar Eisemann, Klaus Hildebrandt, Martin Skrodzki, Nicolas F. Chaves-de-Plaza, Thomas H\\\"ollt","submitted_at":"2023-08-29T16:24:11Z","abstract_excerpt":"Widely used pipelines for analyzing high-dimensional data utilize two-dimensional visualizations. These are created, for instance, via t-distributed stochastic neighbor embedding (t-SNE). A crucial element of the t-SNE embedding procedure is the perplexity hyperparameter. That is because the embedding structure varies when perplexity is changed. A suitable perplexity choice depends on the data set and the intended usage for the embedding. Therefore, perplexity is often chosen based on heuristics, intuition, and prior experience. This paper uncovers a linear relationship between perplexity and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.15513","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/2308.15513/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":"2026-07-05T09:44:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i/NH9MuMS9JLycw4RKK/aZngSAoc2h4B1GH8lyfaA2hmqEOyVkcW1fbg8kORsDPMzwdTknc3/Z4OWakXqBtLDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:03:24.814711Z"},"content_sha256":"e0c5bae6fd1716080023d2ea0e64eee3cf8e063c88b71ae747c10030bf1f107b","schema_version":"1.0","event_id":"sha256:e0c5bae6fd1716080023d2ea0e64eee3cf8e063c88b71ae747c10030bf1f107b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5RYRRAWLMTW65JLSLSXHVCA3NE/bundle.json","state_url":"https://pith.science/pith/5RYRRAWLMTW65JLSLSXHVCA3NE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5RYRRAWLMTW65JLSLSXHVCA3NE/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":"2026-07-06T16:03:24Z","links":{"resolver":"https://pith.science/pith/5RYRRAWLMTW65JLSLSXHVCA3NE","bundle":"https://pith.science/pith/5RYRRAWLMTW65JLSLSXHVCA3NE/bundle.json","state":"https://pith.science/pith/5RYRRAWLMTW65JLSLSXHVCA3NE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5RYRRAWLMTW65JLSLSXHVCA3NE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5RYRRAWLMTW65JLSLSXHVCA3NE","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":"157bc13faecb828ec6d1a3449ad51f72dd8853324b80d80de59a87de015cac72","cross_cats_sorted":["cs.AI","q-bio.QM","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-29T16:24:11Z","title_canon_sha256":"978cfb10d07ffbc32e90f4e55ab1968ef8b111c2a3c065c34d5bc24a3c5f1986"},"schema_version":"1.0","source":{"id":"2308.15513","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.15513","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"arxiv_version","alias_value":"2308.15513v2","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.15513","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"pith_short_12","alias_value":"5RYRRAWLMTW6","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"pith_short_16","alias_value":"5RYRRAWLMTW65JLS","created_at":"2026-07-05T09:44:32Z"},{"alias_kind":"pith_short_8","alias_value":"5RYRRAWL","created_at":"2026-07-05T09:44:32Z"}],"graph_snapshots":[{"event_id":"sha256:e0c5bae6fd1716080023d2ea0e64eee3cf8e063c88b71ae747c10030bf1f107b","target":"graph","created_at":"2026-07-05T09:44:32Z","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/2308.15513/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Widely used pipelines for analyzing high-dimensional data utilize two-dimensional visualizations. These are created, for instance, via t-distributed stochastic neighbor embedding (t-SNE). A crucial element of the t-SNE embedding procedure is the perplexity hyperparameter. That is because the embedding structure varies when perplexity is changed. A suitable perplexity choice depends on the data set and the intended usage for the embedding. Therefore, perplexity is often chosen based on heuristics, intuition, and prior experience. This paper uncovers a linear relationship between perplexity and ","authors_text":"Elmar Eisemann, Klaus Hildebrandt, Martin Skrodzki, Nicolas F. Chaves-de-Plaza, Thomas H\\\"ollt","cross_cats":["cs.AI","q-bio.QM","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-29T16:24:11Z","title":"Navigating Perplexity: A linear relationship with the data set size in t-SNE embeddings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.15513","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":"sha256:1022f03709f22e53ad8d9a9fd55a4f1efd7b34013381f210c62ba66d39baa09b","target":"record","created_at":"2026-07-05T09:44:32Z","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":"157bc13faecb828ec6d1a3449ad51f72dd8853324b80d80de59a87de015cac72","cross_cats_sorted":["cs.AI","q-bio.QM","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-29T16:24:11Z","title_canon_sha256":"978cfb10d07ffbc32e90f4e55ab1968ef8b111c2a3c065c34d5bc24a3c5f1986"},"schema_version":"1.0","source":{"id":"2308.15513","kind":"arxiv","version":2}},"canonical_sha256":"ec711882cb64edeea5725cae7a881b6934c200e422f6dcbe4296be6b310f3027","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ec711882cb64edeea5725cae7a881b6934c200e422f6dcbe4296be6b310f3027","first_computed_at":"2026-07-05T09:44:32.706756Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:44:32.706756Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ED875SfXLh8zMwqBZXgaWjy9h+qr4LJ6qfw0LWbZDiVNf/3IBDru1XfzwooHwVExYPF2lso0XFIiKXcSOnptCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:44:32.707267Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.15513","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1022f03709f22e53ad8d9a9fd55a4f1efd7b34013381f210c62ba66d39baa09b","sha256:e0c5bae6fd1716080023d2ea0e64eee3cf8e063c88b71ae747c10030bf1f107b"],"state_sha256":"f8a63228018658a9831d575dd81bcd310b5b8b9b9792ed5efbff5b1961a9fa8a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BJOD5EUFB5L0srA0A0HwaeoyotY+7KjDlaJu+GmgM+MXlegfoxs46/Igol5s8dP3Hfu5vP+jv72/0Ci/ixntDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T16:03:24.816703Z","bundle_sha256":"d5993a93bc093ec145d44cc76237bfa2f92394ab79af754e662386a90840ab79"}}