{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:KRL2EGAUUL7ZKODNRPWDOMKIHH","short_pith_number":"pith:KRL2EGAU","canonical_record":{"source":{"id":"2310.08577","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-12T17:59:30Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"56bf4d5b8ef5d45d74a1f8f77e191f9b2fc90e5a516a4945747d1012e890be45","abstract_canon_sha256":"c28b808ed38dd6d6089dc2664dd488b5b06753f7c63fb9b2e46ff115a7a01134"},"schema_version":"1.0"},"canonical_sha256":"5457a21814a2ff95386d8bec37314839cf2144cb23f207745e863ea1d8cb1257","source":{"kind":"arxiv","id":"2310.08577","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.08577","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"arxiv_version","alias_value":"2310.08577v3","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.08577","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"pith_short_12","alias_value":"KRL2EGAUUL7Z","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"pith_short_16","alias_value":"KRL2EGAUUL7ZKODN","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"pith_short_8","alias_value":"KRL2EGAU","created_at":"2026-07-05T07:20:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:KRL2EGAUUL7ZKODNRPWDOMKIHH","target":"record","payload":{"canonical_record":{"source":{"id":"2310.08577","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-12T17:59:30Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"56bf4d5b8ef5d45d74a1f8f77e191f9b2fc90e5a516a4945747d1012e890be45","abstract_canon_sha256":"c28b808ed38dd6d6089dc2664dd488b5b06753f7c63fb9b2e46ff115a7a01134"},"schema_version":"1.0"},"canonical_sha256":"5457a21814a2ff95386d8bec37314839cf2144cb23f207745e863ea1d8cb1257","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:20:54.311568Z","signature_b64":"nmp3lrCqq5bG5PDYioZ2zz/tfyshx9NcLheV4V4ntbyoZjmRnz27ffOJQS89zEOiseoDrHQa0wTPDQnm7M2IBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5457a21814a2ff95386d8bec37314839cf2144cb23f207745e863ea1d8cb1257","last_reissued_at":"2026-07-05T07:20:54.311090Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:20:54.311090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.08577","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:20:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"426/zHmw5c+inYmG9kVk6YZ0R/R0OkyQa5rA6MoM8s4OR8tenwIqUtetK0auandCGZdUkjclLgTOzh+Yth+UBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:45:37.721137Z"},"content_sha256":"43b437ea1a9e7e0072d7289a95ad87a638bdabb3eece67081c82ffe07d6453df","schema_version":"1.0","event_id":"sha256:43b437ea1a9e7e0072d7289a95ad87a638bdabb3eece67081c82ffe07d6453df"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:KRL2EGAUUL7ZKODNRPWDOMKIHH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Visual Data-Type Understanding does not emerge from Scaling Vision-Language Models","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Matthias Bethge, Max F. Burg, Samuel Albanie, Vishaal Udandarao","submitted_at":"2023-10-12T17:59:30Z","abstract_excerpt":"Recent advances in the development of vision-language models (VLMs) are yielding remarkable success in recognizing visual semantic content, including impressive instances of compositional image understanding. Here, we introduce the novel task of Visual Data-Type Identification, a basic perceptual skill with implications for data curation (e.g., noisy data-removal from large datasets, domain-specific retrieval) and autonomous vision (e.g., distinguishing changing weather conditions from camera lens staining). We develop two datasets consisting of animal images altered across a diverse set of 27"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.08577","kind":"arxiv","version":3},"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/2310.08577/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":"2026-07-05T07:20:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"laQbgArvTghAQC0ruyGZMIBQKRWw37VEgrO6cnIG5XH3mPFmDqfBFG6auW+Tqi718r3/CGhjHu+xvIha57d0Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:45:37.721658Z"},"content_sha256":"dd12338039e305fddb3ded604a552e893f0b06b70235b84ad9792bd8bc1adc31","schema_version":"1.0","event_id":"sha256:dd12338039e305fddb3ded604a552e893f0b06b70235b84ad9792bd8bc1adc31"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KRL2EGAUUL7ZKODNRPWDOMKIHH/bundle.json","state_url":"https://pith.science/pith/KRL2EGAUUL7ZKODNRPWDOMKIHH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KRL2EGAUUL7ZKODNRPWDOMKIHH/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":"2026-08-04T13:45:37Z","links":{"resolver":"https://pith.science/pith/KRL2EGAUUL7ZKODNRPWDOMKIHH","bundle":"https://pith.science/pith/KRL2EGAUUL7ZKODNRPWDOMKIHH/bundle.json","state":"https://pith.science/pith/KRL2EGAUUL7ZKODNRPWDOMKIHH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KRL2EGAUUL7ZKODNRPWDOMKIHH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KRL2EGAUUL7ZKODNRPWDOMKIHH","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":"c28b808ed38dd6d6089dc2664dd488b5b06753f7c63fb9b2e46ff115a7a01134","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-12T17:59:30Z","title_canon_sha256":"56bf4d5b8ef5d45d74a1f8f77e191f9b2fc90e5a516a4945747d1012e890be45"},"schema_version":"1.0","source":{"id":"2310.08577","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.08577","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"arxiv_version","alias_value":"2310.08577v3","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.08577","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"pith_short_12","alias_value":"KRL2EGAUUL7Z","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"pith_short_16","alias_value":"KRL2EGAUUL7ZKODN","created_at":"2026-07-05T07:20:54Z"},{"alias_kind":"pith_short_8","alias_value":"KRL2EGAU","created_at":"2026-07-05T07:20:54Z"}],"graph_snapshots":[{"event_id":"sha256:dd12338039e305fddb3ded604a552e893f0b06b70235b84ad9792bd8bc1adc31","target":"graph","created_at":"2026-07-05T07:20:54Z","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/2310.08577/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in the development of vision-language models (VLMs) are yielding remarkable success in recognizing visual semantic content, including impressive instances of compositional image understanding. Here, we introduce the novel task of Visual Data-Type Identification, a basic perceptual skill with implications for data curation (e.g., noisy data-removal from large datasets, domain-specific retrieval) and autonomous vision (e.g., distinguishing changing weather conditions from camera lens staining). We develop two datasets consisting of animal images altered across a diverse set of 27","authors_text":"Matthias Bethge, Max F. Burg, Samuel Albanie, Vishaal Udandarao","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-12T17:59:30Z","title":"Visual Data-Type Understanding does not emerge from Scaling Vision-Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.08577","kind":"arxiv","version":3},"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":"sha256:43b437ea1a9e7e0072d7289a95ad87a638bdabb3eece67081c82ffe07d6453df","target":"record","created_at":"2026-07-05T07:20:54Z","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":"c28b808ed38dd6d6089dc2664dd488b5b06753f7c63fb9b2e46ff115a7a01134","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-12T17:59:30Z","title_canon_sha256":"56bf4d5b8ef5d45d74a1f8f77e191f9b2fc90e5a516a4945747d1012e890be45"},"schema_version":"1.0","source":{"id":"2310.08577","kind":"arxiv","version":3}},"canonical_sha256":"5457a21814a2ff95386d8bec37314839cf2144cb23f207745e863ea1d8cb1257","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5457a21814a2ff95386d8bec37314839cf2144cb23f207745e863ea1d8cb1257","first_computed_at":"2026-07-05T07:20:54.311090Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:20:54.311090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nmp3lrCqq5bG5PDYioZ2zz/tfyshx9NcLheV4V4ntbyoZjmRnz27ffOJQS89zEOiseoDrHQa0wTPDQnm7M2IBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:20:54.311568Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.08577","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:43b437ea1a9e7e0072d7289a95ad87a638bdabb3eece67081c82ffe07d6453df","sha256:dd12338039e305fddb3ded604a552e893f0b06b70235b84ad9792bd8bc1adc31"],"state_sha256":"586a9444f512772766d9f6dc2bb1c52d241f07738b40a9f0801d4512461c5deb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k7hFC16rg8edkpdFIWD4TwvgE2ksar2Z0dSETPQN4cTBGOrWygCZ5Rtnf/Ui80EIvLZAWj83W8D6l+8x7jLhBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T13:45:37.725951Z","bundle_sha256":"a20d7d4a9760fe72f27e4e5792ecffcbe91c75e27c78c1f1a6a9f2001335200e"}}