{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DNGJ47IUFOHB4RATIWMICS42LA","short_pith_number":"pith:DNGJ47IU","canonical_record":{"source":{"id":"2605.15618","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-15T04:59:30Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5f7fadab1d1a828f725fb33e1b59a8ecd33a153e7d4ac80743982b13eb5a5429","abstract_canon_sha256":"ce8fa7ae28e3996138c9f04c154072e37d00613cf8957a43e0b9cd54c15f6359"},"schema_version":"1.0"},"canonical_sha256":"1b4c9e7d142b8e1e44134598814b9a581635422ecd493b70b13f84aa34f0006e","source":{"kind":"arxiv","id":"2605.15618","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15618","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15618v1","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15618","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"pith_short_12","alias_value":"DNGJ47IUFOHB","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"pith_short_16","alias_value":"DNGJ47IUFOHB4RAT","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"pith_short_8","alias_value":"DNGJ47IU","created_at":"2026-05-20T00:01:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DNGJ47IUFOHB4RATIWMICS42LA","target":"record","payload":{"canonical_record":{"source":{"id":"2605.15618","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-15T04:59:30Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5f7fadab1d1a828f725fb33e1b59a8ecd33a153e7d4ac80743982b13eb5a5429","abstract_canon_sha256":"ce8fa7ae28e3996138c9f04c154072e37d00613cf8957a43e0b9cd54c15f6359"},"schema_version":"1.0"},"canonical_sha256":"1b4c9e7d142b8e1e44134598814b9a581635422ecd493b70b13f84aa34f0006e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:01:08.482881Z","signature_b64":"84I4i8AsEhGfhpbkbmXmbOybAExtR5irGuJfTPvvBoV8v4v+fIyYm3TdvmChrmawYNxQdH5zJ5CoPOEfnnp0Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1b4c9e7d142b8e1e44134598814b9a581635422ecd493b70b13f84aa34f0006e","last_reissued_at":"2026-05-20T00:01:08.482082Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:01:08.482082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.15618","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":"2026-05-20T00:01:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0Bd4yaHcIFCqx8JCcWJNUd1TeYl8IL+RpTCU8mPcS4s4E/PS/HWK3JOTNJqNiP3JD4qtSp0htRGSmMSCWVToBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T18:53:26.038674Z"},"content_sha256":"f507443ec352fed03471b3407d6cf90be5d7a1ff605f66584c4c466dd7c6e9cd","schema_version":"1.0","event_id":"sha256:f507443ec352fed03471b3407d6cf90be5d7a1ff605f66584c4c466dd7c6e9cd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DNGJ47IUFOHB4RATIWMICS42LA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Latent Video Prediction Learns Better World Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Ali J Alrasheed, Aryan Yazdan Parast, Basim Azam, James Bailey, Naveed Akhtar","submitted_at":"2026-05-15T04:59:30Z","abstract_excerpt":"Self-supervised video models are increasingly framed as world models, yet their evaluation remains largely confined to a single top-1 accuracy score on clean benchmarks. This leaves a major gap in comprehending their potential as world models. We present the first systematic study addressing this gap, analyzing four matched-capacity frontier video foundation models, V-JEPA 2.1, V-JEPA 2, VideoPrism, and VideoMAEv2, across five robustness axes relevant to their deployment as video world models: feature discriminability, corruption robustness, fine-grained discrimination, occlusion robustness, a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.15618","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/2605.15618/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T19:34:34.615485Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T17:41:56.039532Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"2f4ad5c4a9e414c6305a04d7761ce9c71711b2594c7a5ca2e83cee98d25c4c75"},"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":"2026-05-20T00:01:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HImXg3z7aZhe9pI4NwkLpQUEVSqe8dEOY+m8t3Yi58qZ0n2kvdsVQfqZ5KuV+MOIK1nWD+gcRx7od0xYU+ObAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T18:53:26.039135Z"},"content_sha256":"b93bd1419a8b4de3e9d325cda0c25e81b090ad135350d2346fbe04370c03652d","schema_version":"1.0","event_id":"sha256:b93bd1419a8b4de3e9d325cda0c25e81b090ad135350d2346fbe04370c03652d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DNGJ47IUFOHB4RATIWMICS42LA/bundle.json","state_url":"https://pith.science/pith/DNGJ47IUFOHB4RATIWMICS42LA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DNGJ47IUFOHB4RATIWMICS42LA/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":"2026-05-27T18:53:26Z","links":{"resolver":"https://pith.science/pith/DNGJ47IUFOHB4RATIWMICS42LA","bundle":"https://pith.science/pith/DNGJ47IUFOHB4RATIWMICS42LA/bundle.json","state":"https://pith.science/pith/DNGJ47IUFOHB4RATIWMICS42LA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DNGJ47IUFOHB4RATIWMICS42LA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DNGJ47IUFOHB4RATIWMICS42LA","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":"ce8fa7ae28e3996138c9f04c154072e37d00613cf8957a43e0b9cd54c15f6359","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-15T04:59:30Z","title_canon_sha256":"5f7fadab1d1a828f725fb33e1b59a8ecd33a153e7d4ac80743982b13eb5a5429"},"schema_version":"1.0","source":{"id":"2605.15618","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15618","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15618v1","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15618","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"pith_short_12","alias_value":"DNGJ47IUFOHB","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"pith_short_16","alias_value":"DNGJ47IUFOHB4RAT","created_at":"2026-05-20T00:01:08Z"},{"alias_kind":"pith_short_8","alias_value":"DNGJ47IU","created_at":"2026-05-20T00:01:08Z"}],"graph_snapshots":[{"event_id":"sha256:b93bd1419a8b4de3e9d325cda0c25e81b090ad135350d2346fbe04370c03652d","target":"graph","created_at":"2026-05-20T00:01:08Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T19:34:34.615485Z","status":"skipped","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T17:41:56.039532Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.15618/integrity.json","findings":[],"snapshot_sha256":"2f4ad5c4a9e414c6305a04d7761ce9c71711b2594c7a5ca2e83cee98d25c4c75","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Self-supervised video models are increasingly framed as world models, yet their evaluation remains largely confined to a single top-1 accuracy score on clean benchmarks. This leaves a major gap in comprehending their potential as world models. We present the first systematic study addressing this gap, analyzing four matched-capacity frontier video foundation models, V-JEPA 2.1, V-JEPA 2, VideoPrism, and VideoMAEv2, across five robustness axes relevant to their deployment as video world models: feature discriminability, corruption robustness, fine-grained discrimination, occlusion robustness, a","authors_text":"Ali J Alrasheed, Aryan Yazdan Parast, Basim Azam, James Bailey, Naveed Akhtar","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-15T04:59:30Z","title":"Latent Video Prediction Learns Better World Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.15618","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:f507443ec352fed03471b3407d6cf90be5d7a1ff605f66584c4c466dd7c6e9cd","target":"record","created_at":"2026-05-20T00:01:08Z","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":"ce8fa7ae28e3996138c9f04c154072e37d00613cf8957a43e0b9cd54c15f6359","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-15T04:59:30Z","title_canon_sha256":"5f7fadab1d1a828f725fb33e1b59a8ecd33a153e7d4ac80743982b13eb5a5429"},"schema_version":"1.0","source":{"id":"2605.15618","kind":"arxiv","version":1}},"canonical_sha256":"1b4c9e7d142b8e1e44134598814b9a581635422ecd493b70b13f84aa34f0006e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1b4c9e7d142b8e1e44134598814b9a581635422ecd493b70b13f84aa34f0006e","first_computed_at":"2026-05-20T00:01:08.482082Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:01:08.482082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"84I4i8AsEhGfhpbkbmXmbOybAExtR5irGuJfTPvvBoV8v4v+fIyYm3TdvmChrmawYNxQdH5zJ5CoPOEfnnp0Dg==","signature_status":"signed_v1","signed_at":"2026-05-20T00:01:08.482881Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.15618","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f507443ec352fed03471b3407d6cf90be5d7a1ff605f66584c4c466dd7c6e9cd","sha256:b93bd1419a8b4de3e9d325cda0c25e81b090ad135350d2346fbe04370c03652d"],"state_sha256":"c053b14c186d3219206d9a63cabe307df2f73eeb213355e8f4eb02b2815a6859"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vI7GUSLQgtfTYukNkq8MRG8NdhR1RLMpUqH7Hb0audoFc3leXPHsqXnEBQ+IyO/zqXFFt2BMyUROknoFFDJmAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T18:53:26.042195Z","bundle_sha256":"bea98aecc50cbe10f998e8ad30b903a9d71b6334091461dc640c9b188dd01d36"}}