{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:6KN37TC5E3D2RN432NCPWZCPTL","short_pith_number":"pith:6KN37TC5","canonical_record":{"source":{"id":"2003.04035","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-09T10:52:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"17dc105498b797b88d9f7acdac2cee9e9c7fdf2230899c4186077bfcf5f46fbc","abstract_canon_sha256":"7ab304dae645258e8d12074c280c510eea809799eb9e0194b116ea5fdae46414"},"schema_version":"1.0"},"canonical_sha256":"f29bbfcc5d26c7a8b79bd344fb644f9aff2548c19bbe232399e805c021efe7ae","source":{"kind":"arxiv","id":"2003.04035","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.04035","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"arxiv_version","alias_value":"2003.04035v3","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.04035","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"pith_short_12","alias_value":"6KN37TC5E3D2","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"pith_short_16","alias_value":"6KN37TC5E3D2RN43","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"pith_short_8","alias_value":"6KN37TC5","created_at":"2026-07-05T03:32:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:6KN37TC5E3D2RN432NCPWZCPTL","target":"record","payload":{"canonical_record":{"source":{"id":"2003.04035","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-09T10:52:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"17dc105498b797b88d9f7acdac2cee9e9c7fdf2230899c4186077bfcf5f46fbc","abstract_canon_sha256":"7ab304dae645258e8d12074c280c510eea809799eb9e0194b116ea5fdae46414"},"schema_version":"1.0"},"canonical_sha256":"f29bbfcc5d26c7a8b79bd344fb644f9aff2548c19bbe232399e805c021efe7ae","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:32:48.537745Z","signature_b64":"MKqeLRSUXhRKfeUnesO54G7drjSBtS2k+uKBojlzi6VvQQwKppXwGgaqUijV/GOxaPyGaUkfBW+0q0aNbHNaDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f29bbfcc5d26c7a8b79bd344fb644f9aff2548c19bbe232399e805c021efe7ae","last_reissued_at":"2026-07-05T03:32:48.537226Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:32:48.537226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2003.04035","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":"2026-07-05T03:32:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Foi5CTmZJKX4y52zQseQxANeVYzIH/i6dQ1qT3oaIjnqMM2jNo0DdH2lSBaTJif9dJsj/qYFSq5NCxtowJ9JCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T18:58:08.834825Z"},"content_sha256":"f0aa6aea2078e318fa7ccb3612a517eadf28058e44354c10663d03242fa3df23","schema_version":"1.0","event_id":"sha256:f0aa6aea2078e318fa7ccb3612a517eadf28058e44354c10663d03242fa3df23"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:6KN37TC5E3D2RN432NCPWZCPTL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Transformation-based Adversarial Video Prediction on Large-Scale Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Aidan Clark, Albin Cassirer, Diego de las Casas, Karen Simonyan, Pauline Luc, Sander Dieleman, Yotam Doron","submitted_at":"2020-03-09T10:52:25Z","abstract_excerpt":"Recent breakthroughs in adversarial generative modeling have led to models capable of producing video samples of high quality, even on large and complex datasets of real-world video. In this work, we focus on the task of video prediction, where given a sequence of frames extracted from a video, the goal is to generate a plausible future sequence. We first improve the state of the art by performing a systematic empirical study of discriminator decompositions and proposing an architecture that yields faster convergence and higher performance than previous approaches. We then analyze recurrent un"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.04035","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/2003.04035/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":"2026-07-05T03:32:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZF+6Cw2L0yqi5Bm3yel/2ckI2RCsFaknPuk3H7pxM8Dz8qG6RPBD6Ut3UwP6ajzjTHTTQdv46gWJaS54g5JLCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T18:58:08.835680Z"},"content_sha256":"9f463b524bd44046b9f287c980ace0bc81a4931c2ddc66773a4bf598420d17d3","schema_version":"1.0","event_id":"sha256:9f463b524bd44046b9f287c980ace0bc81a4931c2ddc66773a4bf598420d17d3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6KN37TC5E3D2RN432NCPWZCPTL/bundle.json","state_url":"https://pith.science/pith/6KN37TC5E3D2RN432NCPWZCPTL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6KN37TC5E3D2RN432NCPWZCPTL/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":"2026-08-15T18:58:08Z","links":{"resolver":"https://pith.science/pith/6KN37TC5E3D2RN432NCPWZCPTL","bundle":"https://pith.science/pith/6KN37TC5E3D2RN432NCPWZCPTL/bundle.json","state":"https://pith.science/pith/6KN37TC5E3D2RN432NCPWZCPTL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6KN37TC5E3D2RN432NCPWZCPTL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6KN37TC5E3D2RN432NCPWZCPTL","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":"7ab304dae645258e8d12074c280c510eea809799eb9e0194b116ea5fdae46414","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-09T10:52:25Z","title_canon_sha256":"17dc105498b797b88d9f7acdac2cee9e9c7fdf2230899c4186077bfcf5f46fbc"},"schema_version":"1.0","source":{"id":"2003.04035","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.04035","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"arxiv_version","alias_value":"2003.04035v3","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.04035","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"pith_short_12","alias_value":"6KN37TC5E3D2","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"pith_short_16","alias_value":"6KN37TC5E3D2RN43","created_at":"2026-07-05T03:32:48Z"},{"alias_kind":"pith_short_8","alias_value":"6KN37TC5","created_at":"2026-07-05T03:32:48Z"}],"graph_snapshots":[{"event_id":"sha256:9f463b524bd44046b9f287c980ace0bc81a4931c2ddc66773a4bf598420d17d3","target":"graph","created_at":"2026-07-05T03:32:48Z","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/2003.04035/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent breakthroughs in adversarial generative modeling have led to models capable of producing video samples of high quality, even on large and complex datasets of real-world video. In this work, we focus on the task of video prediction, where given a sequence of frames extracted from a video, the goal is to generate a plausible future sequence. We first improve the state of the art by performing a systematic empirical study of discriminator decompositions and proposing an architecture that yields faster convergence and higher performance than previous approaches. We then analyze recurrent un","authors_text":"Aidan Clark, Albin Cassirer, Diego de las Casas, Karen Simonyan, Pauline Luc, Sander Dieleman, Yotam Doron","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-09T10:52:25Z","title":"Transformation-based Adversarial Video Prediction on Large-Scale Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.04035","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:f0aa6aea2078e318fa7ccb3612a517eadf28058e44354c10663d03242fa3df23","target":"record","created_at":"2026-07-05T03:32:48Z","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":"7ab304dae645258e8d12074c280c510eea809799eb9e0194b116ea5fdae46414","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-09T10:52:25Z","title_canon_sha256":"17dc105498b797b88d9f7acdac2cee9e9c7fdf2230899c4186077bfcf5f46fbc"},"schema_version":"1.0","source":{"id":"2003.04035","kind":"arxiv","version":3}},"canonical_sha256":"f29bbfcc5d26c7a8b79bd344fb644f9aff2548c19bbe232399e805c021efe7ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f29bbfcc5d26c7a8b79bd344fb644f9aff2548c19bbe232399e805c021efe7ae","first_computed_at":"2026-07-05T03:32:48.537226Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:32:48.537226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MKqeLRSUXhRKfeUnesO54G7drjSBtS2k+uKBojlzi6VvQQwKppXwGgaqUijV/GOxaPyGaUkfBW+0q0aNbHNaDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:32:48.537745Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.04035","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f0aa6aea2078e318fa7ccb3612a517eadf28058e44354c10663d03242fa3df23","sha256:9f463b524bd44046b9f287c980ace0bc81a4931c2ddc66773a4bf598420d17d3"],"state_sha256":"81bfc4df608dc9987a96895b6e1d85f3b514fba277e2f23b1ee2a3a4b693979e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"StJA4SOQsyTo6/5KB324s5gJeP2YPOV2nAjbhEVhASUh+5g8cwoo2NwXHlhV7ELw/9Lwf1oZ7WGQZLSX+aEYAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T18:58:08.841364Z","bundle_sha256":"b8191d2cfb7c2f2d708a5e54a1754d6c9b5cb27b90227c5c58f6ccd349597384"}}