{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:V7OIE2KN2ECLFUFKJSLAIXIWWE","short_pith_number":"pith:V7OIE2KN","canonical_record":{"source":{"id":"2307.13992","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-07-26T07:01:57Z","cross_cats_sorted":[],"title_canon_sha256":"4921b5db3691a462c042f0295b476ced9127a40b22a3ac8e52337f904d0b4024","abstract_canon_sha256":"749d882e9da1aadba1046b7e0a54ca55758fd01d081199747d9739202e38dfb4"},"schema_version":"1.0"},"canonical_sha256":"afdc82694dd104b2d0aa4c96045d16b10dae2f9509aee5457a49966e42ea352e","source":{"kind":"arxiv","id":"2307.13992","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.13992","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"arxiv_version","alias_value":"2307.13992v2","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.13992","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"pith_short_12","alias_value":"V7OIE2KN2ECL","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"pith_short_16","alias_value":"V7OIE2KN2ECLFUFK","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"pith_short_8","alias_value":"V7OIE2KN","created_at":"2026-07-05T06:35:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:V7OIE2KN2ECLFUFKJSLAIXIWWE","target":"record","payload":{"canonical_record":{"source":{"id":"2307.13992","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-07-26T07:01:57Z","cross_cats_sorted":[],"title_canon_sha256":"4921b5db3691a462c042f0295b476ced9127a40b22a3ac8e52337f904d0b4024","abstract_canon_sha256":"749d882e9da1aadba1046b7e0a54ca55758fd01d081199747d9739202e38dfb4"},"schema_version":"1.0"},"canonical_sha256":"afdc82694dd104b2d0aa4c96045d16b10dae2f9509aee5457a49966e42ea352e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:35:54.001073Z","signature_b64":"U9eK/HnuD5XWJbsDj9uzmBQWlepf0jCUPfRku29TvLmBP4vKbIImq4hH8RIu8PmcaaqBzgeNYqcBzouGkbWOCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"afdc82694dd104b2d0aa4c96045d16b10dae2f9509aee5457a49966e42ea352e","last_reissued_at":"2026-07-05T06:35:54.000699Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:35:54.000699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.13992","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":"2026-07-05T06:35:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b3y/UNFG2Zgnc1GuAR7XSQ84R0gunRS4TrLJNTpFVmCNKTJUQ9DtSvO442Al1u+aoWjJ6TX9EKlxdUpDEpzqAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-15T20:11:21.844751Z"},"content_sha256":"665a7e255a8b55143e066e26d4160bc44dfc669597507d4f0092bb87ce56393f","schema_version":"1.0","event_id":"sha256:665a7e255a8b55143e066e26d4160bc44dfc669597507d4f0092bb87ce56393f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:V7OIE2KN2ECLFUFKJSLAIXIWWE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Causal reasoning in typical computer vision tasks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chaoqiang Zhao, Kexuan Zhang, Qiyu Sun, Yang Tang","submitted_at":"2023-07-26T07:01:57Z","abstract_excerpt":"Deep learning has revolutionized the field of artificial intelligence. Based on the statistical correlations uncovered by deep learning-based methods, computer vision has contributed to tremendous growth in areas like autonomous driving and robotics. Despite being the basis of deep learning, such correlation is not stable and is susceptible to uncontrolled factors. In the absence of the guidance of prior knowledge, statistical correlations can easily turn into spurious correlations and cause confounders. As a result, researchers are now trying to enhance deep learning methods with causal theor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.13992","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/2307.13992/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":"2026-07-05T06:35:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7jWytKtWO/akydceuSfxe1Jo8jHJ3qkASqPfP0QR4Vb3glEeBdHfrHZKq9GNx16PIud1asEWo6lzt0m0l1ueDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-15T20:11:21.845132Z"},"content_sha256":"48fe3c9287cd224343b133a69fd6748cc7fcaa84124e10d63b19facb9b300a49","schema_version":"1.0","event_id":"sha256:48fe3c9287cd224343b133a69fd6748cc7fcaa84124e10d63b19facb9b300a49"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V7OIE2KN2ECLFUFKJSLAIXIWWE/bundle.json","state_url":"https://pith.science/pith/V7OIE2KN2ECLFUFKJSLAIXIWWE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V7OIE2KN2ECLFUFKJSLAIXIWWE/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":"2026-07-15T20:11:21Z","links":{"resolver":"https://pith.science/pith/V7OIE2KN2ECLFUFKJSLAIXIWWE","bundle":"https://pith.science/pith/V7OIE2KN2ECLFUFKJSLAIXIWWE/bundle.json","state":"https://pith.science/pith/V7OIE2KN2ECLFUFKJSLAIXIWWE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V7OIE2KN2ECLFUFKJSLAIXIWWE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:V7OIE2KN2ECLFUFKJSLAIXIWWE","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":"749d882e9da1aadba1046b7e0a54ca55758fd01d081199747d9739202e38dfb4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-07-26T07:01:57Z","title_canon_sha256":"4921b5db3691a462c042f0295b476ced9127a40b22a3ac8e52337f904d0b4024"},"schema_version":"1.0","source":{"id":"2307.13992","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.13992","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"arxiv_version","alias_value":"2307.13992v2","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.13992","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"pith_short_12","alias_value":"V7OIE2KN2ECL","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"pith_short_16","alias_value":"V7OIE2KN2ECLFUFK","created_at":"2026-07-05T06:35:54Z"},{"alias_kind":"pith_short_8","alias_value":"V7OIE2KN","created_at":"2026-07-05T06:35:54Z"}],"graph_snapshots":[{"event_id":"sha256:48fe3c9287cd224343b133a69fd6748cc7fcaa84124e10d63b19facb9b300a49","target":"graph","created_at":"2026-07-05T06:35:54Z","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/2307.13992/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning has revolutionized the field of artificial intelligence. Based on the statistical correlations uncovered by deep learning-based methods, computer vision has contributed to tremendous growth in areas like autonomous driving and robotics. Despite being the basis of deep learning, such correlation is not stable and is susceptible to uncontrolled factors. In the absence of the guidance of prior knowledge, statistical correlations can easily turn into spurious correlations and cause confounders. As a result, researchers are now trying to enhance deep learning methods with causal theor","authors_text":"Chaoqiang Zhao, Kexuan Zhang, Qiyu Sun, Yang Tang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-07-26T07:01:57Z","title":"Causal reasoning in typical computer vision tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.13992","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":"sha256:665a7e255a8b55143e066e26d4160bc44dfc669597507d4f0092bb87ce56393f","target":"record","created_at":"2026-07-05T06:35:54Z","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":"749d882e9da1aadba1046b7e0a54ca55758fd01d081199747d9739202e38dfb4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-07-26T07:01:57Z","title_canon_sha256":"4921b5db3691a462c042f0295b476ced9127a40b22a3ac8e52337f904d0b4024"},"schema_version":"1.0","source":{"id":"2307.13992","kind":"arxiv","version":2}},"canonical_sha256":"afdc82694dd104b2d0aa4c96045d16b10dae2f9509aee5457a49966e42ea352e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"afdc82694dd104b2d0aa4c96045d16b10dae2f9509aee5457a49966e42ea352e","first_computed_at":"2026-07-05T06:35:54.000699Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:35:54.000699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"U9eK/HnuD5XWJbsDj9uzmBQWlepf0jCUPfRku29TvLmBP4vKbIImq4hH8RIu8PmcaaqBzgeNYqcBzouGkbWOCg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:35:54.001073Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.13992","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:665a7e255a8b55143e066e26d4160bc44dfc669597507d4f0092bb87ce56393f","sha256:48fe3c9287cd224343b133a69fd6748cc7fcaa84124e10d63b19facb9b300a49"],"state_sha256":"c280273fe2be2f41b7f408fd588169e34929297278760c87c3f674d1283769fc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gbF30yq6rFxAoxaBOZCuycuwQcyTuY8wIbXdP/Owqx37KRB0XrvNH3qwZRgHl508ewNQnmdwP0Mf6RbZQ7itBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-15T20:11:21.847331Z","bundle_sha256":"eb142fceff440ec14fada8704e249b4e608316e8ccee706b9e4cb44574c32d51"}}