{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF","short_pith_number":"pith:XJ2LOO4E","canonical_record":{"source":{"id":"2408.17363","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-30T15:53:48Z","cross_cats_sorted":[],"title_canon_sha256":"c4b30ff6594a62548f7761f685717a0b8d788a2929cb90dc651c70b77cdaa91b","abstract_canon_sha256":"d144e7825f0f06deb97f89c2df9c28465bee878235bd7ac089e46955d4511f6b"},"schema_version":"1.0"},"canonical_sha256":"ba74b73b8436cc397b1c8722f76f2751571d10b5fe34eb1043e67e34ab191e49","source":{"kind":"arxiv","id":"2408.17363","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.17363","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"arxiv_version","alias_value":"2408.17363v1","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.17363","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"pith_short_12","alias_value":"XJ2LOO4EG3GD","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"pith_short_16","alias_value":"XJ2LOO4EG3GDS6Y4","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"pith_short_8","alias_value":"XJ2LOO4E","created_at":"2026-07-05T09:01:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF","target":"record","payload":{"canonical_record":{"source":{"id":"2408.17363","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-30T15:53:48Z","cross_cats_sorted":[],"title_canon_sha256":"c4b30ff6594a62548f7761f685717a0b8d788a2929cb90dc651c70b77cdaa91b","abstract_canon_sha256":"d144e7825f0f06deb97f89c2df9c28465bee878235bd7ac089e46955d4511f6b"},"schema_version":"1.0"},"canonical_sha256":"ba74b73b8436cc397b1c8722f76f2751571d10b5fe34eb1043e67e34ab191e49","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:01:14.296262Z","signature_b64":"00VC3kT/NBBYH7Bf6dgwquhzYMN/hD5toTsDSYMTnynsPRMNS0tM3j9pL5qzVYqSPSOiZMTIKH3NE8XlK8waAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba74b73b8436cc397b1c8722f76f2751571d10b5fe34eb1043e67e34ab191e49","last_reissued_at":"2026-07-05T09:01:14.295767Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:01:14.295767Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.17363","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":"2026-07-05T09:01:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tGDMgK2QxOD0VKsW9IDS8YVn7Vn7YK/X++OF+eG64o6qSQ3bdQOsSL6GpeAUi3TPoDYvt1bpSyCcw/0w2Y42Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T12:58:53.060492Z"},"content_sha256":"3444132ca415d88ee3773950e9d8068b889a113da2326689201eba211edec559","schema_version":"1.0","event_id":"sha256:3444132ca415d88ee3773950e9d8068b889a113da2326689201eba211edec559"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Look, Learn and Leverage (L$^3$): Mitigating Visual-Domain Shift and Discovering Intrinsic Relations via Symbolic Alignment","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hanchen Xie, Jiageng Zhu, Jiazhi Li, Mahyar Khayatkhoei, Wael AbdAlmageed","submitted_at":"2024-08-30T15:53:48Z","abstract_excerpt":"Modern deep learning models have demonstrated outstanding performance on discovering the underlying mechanisms when both visual appearance and intrinsic relations (e.g., causal structure) data are sufficient, such as Disentangled Representation Learning (DRL), Causal Representation Learning (CRL) and Visual Question Answering (VQA) methods. However, generalization ability of these models is challenged when the visual domain shifts and the relations data is absent during finetuning. To address this challenge, we propose a novel learning framework, Look, Learn and Leverage (L$^3$), which decompo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.17363","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/2408.17363/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":"2026-07-05T09:01:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JRw65vx/qPcvcgZa5Tuagp8UbSCSz9DyEx8EDBaCt6bBvxmVivwqHlTfoVlEYznGH7/MMI7bpNtHaRn0nNfbDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T12:58:53.061560Z"},"content_sha256":"ba616c18c49d7ff2c9b68cf86392c401acebfaeac3377052a6a945c03547dd65","schema_version":"1.0","event_id":"sha256:ba616c18c49d7ff2c9b68cf86392c401acebfaeac3377052a6a945c03547dd65"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF/bundle.json","state_url":"https://pith.science/pith/XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF/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":"2026-08-05T12:58:53Z","links":{"resolver":"https://pith.science/pith/XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF","bundle":"https://pith.science/pith/XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF/bundle.json","state":"https://pith.science/pith/XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XJ2LOO4EG3GDS6Y4Q4RPO3ZHKF","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":"d144e7825f0f06deb97f89c2df9c28465bee878235bd7ac089e46955d4511f6b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-30T15:53:48Z","title_canon_sha256":"c4b30ff6594a62548f7761f685717a0b8d788a2929cb90dc651c70b77cdaa91b"},"schema_version":"1.0","source":{"id":"2408.17363","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.17363","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"arxiv_version","alias_value":"2408.17363v1","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.17363","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"pith_short_12","alias_value":"XJ2LOO4EG3GD","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"pith_short_16","alias_value":"XJ2LOO4EG3GDS6Y4","created_at":"2026-07-05T09:01:14Z"},{"alias_kind":"pith_short_8","alias_value":"XJ2LOO4E","created_at":"2026-07-05T09:01:14Z"}],"graph_snapshots":[{"event_id":"sha256:ba616c18c49d7ff2c9b68cf86392c401acebfaeac3377052a6a945c03547dd65","target":"graph","created_at":"2026-07-05T09:01:14Z","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/2408.17363/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Modern deep learning models have demonstrated outstanding performance on discovering the underlying mechanisms when both visual appearance and intrinsic relations (e.g., causal structure) data are sufficient, such as Disentangled Representation Learning (DRL), Causal Representation Learning (CRL) and Visual Question Answering (VQA) methods. However, generalization ability of these models is challenged when the visual domain shifts and the relations data is absent during finetuning. To address this challenge, we propose a novel learning framework, Look, Learn and Leverage (L$^3$), which decompo","authors_text":"Hanchen Xie, Jiageng Zhu, Jiazhi Li, Mahyar Khayatkhoei, Wael AbdAlmageed","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-30T15:53:48Z","title":"Look, Learn and Leverage (L$^3$): Mitigating Visual-Domain Shift and Discovering Intrinsic Relations via Symbolic Alignment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.17363","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":"sha256:3444132ca415d88ee3773950e9d8068b889a113da2326689201eba211edec559","target":"record","created_at":"2026-07-05T09:01:14Z","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":"d144e7825f0f06deb97f89c2df9c28465bee878235bd7ac089e46955d4511f6b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-30T15:53:48Z","title_canon_sha256":"c4b30ff6594a62548f7761f685717a0b8d788a2929cb90dc651c70b77cdaa91b"},"schema_version":"1.0","source":{"id":"2408.17363","kind":"arxiv","version":1}},"canonical_sha256":"ba74b73b8436cc397b1c8722f76f2751571d10b5fe34eb1043e67e34ab191e49","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba74b73b8436cc397b1c8722f76f2751571d10b5fe34eb1043e67e34ab191e49","first_computed_at":"2026-07-05T09:01:14.295767Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:01:14.295767Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"00VC3kT/NBBYH7Bf6dgwquhzYMN/hD5toTsDSYMTnynsPRMNS0tM3j9pL5qzVYqSPSOiZMTIKH3NE8XlK8waAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:01:14.296262Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.17363","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3444132ca415d88ee3773950e9d8068b889a113da2326689201eba211edec559","sha256:ba616c18c49d7ff2c9b68cf86392c401acebfaeac3377052a6a945c03547dd65"],"state_sha256":"f39415d5f344ccf0f13d07102cbb2bfa0c5d07a230faf79e614f3efafe94ac50"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ULLXQlzpNrILV6wcqLJyEype3aJynYz8PTlCBCV2pcDcRgSyQ+YqPVUK9hkUSxWyaapUNxNNR4TYrut2+UReDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T12:58:53.075858Z","bundle_sha256":"6af7aa62fcaedc8b98da36abacf692b44d8c7220d6de086afd18cc2a085e6003"}}