{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7IE67YHETJE4A2OJYNNI7O3OTQ","short_pith_number":"pith:7IE67YHE","canonical_record":{"source":{"id":"2407.14058","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T06:35:49Z","cross_cats_sorted":[],"title_canon_sha256":"e54c33c256635874d6de5a8ebef1112f58c13593747a866101d23cc9691ccd26","abstract_canon_sha256":"a15042563f29a0d3d5c346b7e823de4d234ffe259ed56755297d6c818e0dc2be"},"schema_version":"1.0"},"canonical_sha256":"fa09efe0e49a49c069c9c35a8fbb6e9c12a8539918cca2fff469fea4300c47f9","source":{"kind":"arxiv","id":"2407.14058","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.14058","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"arxiv_version","alias_value":"2407.14058v6","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.14058","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"pith_short_12","alias_value":"7IE67YHETJE4","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"pith_short_16","alias_value":"7IE67YHETJE4A2OJ","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"pith_short_8","alias_value":"7IE67YHE","created_at":"2026-07-05T11:08:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7IE67YHETJE4A2OJYNNI7O3OTQ","target":"record","payload":{"canonical_record":{"source":{"id":"2407.14058","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T06:35:49Z","cross_cats_sorted":[],"title_canon_sha256":"e54c33c256635874d6de5a8ebef1112f58c13593747a866101d23cc9691ccd26","abstract_canon_sha256":"a15042563f29a0d3d5c346b7e823de4d234ffe259ed56755297d6c818e0dc2be"},"schema_version":"1.0"},"canonical_sha256":"fa09efe0e49a49c069c9c35a8fbb6e9c12a8539918cca2fff469fea4300c47f9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:58.881532Z","signature_b64":"octGEYmIlecRI1osr0J7MiWYyft0IPOXZDBQlyGewaY4zqeCtFxkYM+5Y/OCzs9IgoktrZaqpFXCcuvGeWw+Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa09efe0e49a49c069c9c35a8fbb6e9c12a8539918cca2fff469fea4300c47f9","last_reissued_at":"2026-07-05T11:08:58.880975Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:58.880975Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.14058","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:08:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V92Lj1ePpC4F+CRKqivwCNCeZfxDUsScCo0OfVbysJx29cryPCRGS9FZMIj30T7nodIJayA+s6E1d5Z0bmO1AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T14:08:59.132552Z"},"content_sha256":"c87074fdf5271e616cba0a097363442ef6446f0db38854906b4a538d76883ca5","schema_version":"1.0","event_id":"sha256:c87074fdf5271e616cba0a097363442ef6446f0db38854906b4a538d76883ca5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7IE67YHETJE4A2OJYNNI7O3OTQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards the Causal Complete Cause of Multi-Modal Representation Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Changwen Zheng, Fuchun Sun, Hui Xiong, Jiangmeng Li, Jingyao Wang, Siyu Zhao, Wenwen Qiang","submitted_at":"2024-07-19T06:35:49Z","abstract_excerpt":"Multi-Modal Learning (MML) aims to learn effective representations across modalities for accurate predictions. Existing methods typically focus on modality consistency and specificity to learn effective representations. However, from a causal perspective, they may lead to representations that contain insufficient and unnecessary information. To address this, we propose that effective MML representations should be causally sufficient and necessary. Considering practical issues like spurious correlations and modality conflicts, we relax the exogeneity and monotonicity assumptions prevalent in pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.14058","kind":"arxiv","version":6},"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/2407.14058/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":"2026-07-05T11:08:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I2N+wymXFkBVU6brafVcKdj8BDFRWqKY/s1247C3vKuS1m5V78dc7BtBvEqb6b11vJQYSPmtqzjT6QvpzTA7Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T14:08:59.133155Z"},"content_sha256":"6f6e59b042f6f5eda3c8e3b8195f50fe9e84383661d1f96021b3eb35964e8a5a","schema_version":"1.0","event_id":"sha256:6f6e59b042f6f5eda3c8e3b8195f50fe9e84383661d1f96021b3eb35964e8a5a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7IE67YHETJE4A2OJYNNI7O3OTQ/bundle.json","state_url":"https://pith.science/pith/7IE67YHETJE4A2OJYNNI7O3OTQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7IE67YHETJE4A2OJYNNI7O3OTQ/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":"2026-08-19T14:08:59Z","links":{"resolver":"https://pith.science/pith/7IE67YHETJE4A2OJYNNI7O3OTQ","bundle":"https://pith.science/pith/7IE67YHETJE4A2OJYNNI7O3OTQ/bundle.json","state":"https://pith.science/pith/7IE67YHETJE4A2OJYNNI7O3OTQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7IE67YHETJE4A2OJYNNI7O3OTQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7IE67YHETJE4A2OJYNNI7O3OTQ","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":"a15042563f29a0d3d5c346b7e823de4d234ffe259ed56755297d6c818e0dc2be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T06:35:49Z","title_canon_sha256":"e54c33c256635874d6de5a8ebef1112f58c13593747a866101d23cc9691ccd26"},"schema_version":"1.0","source":{"id":"2407.14058","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.14058","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"arxiv_version","alias_value":"2407.14058v6","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.14058","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"pith_short_12","alias_value":"7IE67YHETJE4","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"pith_short_16","alias_value":"7IE67YHETJE4A2OJ","created_at":"2026-07-05T11:08:58Z"},{"alias_kind":"pith_short_8","alias_value":"7IE67YHE","created_at":"2026-07-05T11:08:58Z"}],"graph_snapshots":[{"event_id":"sha256:6f6e59b042f6f5eda3c8e3b8195f50fe9e84383661d1f96021b3eb35964e8a5a","target":"graph","created_at":"2026-07-05T11:08:58Z","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/2407.14058/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-Modal Learning (MML) aims to learn effective representations across modalities for accurate predictions. Existing methods typically focus on modality consistency and specificity to learn effective representations. However, from a causal perspective, they may lead to representations that contain insufficient and unnecessary information. To address this, we propose that effective MML representations should be causally sufficient and necessary. Considering practical issues like spurious correlations and modality conflicts, we relax the exogeneity and monotonicity assumptions prevalent in pr","authors_text":"Changwen Zheng, Fuchun Sun, Hui Xiong, Jiangmeng Li, Jingyao Wang, Siyu Zhao, Wenwen Qiang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T06:35:49Z","title":"Towards the Causal Complete Cause of Multi-Modal Representation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.14058","kind":"arxiv","version":6},"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:c87074fdf5271e616cba0a097363442ef6446f0db38854906b4a538d76883ca5","target":"record","created_at":"2026-07-05T11:08:58Z","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":"a15042563f29a0d3d5c346b7e823de4d234ffe259ed56755297d6c818e0dc2be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T06:35:49Z","title_canon_sha256":"e54c33c256635874d6de5a8ebef1112f58c13593747a866101d23cc9691ccd26"},"schema_version":"1.0","source":{"id":"2407.14058","kind":"arxiv","version":6}},"canonical_sha256":"fa09efe0e49a49c069c9c35a8fbb6e9c12a8539918cca2fff469fea4300c47f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa09efe0e49a49c069c9c35a8fbb6e9c12a8539918cca2fff469fea4300c47f9","first_computed_at":"2026-07-05T11:08:58.880975Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:58.880975Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"octGEYmIlecRI1osr0J7MiWYyft0IPOXZDBQlyGewaY4zqeCtFxkYM+5Y/OCzs9IgoktrZaqpFXCcuvGeWw+Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:58.881532Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.14058","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c87074fdf5271e616cba0a097363442ef6446f0db38854906b4a538d76883ca5","sha256:6f6e59b042f6f5eda3c8e3b8195f50fe9e84383661d1f96021b3eb35964e8a5a"],"state_sha256":"2386340eb5813cc48b161e6657efdbf78c3da409cb0c2bb0bab4eee04fc732e1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WBsfieQiavw7aseZhW12JQS12/1abz7y596xj43un978PXPflaqCgKA1271NAO+Vl7ZB3Np50chpU/v2p1QGAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T14:08:59.136722Z","bundle_sha256":"a80a4cbf8f6c427a9cc9e3085339e7909e85c2c9856dcad42efd101326d8d947"}}