{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PYYFIV4C6FMMGHVFYGJMYYJIJO","short_pith_number":"pith:PYYFIV4C","canonical_record":{"source":{"id":"2407.20553","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-30T05:15:19Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"334d78161f4f94510ff533f6dca5db68309302829d25f85e2998b21eac896d92","abstract_canon_sha256":"e2fe00d0fcc375fc06b76675843193dd7aa0bbdc166a575c617c358255269043"},"schema_version":"1.0"},"canonical_sha256":"7e30545782f158c31ea5c192cc61284bb856fc7339b1b7341e1df94b2a8dc6eb","source":{"kind":"arxiv","id":"2407.20553","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.20553","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"arxiv_version","alias_value":"2407.20553v1","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.20553","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"pith_short_12","alias_value":"PYYFIV4C6FMM","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"pith_short_16","alias_value":"PYYFIV4C6FMMGHVF","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"pith_short_8","alias_value":"PYYFIV4C","created_at":"2026-07-05T08:50:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PYYFIV4C6FMMGHVFYGJMYYJIJO","target":"record","payload":{"canonical_record":{"source":{"id":"2407.20553","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-30T05:15:19Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"334d78161f4f94510ff533f6dca5db68309302829d25f85e2998b21eac896d92","abstract_canon_sha256":"e2fe00d0fcc375fc06b76675843193dd7aa0bbdc166a575c617c358255269043"},"schema_version":"1.0"},"canonical_sha256":"7e30545782f158c31ea5c192cc61284bb856fc7339b1b7341e1df94b2a8dc6eb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:50:00.361475Z","signature_b64":"+BorqbD/BK3+Oo6CCrXpoI7xY5xZ7vvDW6DmC0tI16VbtQ41yvnSqeniDogZU1nAxXishKktwtl4ayeywgkpBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7e30545782f158c31ea5c192cc61284bb856fc7339b1b7341e1df94b2a8dc6eb","last_reissued_at":"2026-07-05T08:50:00.361061Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:50:00.361061Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.20553","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":"2026-07-05T08:50:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"90hmbJEU7qMu1JWGmz5eb720B1PUykq/1SQxUhu6p41VeHO49K73luFKlGGsl7wF/u9iAIFRZHeAZDcoz341Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T10:45:01.709723Z"},"content_sha256":"59b2683e931e308f2d6caceb14508fb33b9e6316b49ffeebdf414e5f092f39c8","schema_version":"1.0","event_id":"sha256:59b2683e931e308f2d6caceb14508fb33b9e6316b49ffeebdf414e5f092f39c8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PYYFIV4C6FMMGHVFYGJMYYJIJO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DiffusionCounterfactuals: Inferring High-dimensional Counterfactuals with Guidance of Causal Representations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"cs.LG","authors_text":"Hanchen Xie, Jiageng Zhu, Jiazhi Li, Wael Abd-Almageed","submitted_at":"2024-07-30T05:15:19Z","abstract_excerpt":"Accurate estimation of counterfactual outcomes in high-dimensional data is crucial for decision-making and understanding causal relationships and intervention outcomes in various domains, including healthcare, economics, and social sciences. However, existing methods often struggle to generate accurate and consistent counterfactuals, particularly when the causal relationships are complex. We propose a novel framework that incorporates causal mechanisms and diffusion models to generate high-quality counterfactual samples guided by causal representation. Our approach introduces a novel, theoreti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.20553","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/2407.20553/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":"2026-07-05T08:50:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J271bspKwEYc/DctAbjO2pB0x/AhYzGfAwIBQ6XLkt1HH/VCggzRVEtSzJpRhHWxNNKAsDR6vllIcxC+7Qy7CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T10:45:01.710111Z"},"content_sha256":"0046df1886817e34f426eee852054de392bc3240966d4e01dbcf9dce2ba0e333","schema_version":"1.0","event_id":"sha256:0046df1886817e34f426eee852054de392bc3240966d4e01dbcf9dce2ba0e333"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PYYFIV4C6FMMGHVFYGJMYYJIJO/bundle.json","state_url":"https://pith.science/pith/PYYFIV4C6FMMGHVFYGJMYYJIJO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PYYFIV4C6FMMGHVFYGJMYYJIJO/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":"2026-07-20T10:45:01Z","links":{"resolver":"https://pith.science/pith/PYYFIV4C6FMMGHVFYGJMYYJIJO","bundle":"https://pith.science/pith/PYYFIV4C6FMMGHVFYGJMYYJIJO/bundle.json","state":"https://pith.science/pith/PYYFIV4C6FMMGHVFYGJMYYJIJO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PYYFIV4C6FMMGHVFYGJMYYJIJO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PYYFIV4C6FMMGHVFYGJMYYJIJO","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":"e2fe00d0fcc375fc06b76675843193dd7aa0bbdc166a575c617c358255269043","cross_cats_sorted":["stat.ME"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-30T05:15:19Z","title_canon_sha256":"334d78161f4f94510ff533f6dca5db68309302829d25f85e2998b21eac896d92"},"schema_version":"1.0","source":{"id":"2407.20553","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.20553","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"arxiv_version","alias_value":"2407.20553v1","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.20553","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"pith_short_12","alias_value":"PYYFIV4C6FMM","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"pith_short_16","alias_value":"PYYFIV4C6FMMGHVF","created_at":"2026-07-05T08:50:00Z"},{"alias_kind":"pith_short_8","alias_value":"PYYFIV4C","created_at":"2026-07-05T08:50:00Z"}],"graph_snapshots":[{"event_id":"sha256:0046df1886817e34f426eee852054de392bc3240966d4e01dbcf9dce2ba0e333","target":"graph","created_at":"2026-07-05T08:50:00Z","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/2407.20553/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate estimation of counterfactual outcomes in high-dimensional data is crucial for decision-making and understanding causal relationships and intervention outcomes in various domains, including healthcare, economics, and social sciences. However, existing methods often struggle to generate accurate and consistent counterfactuals, particularly when the causal relationships are complex. We propose a novel framework that incorporates causal mechanisms and diffusion models to generate high-quality counterfactual samples guided by causal representation. Our approach introduces a novel, theoreti","authors_text":"Hanchen Xie, Jiageng Zhu, Jiazhi Li, Wael Abd-Almageed","cross_cats":["stat.ME"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-30T05:15:19Z","title":"DiffusionCounterfactuals: Inferring High-dimensional Counterfactuals with Guidance of Causal Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.20553","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":"sha256:59b2683e931e308f2d6caceb14508fb33b9e6316b49ffeebdf414e5f092f39c8","target":"record","created_at":"2026-07-05T08:50:00Z","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":"e2fe00d0fcc375fc06b76675843193dd7aa0bbdc166a575c617c358255269043","cross_cats_sorted":["stat.ME"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-30T05:15:19Z","title_canon_sha256":"334d78161f4f94510ff533f6dca5db68309302829d25f85e2998b21eac896d92"},"schema_version":"1.0","source":{"id":"2407.20553","kind":"arxiv","version":1}},"canonical_sha256":"7e30545782f158c31ea5c192cc61284bb856fc7339b1b7341e1df94b2a8dc6eb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7e30545782f158c31ea5c192cc61284bb856fc7339b1b7341e1df94b2a8dc6eb","first_computed_at":"2026-07-05T08:50:00.361061Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:50:00.361061Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+BorqbD/BK3+Oo6CCrXpoI7xY5xZ7vvDW6DmC0tI16VbtQ41yvnSqeniDogZU1nAxXishKktwtl4ayeywgkpBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:50:00.361475Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.20553","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:59b2683e931e308f2d6caceb14508fb33b9e6316b49ffeebdf414e5f092f39c8","sha256:0046df1886817e34f426eee852054de392bc3240966d4e01dbcf9dce2ba0e333"],"state_sha256":"64c2f03e2777ab191b66147aca56bef6076f59e68e6e3085bef12c2a09c69cbe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vY8GTBnJMn/EfS10fa1gX0zS5hVae6eLSh0qhYMFNulYKAXxLrw54sAHORSgVKMgINm74O9z+PwLUFm1KKIDAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-20T10:45:01.714099Z","bundle_sha256":"53cd206e580f09b089dda69422c217efabe5380977b8cbd436a2086d7c8422d8"}}