{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:MPL7TYOWPQAP2TPJX52PY7V7HS","short_pith_number":"pith:MPL7TYOW","canonical_record":{"source":{"id":"2110.14002","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-26T20:14:30Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"d7f846bcd068a6b22357fa40ecaab70dea51a20d967ccf01f04abb6941124dbe","abstract_canon_sha256":"f5f20a5178095ab7a101dbc6e30950b344733a0222cddab8a0ac0796dfcf0103"},"schema_version":"1.0"},"canonical_sha256":"63d7f9e1d67c00fd4de9bf74fc7ebf3c8342c5933094e2e09760c47e308bbfad","source":{"kind":"arxiv","id":"2110.14002","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.14002","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"arxiv_version","alias_value":"2110.14002v1","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.14002","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"pith_short_12","alias_value":"MPL7TYOWPQAP","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"pith_short_16","alias_value":"MPL7TYOWPQAP2TPJ","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"pith_short_8","alias_value":"MPL7TYOW","created_at":"2026-07-05T03:26:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:MPL7TYOWPQAP2TPJX52PY7V7HS","target":"record","payload":{"canonical_record":{"source":{"id":"2110.14002","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-26T20:14:30Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"d7f846bcd068a6b22357fa40ecaab70dea51a20d967ccf01f04abb6941124dbe","abstract_canon_sha256":"f5f20a5178095ab7a101dbc6e30950b344733a0222cddab8a0ac0796dfcf0103"},"schema_version":"1.0"},"canonical_sha256":"63d7f9e1d67c00fd4de9bf74fc7ebf3c8342c5933094e2e09760c47e308bbfad","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:26:22.726124Z","signature_b64":"fA3ohlOO98fKI6htghHmZVWSFz10ytzgjsVfD62kiGwAAvStxSVYUYuPO91+81KydzKcDVSaecX4odkzpgd6CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"63d7f9e1d67c00fd4de9bf74fc7ebf3c8342c5933094e2e09760c47e308bbfad","last_reissued_at":"2026-07-05T03:26:22.725664Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:26:22.725664Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.14002","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":"2026-07-05T03:26:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"34ChisBl7XuwjCwOQbmJ7b6cZatPlbjdkp/o/AmF97h6jesCaG78NhtHuVSTrLsZZo63r740qU9VLFPB0zUoBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T03:26:29.622618Z"},"content_sha256":"ddba0799deb97611cb1a5c5f873ffbc631f69cf2a352b17a126780022a46acf4","schema_version":"1.0","event_id":"sha256:ddba0799deb97611cb1a5c5f873ffbc631f69cf2a352b17a126780022a46acf4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:MPL7TYOWPQAP2TPJX52PY7V7HS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alek Dimitriev, Mingyuan Zhou","submitted_at":"2021-10-26T20:14:30Z","abstract_excerpt":"Accurately backpropagating the gradient through categorical variables is a challenging task that arises in various domains, such as training discrete latent variable models. To this end, we propose CARMS, an unbiased estimator for categorical random variables based on multiple mutually negatively correlated (jointly antithetic) samples. CARMS combines REINFORCE with copula based sampling to avoid duplicate samples and reduce its variance, while keeping the estimator unbiased using importance sampling. It generalizes both the ARMS antithetic estimator for binary variables, which is CARMS for tw"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.14002","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/2110.14002/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":"2026-07-05T03:26:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pv+8p4QqjB+jQNloyL/v4m1jL3xQyiBoFSHRqkswLMzlxjbjYi1jlqASm0KAypOqic1WMHVxQtxOv3ARcM8yBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T03:26:29.623145Z"},"content_sha256":"c5f7848a46619bc5f0c89d442bdb2c509a37805d69b2835d8f13f1f928239516","schema_version":"1.0","event_id":"sha256:c5f7848a46619bc5f0c89d442bdb2c509a37805d69b2835d8f13f1f928239516"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MPL7TYOWPQAP2TPJX52PY7V7HS/bundle.json","state_url":"https://pith.science/pith/MPL7TYOWPQAP2TPJX52PY7V7HS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MPL7TYOWPQAP2TPJX52PY7V7HS/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":"2026-08-11T03:26:29Z","links":{"resolver":"https://pith.science/pith/MPL7TYOWPQAP2TPJX52PY7V7HS","bundle":"https://pith.science/pith/MPL7TYOWPQAP2TPJX52PY7V7HS/bundle.json","state":"https://pith.science/pith/MPL7TYOWPQAP2TPJX52PY7V7HS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MPL7TYOWPQAP2TPJX52PY7V7HS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:MPL7TYOWPQAP2TPJX52PY7V7HS","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":"f5f20a5178095ab7a101dbc6e30950b344733a0222cddab8a0ac0796dfcf0103","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-26T20:14:30Z","title_canon_sha256":"d7f846bcd068a6b22357fa40ecaab70dea51a20d967ccf01f04abb6941124dbe"},"schema_version":"1.0","source":{"id":"2110.14002","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.14002","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"arxiv_version","alias_value":"2110.14002v1","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.14002","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"pith_short_12","alias_value":"MPL7TYOWPQAP","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"pith_short_16","alias_value":"MPL7TYOWPQAP2TPJ","created_at":"2026-07-05T03:26:22Z"},{"alias_kind":"pith_short_8","alias_value":"MPL7TYOW","created_at":"2026-07-05T03:26:22Z"}],"graph_snapshots":[{"event_id":"sha256:c5f7848a46619bc5f0c89d442bdb2c509a37805d69b2835d8f13f1f928239516","target":"graph","created_at":"2026-07-05T03:26:22Z","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/2110.14002/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurately backpropagating the gradient through categorical variables is a challenging task that arises in various domains, such as training discrete latent variable models. To this end, we propose CARMS, an unbiased estimator for categorical random variables based on multiple mutually negatively correlated (jointly antithetic) samples. CARMS combines REINFORCE with copula based sampling to avoid duplicate samples and reduce its variance, while keeping the estimator unbiased using importance sampling. It generalizes both the ARMS antithetic estimator for binary variables, which is CARMS for tw","authors_text":"Alek Dimitriev, Mingyuan Zhou","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-26T20:14:30Z","title":"CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.14002","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:ddba0799deb97611cb1a5c5f873ffbc631f69cf2a352b17a126780022a46acf4","target":"record","created_at":"2026-07-05T03:26:22Z","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":"f5f20a5178095ab7a101dbc6e30950b344733a0222cddab8a0ac0796dfcf0103","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-26T20:14:30Z","title_canon_sha256":"d7f846bcd068a6b22357fa40ecaab70dea51a20d967ccf01f04abb6941124dbe"},"schema_version":"1.0","source":{"id":"2110.14002","kind":"arxiv","version":1}},"canonical_sha256":"63d7f9e1d67c00fd4de9bf74fc7ebf3c8342c5933094e2e09760c47e308bbfad","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"63d7f9e1d67c00fd4de9bf74fc7ebf3c8342c5933094e2e09760c47e308bbfad","first_computed_at":"2026-07-05T03:26:22.725664Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:26:22.725664Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fA3ohlOO98fKI6htghHmZVWSFz10ytzgjsVfD62kiGwAAvStxSVYUYuPO91+81KydzKcDVSaecX4odkzpgd6CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:26:22.726124Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.14002","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ddba0799deb97611cb1a5c5f873ffbc631f69cf2a352b17a126780022a46acf4","sha256:c5f7848a46619bc5f0c89d442bdb2c509a37805d69b2835d8f13f1f928239516"],"state_sha256":"875411fa86f17942a1cac4b71699dfafe142efd41d7e0d9089d94e4a94aca933"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uyssSd0upJTdF39s/skn9kvaJKN21WGgLWMfnZj9lkX5IH9Yph3pzsYuUMrn2CFqxQglRC59TWkZ5PpRkCliDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T03:26:29.629041Z","bundle_sha256":"16339b3930a716f88b95f2355f9e7e12ef825a1c287399ecd4ef9b5fd003d118"}}