{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:N7ZFEYLTLTN52JI7TZ76V5Z6W6","short_pith_number":"pith:N7ZFEYLT","canonical_record":{"source":{"id":"2007.01359","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-07-02T19:55:08Z","cross_cats_sorted":[],"title_canon_sha256":"227cc7d1a96b08c855b58e396abd5244cc2160a863045e6010cd6b1c74025ac7","abstract_canon_sha256":"4f72df7e0c1ab52a1b0c5c76ed38124243c2dc1d1b70d6e32f9a4b19c8f4675d"},"schema_version":"1.0"},"canonical_sha256":"6ff25261735cdbdd251f9e7feaf73eb792e85afa56f3c49b79047ae750109e96","source":{"kind":"arxiv","id":"2007.01359","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.01359","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"arxiv_version","alias_value":"2007.01359v3","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.01359","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"pith_short_12","alias_value":"N7ZFEYLTLTN5","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"pith_short_16","alias_value":"N7ZFEYLTLTN52JI7","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"pith_short_8","alias_value":"N7ZFEYLT","created_at":"2026-07-05T07:59:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:N7ZFEYLTLTN52JI7TZ76V5Z6W6","target":"record","payload":{"canonical_record":{"source":{"id":"2007.01359","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-07-02T19:55:08Z","cross_cats_sorted":[],"title_canon_sha256":"227cc7d1a96b08c855b58e396abd5244cc2160a863045e6010cd6b1c74025ac7","abstract_canon_sha256":"4f72df7e0c1ab52a1b0c5c76ed38124243c2dc1d1b70d6e32f9a4b19c8f4675d"},"schema_version":"1.0"},"canonical_sha256":"6ff25261735cdbdd251f9e7feaf73eb792e85afa56f3c49b79047ae750109e96","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:59:45.019219Z","signature_b64":"l0dKreoCR1jQrQant/gNkB0ydK8xTkxoIi8Z2Scd4DVRyZETGbrvyaBYsTbIERyhwXmI9NUwvMtcFcDr4hzhBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6ff25261735cdbdd251f9e7feaf73eb792e85afa56f3c49b79047ae750109e96","last_reissued_at":"2026-07-05T07:59:45.018814Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:59:45.018814Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2007.01359","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:59:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8jx9z7yvu/ZkdG0V61+atdx3NNSM1rMadUtxOh7KrL2bOBUjZvlDI4+PEINwwxDShNUdJqXyx1S/+j4+tEscBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T16:20:46.232451Z"},"content_sha256":"23177092f89c8815d98f3eaa1a0e90bb4fe169dd8b00b94ba531faf7125b0140","schema_version":"1.0","event_id":"sha256:23177092f89c8815d98f3eaa1a0e90bb4fe169dd8b00b94ba531faf7125b0140"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:N7ZFEYLTLTN52JI7TZ76V5Z6W6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Bayesian Multilingual Document Model for Zero-shot Topic Identification and Discovery","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"J\\'an \\v{C}ernock\\'y, Luk\\'a\\v{s} Burget, Ond\\v{r}ej Glembek, Sangeet Sagar, Santosh Kesiraju, Suryakanth V Gangashetty","submitted_at":"2020-07-02T19:55:08Z","abstract_excerpt":"In this paper, we present a Bayesian multilingual document model for learning language-independent document embeddings. The model is an extension of BaySMM [Kesiraju et al 2020] to the multilingual scenario. It learns to represent the document embeddings in the form of Gaussian distributions, thereby encoding the uncertainty in its covariance. We propagate the learned uncertainties through linear classifiers that benefit zero-shot cross-lingual topic identification. Our experiments on 17 languages show that the proposed multilingual Bayesian document model performs competitively, when compared"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.01359","kind":"arxiv","version":3},"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/2007.01359/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":"2026-07-05T07:59:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vrHEkrIsywcNU9BQF6EtFuw62POugCwtEmKwt5jFv36wvFfGL77nmZQhDdBjOIs2CmJTRHDu4hyFJgF/+LCzBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T16:20:46.233263Z"},"content_sha256":"4720b8943aa3cfd1006daa764a0bc49f7d23bc867d977e1a8e537f0f13ee9de4","schema_version":"1.0","event_id":"sha256:4720b8943aa3cfd1006daa764a0bc49f7d23bc867d977e1a8e537f0f13ee9de4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N7ZFEYLTLTN52JI7TZ76V5Z6W6/bundle.json","state_url":"https://pith.science/pith/N7ZFEYLTLTN52JI7TZ76V5Z6W6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N7ZFEYLTLTN52JI7TZ76V5Z6W6/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":"2026-08-04T16:20:46Z","links":{"resolver":"https://pith.science/pith/N7ZFEYLTLTN52JI7TZ76V5Z6W6","bundle":"https://pith.science/pith/N7ZFEYLTLTN52JI7TZ76V5Z6W6/bundle.json","state":"https://pith.science/pith/N7ZFEYLTLTN52JI7TZ76V5Z6W6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N7ZFEYLTLTN52JI7TZ76V5Z6W6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:N7ZFEYLTLTN52JI7TZ76V5Z6W6","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":"4f72df7e0c1ab52a1b0c5c76ed38124243c2dc1d1b70d6e32f9a4b19c8f4675d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-07-02T19:55:08Z","title_canon_sha256":"227cc7d1a96b08c855b58e396abd5244cc2160a863045e6010cd6b1c74025ac7"},"schema_version":"1.0","source":{"id":"2007.01359","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.01359","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"arxiv_version","alias_value":"2007.01359v3","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.01359","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"pith_short_12","alias_value":"N7ZFEYLTLTN5","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"pith_short_16","alias_value":"N7ZFEYLTLTN52JI7","created_at":"2026-07-05T07:59:45Z"},{"alias_kind":"pith_short_8","alias_value":"N7ZFEYLT","created_at":"2026-07-05T07:59:45Z"}],"graph_snapshots":[{"event_id":"sha256:4720b8943aa3cfd1006daa764a0bc49f7d23bc867d977e1a8e537f0f13ee9de4","target":"graph","created_at":"2026-07-05T07:59:45Z","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/2007.01359/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we present a Bayesian multilingual document model for learning language-independent document embeddings. The model is an extension of BaySMM [Kesiraju et al 2020] to the multilingual scenario. It learns to represent the document embeddings in the form of Gaussian distributions, thereby encoding the uncertainty in its covariance. We propagate the learned uncertainties through linear classifiers that benefit zero-shot cross-lingual topic identification. Our experiments on 17 languages show that the proposed multilingual Bayesian document model performs competitively, when compared","authors_text":"J\\'an \\v{C}ernock\\'y, Luk\\'a\\v{s} Burget, Ond\\v{r}ej Glembek, Sangeet Sagar, Santosh Kesiraju, Suryakanth V Gangashetty","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-07-02T19:55:08Z","title":"A Bayesian Multilingual Document Model for Zero-shot Topic Identification and Discovery"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.01359","kind":"arxiv","version":3},"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":"sha256:23177092f89c8815d98f3eaa1a0e90bb4fe169dd8b00b94ba531faf7125b0140","target":"record","created_at":"2026-07-05T07:59:45Z","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":"4f72df7e0c1ab52a1b0c5c76ed38124243c2dc1d1b70d6e32f9a4b19c8f4675d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-07-02T19:55:08Z","title_canon_sha256":"227cc7d1a96b08c855b58e396abd5244cc2160a863045e6010cd6b1c74025ac7"},"schema_version":"1.0","source":{"id":"2007.01359","kind":"arxiv","version":3}},"canonical_sha256":"6ff25261735cdbdd251f9e7feaf73eb792e85afa56f3c49b79047ae750109e96","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6ff25261735cdbdd251f9e7feaf73eb792e85afa56f3c49b79047ae750109e96","first_computed_at":"2026-07-05T07:59:45.018814Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:59:45.018814Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l0dKreoCR1jQrQant/gNkB0ydK8xTkxoIi8Z2Scd4DVRyZETGbrvyaBYsTbIERyhwXmI9NUwvMtcFcDr4hzhBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:59:45.019219Z","signed_message":"canonical_sha256_bytes"},"source_id":"2007.01359","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:23177092f89c8815d98f3eaa1a0e90bb4fe169dd8b00b94ba531faf7125b0140","sha256:4720b8943aa3cfd1006daa764a0bc49f7d23bc867d977e1a8e537f0f13ee9de4"],"state_sha256":"8e879ae1fa5dcaeb3813daa80259728e8e43d5fe88b330011cc6deb196237dbd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SG6gOY7TZwb0Hv9kRKi+cxlDNwZyp+VMjNu6AnF3446kXxF8FB7vwjkAuFCaKrOmS3ZARDS36oJej2XxTxd8Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T16:20:46.238263Z","bundle_sha256":"09ec95bd1706f3752854115a9a1beb5e05a6918aed2dbc101375a141a009079b"}}