{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ST6AULE6F7KHIKSHPFROG2BXBU","short_pith_number":"pith:ST6AULE6","canonical_record":{"source":{"id":"2012.11689","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2020-12-21T21:25:11Z","cross_cats_sorted":[],"title_canon_sha256":"ca223c8484f6bedb5b1099bfd1c788ee6c897c7340c841496f8d88c48ef57ead","abstract_canon_sha256":"fbb5f885f986180fe49a13b2dd957b12809fe0d36361c2018af2277ae264e100"},"schema_version":"1.0"},"canonical_sha256":"94fc0a2c9e2fd4742a477962e368370d01019f67ef6c2dfd84187bc71c8b06a4","source":{"kind":"arxiv","id":"2012.11689","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.11689","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"arxiv_version","alias_value":"2012.11689v1","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.11689","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"pith_short_12","alias_value":"ST6AULE6F7KH","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"pith_short_16","alias_value":"ST6AULE6F7KHIKSH","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"pith_short_8","alias_value":"ST6AULE6","created_at":"2026-07-05T02:01:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ST6AULE6F7KHIKSHPFROG2BXBU","target":"record","payload":{"canonical_record":{"source":{"id":"2012.11689","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2020-12-21T21:25:11Z","cross_cats_sorted":[],"title_canon_sha256":"ca223c8484f6bedb5b1099bfd1c788ee6c897c7340c841496f8d88c48ef57ead","abstract_canon_sha256":"fbb5f885f986180fe49a13b2dd957b12809fe0d36361c2018af2277ae264e100"},"schema_version":"1.0"},"canonical_sha256":"94fc0a2c9e2fd4742a477962e368370d01019f67ef6c2dfd84187bc71c8b06a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:01:20.342433Z","signature_b64":"z4AsPUGgoEE+AJdCYbQeCAaQcXat3z47dMoDzSErfY4mUHF8o44RXAjmHcu8lKQ77sOvMJ8iu4Sl3E9Cr88qAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"94fc0a2c9e2fd4742a477962e368370d01019f67ef6c2dfd84187bc71c8b06a4","last_reissued_at":"2026-07-05T02:01:20.342029Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:01:20.342029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2012.11689","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":"2026-07-05T02:01:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2NTT2479XXPRTKXgNM/p5rTFyoROZG4lkxJsXXZcW343wqYYyrN+EnkJvGSNe6OFqGZ7gLkeIQ7+1+NvD7U8Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T14:01:42.895084Z"},"content_sha256":"5eb02c9c2e3004b41de945273f90bf3311060679dac873315e1b92bced414a9a","schema_version":"1.0","event_id":"sha256:5eb02c9c2e3004b41de945273f90bf3311060679dac873315e1b92bced414a9a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ST6AULE6F7KHIKSHPFROG2BXBU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Clement Chung, Jixuan Wang, Kai Wei, Martin Radfar, Weiwei Zhang","submitted_at":"2020-12-21T21:25:11Z","abstract_excerpt":"We propose a novel Transformer encoder-based architecture with syntactical knowledge encoded for intent detection and slot filling. Specifically, we encode syntactic knowledge into the Transformer encoder by jointly training it to predict syntactic parse ancestors and part-of-speech of each token via multi-task learning. Our model is based on self-attention and feed-forward layers and does not require external syntactic information to be available at inference time. Experiments show that on two benchmark datasets, our models with only two Transformer encoder layers achieve state-of-the-art res"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.11689","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/2012.11689/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":"2026-07-05T02:01:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WKK2bOwSL4r4oIZ4wWXkWxDlNUu2+/lx+BUmrFWwLl96mQCKXpXuPuDhQGy4joIeO6c9j3utm7qgOJVD5wRsDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T14:01:42.895485Z"},"content_sha256":"0363f96a04e34cb36e2c74dfe03ba9058e7bd15661241c0c7537d2449cbac906","schema_version":"1.0","event_id":"sha256:0363f96a04e34cb36e2c74dfe03ba9058e7bd15661241c0c7537d2449cbac906"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ST6AULE6F7KHIKSHPFROG2BXBU/bundle.json","state_url":"https://pith.science/pith/ST6AULE6F7KHIKSHPFROG2BXBU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ST6AULE6F7KHIKSHPFROG2BXBU/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":"2026-07-08T14:01:42Z","links":{"resolver":"https://pith.science/pith/ST6AULE6F7KHIKSHPFROG2BXBU","bundle":"https://pith.science/pith/ST6AULE6F7KHIKSHPFROG2BXBU/bundle.json","state":"https://pith.science/pith/ST6AULE6F7KHIKSHPFROG2BXBU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ST6AULE6F7KHIKSHPFROG2BXBU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ST6AULE6F7KHIKSHPFROG2BXBU","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":"fbb5f885f986180fe49a13b2dd957b12809fe0d36361c2018af2277ae264e100","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2020-12-21T21:25:11Z","title_canon_sha256":"ca223c8484f6bedb5b1099bfd1c788ee6c897c7340c841496f8d88c48ef57ead"},"schema_version":"1.0","source":{"id":"2012.11689","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.11689","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"arxiv_version","alias_value":"2012.11689v1","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.11689","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"pith_short_12","alias_value":"ST6AULE6F7KH","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"pith_short_16","alias_value":"ST6AULE6F7KHIKSH","created_at":"2026-07-05T02:01:20Z"},{"alias_kind":"pith_short_8","alias_value":"ST6AULE6","created_at":"2026-07-05T02:01:20Z"}],"graph_snapshots":[{"event_id":"sha256:0363f96a04e34cb36e2c74dfe03ba9058e7bd15661241c0c7537d2449cbac906","target":"graph","created_at":"2026-07-05T02:01:20Z","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/2012.11689/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a novel Transformer encoder-based architecture with syntactical knowledge encoded for intent detection and slot filling. Specifically, we encode syntactic knowledge into the Transformer encoder by jointly training it to predict syntactic parse ancestors and part-of-speech of each token via multi-task learning. Our model is based on self-attention and feed-forward layers and does not require external syntactic information to be available at inference time. Experiments show that on two benchmark datasets, our models with only two Transformer encoder layers achieve state-of-the-art res","authors_text":"Clement Chung, Jixuan Wang, Kai Wei, Martin Radfar, Weiwei Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2020-12-21T21:25:11Z","title":"Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.11689","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":"sha256:5eb02c9c2e3004b41de945273f90bf3311060679dac873315e1b92bced414a9a","target":"record","created_at":"2026-07-05T02:01:20Z","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":"fbb5f885f986180fe49a13b2dd957b12809fe0d36361c2018af2277ae264e100","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2020-12-21T21:25:11Z","title_canon_sha256":"ca223c8484f6bedb5b1099bfd1c788ee6c897c7340c841496f8d88c48ef57ead"},"schema_version":"1.0","source":{"id":"2012.11689","kind":"arxiv","version":1}},"canonical_sha256":"94fc0a2c9e2fd4742a477962e368370d01019f67ef6c2dfd84187bc71c8b06a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"94fc0a2c9e2fd4742a477962e368370d01019f67ef6c2dfd84187bc71c8b06a4","first_computed_at":"2026-07-05T02:01:20.342029Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:01:20.342029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"z4AsPUGgoEE+AJdCYbQeCAaQcXat3z47dMoDzSErfY4mUHF8o44RXAjmHcu8lKQ77sOvMJ8iu4Sl3E9Cr88qAA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:01:20.342433Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.11689","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5eb02c9c2e3004b41de945273f90bf3311060679dac873315e1b92bced414a9a","sha256:0363f96a04e34cb36e2c74dfe03ba9058e7bd15661241c0c7537d2449cbac906"],"state_sha256":"5b3118c9d18221e137aa82b58b0d8a645353b49a6b6744f821deb24f0edd2a21"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WnofH1+XkwIk5n/mN7UFl1r5P9OPz5jpjia7kglUWFZOR+r03ezJfdcH9vBQvUm4XQg69WO9YGUarPqBOxWJCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T14:01:42.897613Z","bundle_sha256":"16c185902391e2326d6a8e7b665f7516fd0d059ab4637c0a44bd80909a38500a"}}