{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:2MECNXKZU36RLK4EBU2X66SCLI","short_pith_number":"pith:2MECNXKZ","canonical_record":{"source":{"id":"2109.00729","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-02T05:57:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cde6b3d194c28cf69998f0dbc0fcfd5fa0f9440032174c4a246b47e1d690b6b8","abstract_canon_sha256":"c0b41115cf678aac7b1601f70a479cbf3a2f3e7c22b191ef156916fdc98fe429"},"schema_version":"1.0"},"canonical_sha256":"d30826dd59a6fd15ab840d357f7a425a3d679d82ad5b6a2d722b2abd08b1a751","source":{"kind":"arxiv","id":"2109.00729","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.00729","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"arxiv_version","alias_value":"2109.00729v1","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.00729","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"pith_short_12","alias_value":"2MECNXKZU36R","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"pith_short_16","alias_value":"2MECNXKZU36RLK4E","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"pith_short_8","alias_value":"2MECNXKZ","created_at":"2026-07-05T03:10:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:2MECNXKZU36RLK4EBU2X66SCLI","target":"record","payload":{"canonical_record":{"source":{"id":"2109.00729","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-02T05:57:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cde6b3d194c28cf69998f0dbc0fcfd5fa0f9440032174c4a246b47e1d690b6b8","abstract_canon_sha256":"c0b41115cf678aac7b1601f70a479cbf3a2f3e7c22b191ef156916fdc98fe429"},"schema_version":"1.0"},"canonical_sha256":"d30826dd59a6fd15ab840d357f7a425a3d679d82ad5b6a2d722b2abd08b1a751","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:10:58.065816Z","signature_b64":"adtq9qwlFNYb3+AN7ITIsIpeq1BJXqbfx/hkUU0UWCNB9BLtP6RDkVXogC8ifszJreOtmHyzqRytR8akpGwJDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d30826dd59a6fd15ab840d357f7a425a3d679d82ad5b6a2d722b2abd08b1a751","last_reissued_at":"2026-07-05T03:10:58.065470Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:10:58.065470Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.00729","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":"2026-07-05T03:10:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OHNrQ7vefJs+ICvnkJYr6pkmn9Ub4Z4BWn7trCrHE4mH1/ZhcvgpFKwMJx6S/B5lZOZaOey58pVvcjus9dfPCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T03:03:13.782555Z"},"content_sha256":"9b555778f760db0bd1fbc5e249b9d9dd06d7402c6741d66e90af96067422a87e","schema_version":"1.0","event_id":"sha256:9b555778f760db0bd1fbc5e249b9d9dd06d7402c6741d66e90af96067422a87e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:2MECNXKZU36RLK4EBU2X66SCLI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ConQX: Semantic Expansion of Spoken Queries for Intent Detection based on Conditioned Text Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cagri Toraman, Eyup Halit Yilmaz","submitted_at":"2021-09-02T05:57:07Z","abstract_excerpt":"Intent detection of spoken queries is a challenging task due to their noisy structure and short length. To provide additional information regarding the query and enhance the performance of intent detection, we propose a method for semantic expansion of spoken queries, called ConQX, which utilizes the text generation ability of an auto-regressive language model, GPT-2. To avoid off-topic text generation, we condition the input query to a structured context with prompt mining. We then apply zero-shot, one-shot, and few-shot learning. We lastly use the expanded queries to fine-tune BERT and RoBER"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.00729","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/2109.00729/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":"2026-07-05T03:10:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nl0pvQ4QRgNhitVF5YiZqUtocl01KWzr3M9G9t+XMphx3BJYHolPqdWl13YJTfkhgq9ouuXdQUlph1vtBrqyBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T03:03:13.783100Z"},"content_sha256":"1d0fac7c680b0e2ffd1d9e60fca2d6476146dffcb739f143e671979b5d692d89","schema_version":"1.0","event_id":"sha256:1d0fac7c680b0e2ffd1d9e60fca2d6476146dffcb739f143e671979b5d692d89"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2MECNXKZU36RLK4EBU2X66SCLI/bundle.json","state_url":"https://pith.science/pith/2MECNXKZU36RLK4EBU2X66SCLI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2MECNXKZU36RLK4EBU2X66SCLI/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":"2026-08-16T03:03:13Z","links":{"resolver":"https://pith.science/pith/2MECNXKZU36RLK4EBU2X66SCLI","bundle":"https://pith.science/pith/2MECNXKZU36RLK4EBU2X66SCLI/bundle.json","state":"https://pith.science/pith/2MECNXKZU36RLK4EBU2X66SCLI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2MECNXKZU36RLK4EBU2X66SCLI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:2MECNXKZU36RLK4EBU2X66SCLI","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":"c0b41115cf678aac7b1601f70a479cbf3a2f3e7c22b191ef156916fdc98fe429","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-02T05:57:07Z","title_canon_sha256":"cde6b3d194c28cf69998f0dbc0fcfd5fa0f9440032174c4a246b47e1d690b6b8"},"schema_version":"1.0","source":{"id":"2109.00729","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.00729","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"arxiv_version","alias_value":"2109.00729v1","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.00729","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"pith_short_12","alias_value":"2MECNXKZU36R","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"pith_short_16","alias_value":"2MECNXKZU36RLK4E","created_at":"2026-07-05T03:10:58Z"},{"alias_kind":"pith_short_8","alias_value":"2MECNXKZ","created_at":"2026-07-05T03:10:58Z"}],"graph_snapshots":[{"event_id":"sha256:1d0fac7c680b0e2ffd1d9e60fca2d6476146dffcb739f143e671979b5d692d89","target":"graph","created_at":"2026-07-05T03:10:58Z","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/2109.00729/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Intent detection of spoken queries is a challenging task due to their noisy structure and short length. To provide additional information regarding the query and enhance the performance of intent detection, we propose a method for semantic expansion of spoken queries, called ConQX, which utilizes the text generation ability of an auto-regressive language model, GPT-2. To avoid off-topic text generation, we condition the input query to a structured context with prompt mining. We then apply zero-shot, one-shot, and few-shot learning. We lastly use the expanded queries to fine-tune BERT and RoBER","authors_text":"Cagri Toraman, Eyup Halit Yilmaz","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-02T05:57:07Z","title":"ConQX: Semantic Expansion of Spoken Queries for Intent Detection based on Conditioned Text Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.00729","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":"sha256:9b555778f760db0bd1fbc5e249b9d9dd06d7402c6741d66e90af96067422a87e","target":"record","created_at":"2026-07-05T03:10:58Z","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":"c0b41115cf678aac7b1601f70a479cbf3a2f3e7c22b191ef156916fdc98fe429","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-02T05:57:07Z","title_canon_sha256":"cde6b3d194c28cf69998f0dbc0fcfd5fa0f9440032174c4a246b47e1d690b6b8"},"schema_version":"1.0","source":{"id":"2109.00729","kind":"arxiv","version":1}},"canonical_sha256":"d30826dd59a6fd15ab840d357f7a425a3d679d82ad5b6a2d722b2abd08b1a751","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d30826dd59a6fd15ab840d357f7a425a3d679d82ad5b6a2d722b2abd08b1a751","first_computed_at":"2026-07-05T03:10:58.065470Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:10:58.065470Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"adtq9qwlFNYb3+AN7ITIsIpeq1BJXqbfx/hkUU0UWCNB9BLtP6RDkVXogC8ifszJreOtmHyzqRytR8akpGwJDg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:10:58.065816Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.00729","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9b555778f760db0bd1fbc5e249b9d9dd06d7402c6741d66e90af96067422a87e","sha256:1d0fac7c680b0e2ffd1d9e60fca2d6476146dffcb739f143e671979b5d692d89"],"state_sha256":"f5027f76767413871d26fb5427677b0da38fb2fcb83722e9f67967724b93318c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5zErdnl3JD4TAAbmDqy9cqwLFsmPo3cHaxTY2cYe/w3J8n+S5NZ8TckySqUmexusWlEM5lKXVSKqIpQZqBNzCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T03:03:13.788218Z","bundle_sha256":"fb28d5c3489d0439ad5d59bce99c2ed0e7ee522a8ec636177162897349eb6293"}}