{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:TH4K3QNC5225UXSW335ECYWP5W","short_pith_number":"pith:TH4K3QNC","schema_version":"1.0","canonical_sha256":"99f8adc1a2eeb5da5e56defa4162cfedb6420a9acd36766e408b1a33fa025bba","source":{"kind":"arxiv","id":"2606.23107","version":1},"attestation_state":"computed","paper":{"title":"A Dual-Track Framework for Template-Constrained LaTeX Conversion","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chung Cheuk Hei, Liu Li","submitted_at":"2026-06-22T09:51:11Z","abstract_excerpt":"With the increasing demands for advanced document conversion, mapping structured Markdown drafts into template-compliant formats like LaTeX remains a challenge. Existing approaches largely depend on either deterministic rule-based converters or pure end-to-end Large Language Model (LLM) generation. The former fails to correctly handle asset insertions and template-specific constraints, while the latter tends to induce semantic drift, leading to hallucinations that are difficult to debug. To address these limitations, we introduce a robust Dual-Track Framework that systematically decouples temp"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.23107","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-22T09:51:11Z","cross_cats_sorted":[],"title_canon_sha256":"2700d70021ac63550d16701868face83ca3a7b5a35cfc9ab14685f2f68345c31","abstract_canon_sha256":"5c3665a4687191299fccf15a01f74aa88dfbc8defcf0ceb425ac2b7f9f7d5728"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T03:14:10.122984Z","signature_b64":"69aqsefF/6uhs2zpIVQEvNZkcnfZWIDBvhRFCOv25PyrptD8p99ENfn5IMKob8+LVgGGj3Jn6hdww/ZkGQCrCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99f8adc1a2eeb5da5e56defa4162cfedb6420a9acd36766e408b1a33fa025bba","last_reissued_at":"2026-06-23T03:14:10.122598Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T03:14:10.122598Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Dual-Track Framework for Template-Constrained LaTeX Conversion","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chung Cheuk Hei, Liu Li","submitted_at":"2026-06-22T09:51:11Z","abstract_excerpt":"With the increasing demands for advanced document conversion, mapping structured Markdown drafts into template-compliant formats like LaTeX remains a challenge. Existing approaches largely depend on either deterministic rule-based converters or pure end-to-end Large Language Model (LLM) generation. The former fails to correctly handle asset insertions and template-specific constraints, while the latter tends to induce semantic drift, leading to hallucinations that are difficult to debug. To address these limitations, we introduce a robust Dual-Track Framework that systematically decouples temp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23107","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/2606.23107/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.23107","created_at":"2026-06-23T03:14:10.122653+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.23107v1","created_at":"2026-06-23T03:14:10.122653+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23107","created_at":"2026-06-23T03:14:10.122653+00:00"},{"alias_kind":"pith_short_12","alias_value":"TH4K3QNC5225","created_at":"2026-06-23T03:14:10.122653+00:00"},{"alias_kind":"pith_short_16","alias_value":"TH4K3QNC5225UXSW","created_at":"2026-06-23T03:14:10.122653+00:00"},{"alias_kind":"pith_short_8","alias_value":"TH4K3QNC","created_at":"2026-06-23T03:14:10.122653+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W","json":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W.json","graph_json":"https://pith.science/api/pith-number/TH4K3QNC5225UXSW335ECYWP5W/graph.json","events_json":"https://pith.science/api/pith-number/TH4K3QNC5225UXSW335ECYWP5W/events.json","paper":"https://pith.science/paper/TH4K3QNC"},"agent_actions":{"view_html":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W","download_json":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W.json","view_paper":"https://pith.science/paper/TH4K3QNC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.23107&json=true","fetch_graph":"https://pith.science/api/pith-number/TH4K3QNC5225UXSW335ECYWP5W/graph.json","fetch_events":"https://pith.science/api/pith-number/TH4K3QNC5225UXSW335ECYWP5W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W/action/storage_attestation","attest_author":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W/action/author_attestation","sign_citation":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W/action/citation_signature","submit_replication":"https://pith.science/pith/TH4K3QNC5225UXSW335ECYWP5W/action/replication_record"}},"created_at":"2026-06-23T03:14:10.122653+00:00","updated_at":"2026-06-23T03:14:10.122653+00:00"}