{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:PRN35J7W6KRJD4YWQJ2Y3ZJZG4","short_pith_number":"pith:PRN35J7W","schema_version":"1.0","canonical_sha256":"7c5bbea7f6f2a291f31682758de5393723ec9170ac8d795b0bbd6e7d837c8ec1","source":{"kind":"arxiv","id":"1908.06592","version":1},"attestation_state":"computed","paper":{"title":"Seq-SG2SL: Inferring Semantic Layout from Scene Graph Through Sequence to Sequence Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boren Li, Boyu Zhuang, Jian Gu, Mingyang Li","submitted_at":"2019-08-19T04:47:26Z","abstract_excerpt":"Generating semantic layout from scene graph is a crucial intermediate task connecting text to image. We present a conceptually simple, flexible and general framework using sequence to sequence (seq-to-seq) learning for this task. The framework, called Seq-SG2SL, derives sequence proxies for the two modality and a Transformer-based seq-to-seq model learns to transduce one into the other. A scene graph is decomposed into a sequence of semantic fragments (SF), one for each relationship. A semantic layout is represented as the consequence from a series of brick-action code segments (BACS), dictati"},"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":"1908.06592","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-19T04:47:26Z","cross_cats_sorted":[],"title_canon_sha256":"daaba1a7ef156b9c43a9efac16b0238cb71d5c4884608c257f8141c373513a5d","abstract_canon_sha256":"f96c12b9c033f69202368503599d46915afa05a04fe444693ae9fcd8db701c10"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:58:17.555469Z","signature_b64":"tU/6YU1vuxNFoxXNgVQKgZxA2QVYk8QcMdCpdsvAOHNzWFnFVT+Uz2k3RKUrCApw4jByeJeMs7QfIutZLyXoBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c5bbea7f6f2a291f31682758de5393723ec9170ac8d795b0bbd6e7d837c8ec1","last_reissued_at":"2026-07-04T23:58:17.555104Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:58:17.555104Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Seq-SG2SL: Inferring Semantic Layout from Scene Graph Through Sequence to Sequence Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boren Li, Boyu Zhuang, Jian Gu, Mingyang Li","submitted_at":"2019-08-19T04:47:26Z","abstract_excerpt":"Generating semantic layout from scene graph is a crucial intermediate task connecting text to image. We present a conceptually simple, flexible and general framework using sequence to sequence (seq-to-seq) learning for this task. The framework, called Seq-SG2SL, derives sequence proxies for the two modality and a Transformer-based seq-to-seq model learns to transduce one into the other. A scene graph is decomposed into a sequence of semantic fragments (SF), one for each relationship. A semantic layout is represented as the consequence from a series of brick-action code segments (BACS), dictati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06592","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/1908.06592/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":"1908.06592","created_at":"2026-07-04T23:58:17.555162+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.06592v1","created_at":"2026-07-04T23:58:17.555162+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06592","created_at":"2026-07-04T23:58:17.555162+00:00"},{"alias_kind":"pith_short_12","alias_value":"PRN35J7W6KRJ","created_at":"2026-07-04T23:58:17.555162+00:00"},{"alias_kind":"pith_short_16","alias_value":"PRN35J7W6KRJD4YW","created_at":"2026-07-04T23:58:17.555162+00:00"},{"alias_kind":"pith_short_8","alias_value":"PRN35J7W","created_at":"2026-07-04T23:58:17.555162+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/PRN35J7W6KRJD4YWQJ2Y3ZJZG4","json":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4.json","graph_json":"https://pith.science/api/pith-number/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/graph.json","events_json":"https://pith.science/api/pith-number/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/events.json","paper":"https://pith.science/paper/PRN35J7W"},"agent_actions":{"view_html":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4","download_json":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4.json","view_paper":"https://pith.science/paper/PRN35J7W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.06592&json=true","fetch_graph":"https://pith.science/api/pith-number/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/graph.json","fetch_events":"https://pith.science/api/pith-number/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/action/storage_attestation","attest_author":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/action/author_attestation","sign_citation":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/action/citation_signature","submit_replication":"https://pith.science/pith/PRN35J7W6KRJD4YWQJ2Y3ZJZG4/action/replication_record"}},"created_at":"2026-07-04T23:58:17.555162+00:00","updated_at":"2026-07-04T23:58:17.555162+00:00"}