{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:63GYGKP2P252VUAFSZ75DKX4GT","short_pith_number":"pith:63GYGKP2","schema_version":"1.0","canonical_sha256":"f6cd8329fa7ebbaad005967fd1aafc34d4eeb227ce247fc3c96d227f31bd31c1","source":{"kind":"arxiv","id":"1611.01867","version":1},"attestation_state":"computed","paper":{"title":"Latent Attention For If-Then Program Synthesis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chang Liu, Dawn Song, Mingcheng Chen, Richard Shin, Xinyun Chen","submitted_at":"2016-11-07T00:56:19Z","abstract_excerpt":"Automatic translation from natural language descriptions into programs is a longstanding challenging problem. In this work, we consider a simple yet important sub-problem: translation from textual descriptions to If-Then programs. We devise a novel neural network architecture for this task which we train end-to-end. Specifically, we introduce Latent Attention, which computes multiplicative weights for the words in the description in a two-stage process with the goal of better leveraging the natural language structures that indicate the relevant parts for predicting program elements. Our archit"},"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":"1611.01867","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-11-07T00:56:19Z","cross_cats_sorted":[],"title_canon_sha256":"a8549bd1ad9171c605a7434f470f924b8dcbe496680fd72ab9bcc18987838b05","abstract_canon_sha256":"999941c68058f4da7c050b112332c26adfc342193d56b0d27883b1911566c07a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:00:04.280490Z","signature_b64":"U8V1WU10KH0wv6mzqZunrI3l6U0VGi280dQR9Y8/gF2k79TpZCq/yWfyyKp5V7EWm2KY91eGT5VhKQtXiJlvDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f6cd8329fa7ebbaad005967fd1aafc34d4eeb227ce247fc3c96d227f31bd31c1","last_reissued_at":"2026-05-18T01:00:04.279841Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:00:04.279841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Latent Attention For If-Then Program Synthesis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chang Liu, Dawn Song, Mingcheng Chen, Richard Shin, Xinyun Chen","submitted_at":"2016-11-07T00:56:19Z","abstract_excerpt":"Automatic translation from natural language descriptions into programs is a longstanding challenging problem. In this work, we consider a simple yet important sub-problem: translation from textual descriptions to If-Then programs. We devise a novel neural network architecture for this task which we train end-to-end. Specifically, we introduce Latent Attention, which computes multiplicative weights for the words in the description in a two-stage process with the goal of better leveraging the natural language structures that indicate the relevant parts for predicting program elements. Our archit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.01867","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":""},"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":"1611.01867","created_at":"2026-05-18T01:00:04.279969+00:00"},{"alias_kind":"arxiv_version","alias_value":"1611.01867v1","created_at":"2026-05-18T01:00:04.279969+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.01867","created_at":"2026-05-18T01:00:04.279969+00:00"},{"alias_kind":"pith_short_12","alias_value":"63GYGKP2P252","created_at":"2026-05-18T12:30:01.593930+00:00"},{"alias_kind":"pith_short_16","alias_value":"63GYGKP2P252VUAF","created_at":"2026-05-18T12:30:01.593930+00:00"},{"alias_kind":"pith_short_8","alias_value":"63GYGKP2","created_at":"2026-05-18T12:30:01.593930+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/63GYGKP2P252VUAFSZ75DKX4GT","json":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT.json","graph_json":"https://pith.science/api/pith-number/63GYGKP2P252VUAFSZ75DKX4GT/graph.json","events_json":"https://pith.science/api/pith-number/63GYGKP2P252VUAFSZ75DKX4GT/events.json","paper":"https://pith.science/paper/63GYGKP2"},"agent_actions":{"view_html":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT","download_json":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT.json","view_paper":"https://pith.science/paper/63GYGKP2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1611.01867&json=true","fetch_graph":"https://pith.science/api/pith-number/63GYGKP2P252VUAFSZ75DKX4GT/graph.json","fetch_events":"https://pith.science/api/pith-number/63GYGKP2P252VUAFSZ75DKX4GT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT/action/storage_attestation","attest_author":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT/action/author_attestation","sign_citation":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT/action/citation_signature","submit_replication":"https://pith.science/pith/63GYGKP2P252VUAFSZ75DKX4GT/action/replication_record"}},"created_at":"2026-05-18T01:00:04.279969+00:00","updated_at":"2026-05-18T01:00:04.279969+00:00"}