{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:SBEKGIHJGSH6BEMAQQNGSROLG7","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":"e59ce514469373b0a958b2a1506b3bb85eadc46bdd1e21fb93b9311cbb33b93d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-05-25T14:09:48Z","title_canon_sha256":"b3e4b351a739a544ca938ab136510fb95d57743d36ab6c2b9a888f2283289a74"},"schema_version":"1.0","source":{"id":"1705.09189","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.09189","created_at":"2026-07-05T00:33:32Z"},{"alias_kind":"arxiv_version","alias_value":"1705.09189v1","created_at":"2026-07-05T00:33:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.09189","created_at":"2026-07-05T00:33:32Z"},{"alias_kind":"pith_short_12","alias_value":"SBEKGIHJGSH6","created_at":"2026-07-05T00:33:32Z"},{"alias_kind":"pith_short_16","alias_value":"SBEKGIHJGSH6BEMA","created_at":"2026-07-05T00:33:32Z"},{"alias_kind":"pith_short_8","alias_value":"SBEKGIHJ","created_at":"2026-07-05T00:33:32Z"}],"graph_snapshots":[{"event_id":"sha256:bc840e33305702cd32ff0c8c6b50d46c9a40e4304ba6e3baeffb84c958624e8b","target":"graph","created_at":"2026-07-05T00:33:32Z","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/1705.09189/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a neural network that represents sentences by composing their words according to induced binary parse trees. We use Tree-LSTM as our composition function, applied along a tree structure found by a fully differentiable natural language chart parser. Our model simultaneously optimises both the composition function and the parser, thus eliminating the need for externally-provided parse trees which are normally required for Tree-LSTM. It can therefore be seen as a tree-based RNN that is unsupervised with respect to the parse trees. As it is fully differentiable, our model is easily tr","authors_text":"Dani Yogatama, Jean Maillard, Stephen Clark","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-05-25T14:09:48Z","title":"Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.09189","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:e1c60875a7c0256c29be2adc8f12a15593b835e389445e7e923be22332a3b3a5","target":"record","created_at":"2026-07-05T00:33:32Z","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":"e59ce514469373b0a958b2a1506b3bb85eadc46bdd1e21fb93b9311cbb33b93d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-05-25T14:09:48Z","title_canon_sha256":"b3e4b351a739a544ca938ab136510fb95d57743d36ab6c2b9a888f2283289a74"},"schema_version":"1.0","source":{"id":"1705.09189","kind":"arxiv","version":1}},"canonical_sha256":"9048a320e9348fe09180841a6945cb37ec97c942a9bd2c9dcd6e3af7b4611b20","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9048a320e9348fe09180841a6945cb37ec97c942a9bd2c9dcd6e3af7b4611b20","first_computed_at":"2026-07-05T00:33:32.135853Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:33:32.135853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"z/0ArrpMyDEWwoD4h+m+QCi0aGHnSdGYg6Yb8ocG89MjUXXL03uvMWYHUCCy9AqqX9R4m3uGzaGkZlYQYVwOCg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:33:32.136211Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.09189","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e1c60875a7c0256c29be2adc8f12a15593b835e389445e7e923be22332a3b3a5","sha256:bc840e33305702cd32ff0c8c6b50d46c9a40e4304ba6e3baeffb84c958624e8b"],"state_sha256":"b2a0597c95849104de8e77dfc0fea70c59413727448e26747cf0e639685bd467"}