{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:YONVRT3BIDOHGPBLXTGILD5DKV","short_pith_number":"pith:YONVRT3B","canonical_record":{"source":{"id":"1703.01925","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-06T15:36:37Z","cross_cats_sorted":[],"title_canon_sha256":"798e6c86090e18bc4ef2e2e0b669e69fe3db64035f9e05795efd4c4e584bf7ff","abstract_canon_sha256":"1fe20027cf6ad03ef616b2d44d7f1e8276d05322caf6d02f6ef338325bf07df1"},"schema_version":"1.0"},"canonical_sha256":"c39b58cf6140dc733c2bbccc858fa3555fbbee370093eb0f93651f9dbb0615e9","source":{"kind":"arxiv","id":"1703.01925","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.01925","created_at":"2026-05-18T00:49:29Z"},{"alias_kind":"arxiv_version","alias_value":"1703.01925v1","created_at":"2026-05-18T00:49:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.01925","created_at":"2026-05-18T00:49:29Z"},{"alias_kind":"pith_short_12","alias_value":"YONVRT3BIDOH","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YONVRT3BIDOHGPBL","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YONVRT3B","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:YONVRT3BIDOHGPBLXTGILD5DKV","target":"record","payload":{"canonical_record":{"source":{"id":"1703.01925","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-06T15:36:37Z","cross_cats_sorted":[],"title_canon_sha256":"798e6c86090e18bc4ef2e2e0b669e69fe3db64035f9e05795efd4c4e584bf7ff","abstract_canon_sha256":"1fe20027cf6ad03ef616b2d44d7f1e8276d05322caf6d02f6ef338325bf07df1"},"schema_version":"1.0"},"canonical_sha256":"c39b58cf6140dc733c2bbccc858fa3555fbbee370093eb0f93651f9dbb0615e9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:49:29.263996Z","signature_b64":"0raHvyStvbCkXDs3TTEdct77BAaa1Mu9v7BEcxd25jyfrFVStbhf5hg+ne+TWG9h6vCKUzKvDr77IsPTmc2PAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c39b58cf6140dc733c2bbccc858fa3555fbbee370093eb0f93651f9dbb0615e9","last_reissued_at":"2026-05-18T00:49:29.263372Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:49:29.263372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.01925","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":"2026-05-18T00:49:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KppSeZk/FyXZGda9KWVK6/HSJlbR4Xhktq9qnTiC86cmj+doTXp+ik4Cuj56rBSYrK99HRFtqhdeClrS2TrFBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T07:17:02.792600Z"},"content_sha256":"2011917833ee3f28e228f1813ef705bf2be0a1daf0c1cc17c870a3f880557b15","schema_version":"1.0","event_id":"sha256:2011917833ee3f28e228f1813ef705bf2be0a1daf0c1cc17c870a3f880557b15"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:YONVRT3BIDOHGPBLXTGILD5DKV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Grammar Variational Autoencoder","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Brooks Paige, Jos\\'e Miguel Hern\\'andez-Lobato, Matt J. Kusner","submitted_at":"2017-03-06T15:36:37Z","abstract_excerpt":"Deep generative models have been wildly successful at learning coherent latent representations for continuous data such as video and audio. However, generative modeling of discrete data such as arithmetic expressions and molecular structures still poses significant challenges. Crucially, state-of-the-art methods often produce outputs that are not valid. We make the key observation that frequently, discrete data can be represented as a parse tree from a context-free grammar. We propose a variational autoencoder which encodes and decodes directly to and from these parse trees, ensuring the gener"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.01925","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:49:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F/Pht6tI/1ZEXTwjdgD/xM/v+7ImMZArZCkL3JUg3hj02rV/sF8FGrs9sdKgrbXwssiQDhP4F9wUSiDpX9zvDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T07:17:02.792953Z"},"content_sha256":"a2fe90984527dd57c2ef138c0f40cfd3cfd86c0b1d6685a7d02adf986a22ef32","schema_version":"1.0","event_id":"sha256:a2fe90984527dd57c2ef138c0f40cfd3cfd86c0b1d6685a7d02adf986a22ef32"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YONVRT3BIDOHGPBLXTGILD5DKV/bundle.json","state_url":"https://pith.science/pith/YONVRT3BIDOHGPBLXTGILD5DKV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YONVRT3BIDOHGPBLXTGILD5DKV/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":"2026-06-02T07:17:02Z","links":{"resolver":"https://pith.science/pith/YONVRT3BIDOHGPBLXTGILD5DKV","bundle":"https://pith.science/pith/YONVRT3BIDOHGPBLXTGILD5DKV/bundle.json","state":"https://pith.science/pith/YONVRT3BIDOHGPBLXTGILD5DKV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YONVRT3BIDOHGPBLXTGILD5DKV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:YONVRT3BIDOHGPBLXTGILD5DKV","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":"1fe20027cf6ad03ef616b2d44d7f1e8276d05322caf6d02f6ef338325bf07df1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-06T15:36:37Z","title_canon_sha256":"798e6c86090e18bc4ef2e2e0b669e69fe3db64035f9e05795efd4c4e584bf7ff"},"schema_version":"1.0","source":{"id":"1703.01925","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.01925","created_at":"2026-05-18T00:49:29Z"},{"alias_kind":"arxiv_version","alias_value":"1703.01925v1","created_at":"2026-05-18T00:49:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.01925","created_at":"2026-05-18T00:49:29Z"},{"alias_kind":"pith_short_12","alias_value":"YONVRT3BIDOH","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YONVRT3BIDOHGPBL","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YONVRT3B","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:a2fe90984527dd57c2ef138c0f40cfd3cfd86c0b1d6685a7d02adf986a22ef32","target":"graph","created_at":"2026-05-18T00:49:29Z","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"},"paper":{"abstract_excerpt":"Deep generative models have been wildly successful at learning coherent latent representations for continuous data such as video and audio. However, generative modeling of discrete data such as arithmetic expressions and molecular structures still poses significant challenges. Crucially, state-of-the-art methods often produce outputs that are not valid. We make the key observation that frequently, discrete data can be represented as a parse tree from a context-free grammar. We propose a variational autoencoder which encodes and decodes directly to and from these parse trees, ensuring the gener","authors_text":"Brooks Paige, Jos\\'e Miguel Hern\\'andez-Lobato, Matt J. Kusner","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-06T15:36:37Z","title":"Grammar Variational Autoencoder"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.01925","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":"sha256:2011917833ee3f28e228f1813ef705bf2be0a1daf0c1cc17c870a3f880557b15","target":"record","created_at":"2026-05-18T00:49:29Z","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":"1fe20027cf6ad03ef616b2d44d7f1e8276d05322caf6d02f6ef338325bf07df1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-06T15:36:37Z","title_canon_sha256":"798e6c86090e18bc4ef2e2e0b669e69fe3db64035f9e05795efd4c4e584bf7ff"},"schema_version":"1.0","source":{"id":"1703.01925","kind":"arxiv","version":1}},"canonical_sha256":"c39b58cf6140dc733c2bbccc858fa3555fbbee370093eb0f93651f9dbb0615e9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c39b58cf6140dc733c2bbccc858fa3555fbbee370093eb0f93651f9dbb0615e9","first_computed_at":"2026-05-18T00:49:29.263372Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:49:29.263372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0raHvyStvbCkXDs3TTEdct77BAaa1Mu9v7BEcxd25jyfrFVStbhf5hg+ne+TWG9h6vCKUzKvDr77IsPTmc2PAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:49:29.263996Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.01925","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2011917833ee3f28e228f1813ef705bf2be0a1daf0c1cc17c870a3f880557b15","sha256:a2fe90984527dd57c2ef138c0f40cfd3cfd86c0b1d6685a7d02adf986a22ef32"],"state_sha256":"0413bf6e42e052142dd52baa31240d322f8d34bdeb9aff816d61f57d46c19365"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XjWYu+bU0dHfzFmuC8R6s9xlNLeGJ47broo0UGb434ZIjuqtwYtqOuIr9lEdImNlKJMDr1VA4s0/RDkPHrlMCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T07:17:02.794964Z","bundle_sha256":"94b1bf1036eedadcf3293345c311eaf6473f6a2f1810d7c3645650548c797388"}}