{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:SL7LOB6MA3TXF3QXNBBKGHZEVS","short_pith_number":"pith:SL7LOB6M","canonical_record":{"source":{"id":"1806.04550","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-12T14:19:48Z","cross_cats_sorted":["cs.CL","stat.ML"],"title_canon_sha256":"d1992f288e48e24ea1dbe643b26e4b7e501f96a878e915d0fdeebd8dadc676de","abstract_canon_sha256":"163b7d25ec86d5c93c8401ff4a928340a1dbef45ebbc6784f5e7d0b2a7b5b11b"},"schema_version":"1.0"},"canonical_sha256":"92feb707cc06e772ee176842a31f24ac83aef9a33ac8ddecbeb8d81c0b4e716e","source":{"kind":"arxiv","id":"1806.04550","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04550","created_at":"2026-05-18T00:02:09Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04550v2","created_at":"2026-05-18T00:02:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04550","created_at":"2026-05-18T00:02:09Z"},{"alias_kind":"pith_short_12","alias_value":"SL7LOB6MA3TX","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SL7LOB6MA3TXF3QX","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SL7LOB6M","created_at":"2026-05-18T12:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:SL7LOB6MA3TXF3QXNBBKGHZEVS","target":"record","payload":{"canonical_record":{"source":{"id":"1806.04550","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-12T14:19:48Z","cross_cats_sorted":["cs.CL","stat.ML"],"title_canon_sha256":"d1992f288e48e24ea1dbe643b26e4b7e501f96a878e915d0fdeebd8dadc676de","abstract_canon_sha256":"163b7d25ec86d5c93c8401ff4a928340a1dbef45ebbc6784f5e7d0b2a7b5b11b"},"schema_version":"1.0"},"canonical_sha256":"92feb707cc06e772ee176842a31f24ac83aef9a33ac8ddecbeb8d81c0b4e716e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:02:09.790997Z","signature_b64":"83bJKLCGu2ZQqIvLxqf4s+tw3+d4gX7ky8t/dXkokHOAueP3aDC+9D9kIQC80TIVC9f+PNxpTE3mrCHiHr8rCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92feb707cc06e772ee176842a31f24ac83aef9a33ac8ddecbeb8d81c0b4e716e","last_reissued_at":"2026-05-18T00:02:09.790378Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:02:09.790378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.04550","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:02:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s2meAQQrnbIL2JSaJunlzBdao9UL4WmrsbmSI0uQ3pv3TMQE6vs3oYmo6M5deKUyDgeUivCZ5mKujren1ThaDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T18:24:10.638166Z"},"content_sha256":"b29da9e26a62c943c20203a840c1ec3e2c400102c20f744e3b14046ba8a0764d","schema_version":"1.0","event_id":"sha256:b29da9e26a62c943c20203a840c1ec3e2c400102c20f744e3b14046ba8a0764d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:SL7LOB6MA3TXF3QXNBBKGHZEVS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep State Space Models for Unconditional Word Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","stat.ML"],"primary_cat":"cs.LG","authors_text":"Florian Schmidt, Thomas Hofmann","submitted_at":"2018-06-12T14:19:48Z","abstract_excerpt":"Autoregressive feedback is considered a necessity for successful unconditional text generation using stochastic sequence models. However, such feedback is known to introduce systematic biases into the training process and it obscures a principle of generation: committing to global information and forgetting local nuances. We show that a non-autoregressive deep state space model with a clear separation of global and local uncertainty can be built from only two ingredients: An independent noise source and a deterministic transition function. Recent advances on flow-based variational inference ca"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04550","kind":"arxiv","version":2},"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":"2026-05-18T00:02:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T4O2ShDy5sJN6OGQ7B0GxPBHY1WBU5EjrtYC4OxFCfZPJgg/oSGYK/C3j6y2jLEsegPR5kgqPBRvjcyOdmBJAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T18:24:10.638539Z"},"content_sha256":"4cb73eaddc602e460353d2f514931dde2ce78078fd8efabb9dc2474012e8a532","schema_version":"1.0","event_id":"sha256:4cb73eaddc602e460353d2f514931dde2ce78078fd8efabb9dc2474012e8a532"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SL7LOB6MA3TXF3QXNBBKGHZEVS/bundle.json","state_url":"https://pith.science/pith/SL7LOB6MA3TXF3QXNBBKGHZEVS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SL7LOB6MA3TXF3QXNBBKGHZEVS/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":"2026-06-24T18:24:10Z","links":{"resolver":"https://pith.science/pith/SL7LOB6MA3TXF3QXNBBKGHZEVS","bundle":"https://pith.science/pith/SL7LOB6MA3TXF3QXNBBKGHZEVS/bundle.json","state":"https://pith.science/pith/SL7LOB6MA3TXF3QXNBBKGHZEVS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SL7LOB6MA3TXF3QXNBBKGHZEVS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:SL7LOB6MA3TXF3QXNBBKGHZEVS","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":"163b7d25ec86d5c93c8401ff4a928340a1dbef45ebbc6784f5e7d0b2a7b5b11b","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-12T14:19:48Z","title_canon_sha256":"d1992f288e48e24ea1dbe643b26e4b7e501f96a878e915d0fdeebd8dadc676de"},"schema_version":"1.0","source":{"id":"1806.04550","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04550","created_at":"2026-05-18T00:02:09Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04550v2","created_at":"2026-05-18T00:02:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04550","created_at":"2026-05-18T00:02:09Z"},{"alias_kind":"pith_short_12","alias_value":"SL7LOB6MA3TX","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SL7LOB6MA3TXF3QX","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SL7LOB6M","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:4cb73eaddc602e460353d2f514931dde2ce78078fd8efabb9dc2474012e8a532","target":"graph","created_at":"2026-05-18T00:02:09Z","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":"Autoregressive feedback is considered a necessity for successful unconditional text generation using stochastic sequence models. However, such feedback is known to introduce systematic biases into the training process and it obscures a principle of generation: committing to global information and forgetting local nuances. We show that a non-autoregressive deep state space model with a clear separation of global and local uncertainty can be built from only two ingredients: An independent noise source and a deterministic transition function. Recent advances on flow-based variational inference ca","authors_text":"Florian Schmidt, Thomas Hofmann","cross_cats":["cs.CL","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-12T14:19:48Z","title":"Deep State Space Models for Unconditional Word Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04550","kind":"arxiv","version":2},"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:b29da9e26a62c943c20203a840c1ec3e2c400102c20f744e3b14046ba8a0764d","target":"record","created_at":"2026-05-18T00:02:09Z","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":"163b7d25ec86d5c93c8401ff4a928340a1dbef45ebbc6784f5e7d0b2a7b5b11b","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-12T14:19:48Z","title_canon_sha256":"d1992f288e48e24ea1dbe643b26e4b7e501f96a878e915d0fdeebd8dadc676de"},"schema_version":"1.0","source":{"id":"1806.04550","kind":"arxiv","version":2}},"canonical_sha256":"92feb707cc06e772ee176842a31f24ac83aef9a33ac8ddecbeb8d81c0b4e716e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92feb707cc06e772ee176842a31f24ac83aef9a33ac8ddecbeb8d81c0b4e716e","first_computed_at":"2026-05-18T00:02:09.790378Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:09.790378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"83bJKLCGu2ZQqIvLxqf4s+tw3+d4gX7ky8t/dXkokHOAueP3aDC+9D9kIQC80TIVC9f+PNxpTE3mrCHiHr8rCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:09.790997Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.04550","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b29da9e26a62c943c20203a840c1ec3e2c400102c20f744e3b14046ba8a0764d","sha256:4cb73eaddc602e460353d2f514931dde2ce78078fd8efabb9dc2474012e8a532"],"state_sha256":"4f17bad61fa010f8255cb8e857ca189b2e7436ab36e309a1aab3e0658468a6bb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BEhBBGhqjJiVHcOwAtmlKiYVjhaDc0zBQnTAmoPw/N5re8yDSwtiNsgtBGMeBqDZD8dnAHM5zSZM+QOGdgYkAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T18:24:10.640417Z","bundle_sha256":"c5f6c85ce7052ac30928a8803ed62c73aec0e3da725bfae0302d0b561661afd5"}}