{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:AUS3C5YVJJL575BZBDQDUIYJL4","short_pith_number":"pith:AUS3C5YV","canonical_record":{"source":{"id":"1907.04944","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-10T22:13:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5897429bb30f1aef2b2ab3c8fb2be2543e10477749fc978399637b897d37cfe3","abstract_canon_sha256":"5043e5fd94e036a26a93641e5c051e561ce4965373e7d1a658b6a9a7892bb890"},"schema_version":"1.0"},"canonical_sha256":"0525b177154a57dff43908e03a23095f35d4caafd45a1aec026e8ce1e0c50071","source":{"kind":"arxiv","id":"1907.04944","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.04944","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.04944v2","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.04944","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"pith_short_12","alias_value":"AUS3C5YVJJL5","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"pith_short_16","alias_value":"AUS3C5YVJJL575BZ","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"pith_short_8","alias_value":"AUS3C5YV","created_at":"2026-07-05T00:32:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:AUS3C5YVJJL575BZBDQDUIYJL4","target":"record","payload":{"canonical_record":{"source":{"id":"1907.04944","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-10T22:13:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5897429bb30f1aef2b2ab3c8fb2be2543e10477749fc978399637b897d37cfe3","abstract_canon_sha256":"5043e5fd94e036a26a93641e5c051e561ce4965373e7d1a658b6a9a7892bb890"},"schema_version":"1.0"},"canonical_sha256":"0525b177154a57dff43908e03a23095f35d4caafd45a1aec026e8ce1e0c50071","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:32:38.800448Z","signature_b64":"WgAqwzhbJwd7NBKBVg6E1NPBHfrCraKFqXgimXYL7yF7hjIrN5YEIzNXpQL0N2ZLF1wJjhJhSjrvkKrmZpxwCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0525b177154a57dff43908e03a23095f35d4caafd45a1aec026e8ce1e0c50071","last_reissued_at":"2026-07-05T00:32:38.799984Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:32:38.799984Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.04944","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":"2026-07-05T00:32:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aM3AQnVUrLypeJxhMTojDZZ1Go04Yt7KbYXpVb0tw52nayWJGYswIA+BAOfwGaqWMsFL7s2w4GTTUXxSu+rEAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T03:51:42.417113Z"},"content_sha256":"5564c75906a12e5d780125d7b22408e6e5c651a2144ae9aa8a27fd6cb510ba9a","schema_version":"1.0","event_id":"sha256:5564c75906a12e5d780125d7b22408e6e5c651a2144ae9aa8a27fd6cb510ba9a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:AUS3C5YVJJL575BZBDQDUIYJL4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can Unconditional Language Models Recover Arbitrary Sentences?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Kyunghyun Cho, Nishant Subramani, Samuel R. Bowman","submitted_at":"2019-07-10T22:13:48Z","abstract_excerpt":"Neural network-based generative language models like ELMo and BERT can work effectively as general purpose sentence encoders in text classification without further fine-tuning. Is it possible to adapt them in a similar way for use as general-purpose decoders? For this to be possible, it would need to be the case that for any target sentence of interest, there is some continuous representation that can be passed to the language model to cause it to reproduce that sentence. We set aside the difficult problem of designing an encoder that can produce such representations and, instead, ask directly"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.04944","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1907.04944/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:32:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"skPLwJoc4rjNX68CAqH2AgJIEUq7pzXGchLBMILoTyvct0LQfKj075hc9N26zsL2GVN2nk5dcgcdS9ycgpzEAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T03:51:42.417498Z"},"content_sha256":"a76a27ec8431a0f27380e508e2b18464fd26c76e2e70ae3e326ff3d611642237","schema_version":"1.0","event_id":"sha256:a76a27ec8431a0f27380e508e2b18464fd26c76e2e70ae3e326ff3d611642237"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AUS3C5YVJJL575BZBDQDUIYJL4/bundle.json","state_url":"https://pith.science/pith/AUS3C5YVJJL575BZBDQDUIYJL4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AUS3C5YVJJL575BZBDQDUIYJL4/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":"2026-07-07T03:51:42Z","links":{"resolver":"https://pith.science/pith/AUS3C5YVJJL575BZBDQDUIYJL4","bundle":"https://pith.science/pith/AUS3C5YVJJL575BZBDQDUIYJL4/bundle.json","state":"https://pith.science/pith/AUS3C5YVJJL575BZBDQDUIYJL4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AUS3C5YVJJL575BZBDQDUIYJL4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:AUS3C5YVJJL575BZBDQDUIYJL4","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":"5043e5fd94e036a26a93641e5c051e561ce4965373e7d1a658b6a9a7892bb890","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-10T22:13:48Z","title_canon_sha256":"5897429bb30f1aef2b2ab3c8fb2be2543e10477749fc978399637b897d37cfe3"},"schema_version":"1.0","source":{"id":"1907.04944","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.04944","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.04944v2","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.04944","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"pith_short_12","alias_value":"AUS3C5YVJJL5","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"pith_short_16","alias_value":"AUS3C5YVJJL575BZ","created_at":"2026-07-05T00:32:38Z"},{"alias_kind":"pith_short_8","alias_value":"AUS3C5YV","created_at":"2026-07-05T00:32:38Z"}],"graph_snapshots":[{"event_id":"sha256:a76a27ec8431a0f27380e508e2b18464fd26c76e2e70ae3e326ff3d611642237","target":"graph","created_at":"2026-07-05T00:32:38Z","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/1907.04944/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural network-based generative language models like ELMo and BERT can work effectively as general purpose sentence encoders in text classification without further fine-tuning. Is it possible to adapt them in a similar way for use as general-purpose decoders? For this to be possible, it would need to be the case that for any target sentence of interest, there is some continuous representation that can be passed to the language model to cause it to reproduce that sentence. We set aside the difficult problem of designing an encoder that can produce such representations and, instead, ask directly","authors_text":"Kyunghyun Cho, Nishant Subramani, Samuel R. Bowman","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-10T22:13:48Z","title":"Can Unconditional Language Models Recover Arbitrary Sentences?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.04944","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":"sha256:5564c75906a12e5d780125d7b22408e6e5c651a2144ae9aa8a27fd6cb510ba9a","target":"record","created_at":"2026-07-05T00:32:38Z","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":"5043e5fd94e036a26a93641e5c051e561ce4965373e7d1a658b6a9a7892bb890","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-10T22:13:48Z","title_canon_sha256":"5897429bb30f1aef2b2ab3c8fb2be2543e10477749fc978399637b897d37cfe3"},"schema_version":"1.0","source":{"id":"1907.04944","kind":"arxiv","version":2}},"canonical_sha256":"0525b177154a57dff43908e03a23095f35d4caafd45a1aec026e8ce1e0c50071","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0525b177154a57dff43908e03a23095f35d4caafd45a1aec026e8ce1e0c50071","first_computed_at":"2026-07-05T00:32:38.799984Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:32:38.799984Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WgAqwzhbJwd7NBKBVg6E1NPBHfrCraKFqXgimXYL7yF7hjIrN5YEIzNXpQL0N2ZLF1wJjhJhSjrvkKrmZpxwCw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:32:38.800448Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.04944","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5564c75906a12e5d780125d7b22408e6e5c651a2144ae9aa8a27fd6cb510ba9a","sha256:a76a27ec8431a0f27380e508e2b18464fd26c76e2e70ae3e326ff3d611642237"],"state_sha256":"508de2b56fdbc77c48fd38b16f04cc2f00d35a2cdba86d7e49f4f3f1f51962e6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9M5b6zzL4lyayd+Ywell/YOnWAfeIcEMCQc4VornmqZg9HygXKiLS38JsiKE/HbVxBiz4vLmoJGHFlYmkw0CDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T03:51:42.419458Z","bundle_sha256":"abe9481012d74a46ce0e36556dc4abe83029eff8959e94eef67dc29cc46792d8"}}