{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5CNVFQWXGSGPYBPWCCH7BBLSOL","short_pith_number":"pith:5CNVFQWX","canonical_record":{"source":{"id":"2310.20620","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-31T16:53:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"bef62037bdfba1bc39d4a8e30d6e6511a36fc1fa8b5ba6c37bf4b0cc522db67c","abstract_canon_sha256":"442e97362ce419f538f8af3778f184c24d4efb7b09a5c8a63912902c5aaea6dc"},"schema_version":"1.0"},"canonical_sha256":"e89b52c2d7348cfc05f6108ff0857272e38237fcd1380b45adb4b0a57f49e502","source":{"kind":"arxiv","id":"2310.20620","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.20620","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"arxiv_version","alias_value":"2310.20620v2","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.20620","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"pith_short_12","alias_value":"5CNVFQWXGSGP","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"pith_short_16","alias_value":"5CNVFQWXGSGPYBPW","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"pith_short_8","alias_value":"5CNVFQWX","created_at":"2026-07-05T08:03:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5CNVFQWXGSGPYBPWCCH7BBLSOL","target":"record","payload":{"canonical_record":{"source":{"id":"2310.20620","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-31T16:53:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"bef62037bdfba1bc39d4a8e30d6e6511a36fc1fa8b5ba6c37bf4b0cc522db67c","abstract_canon_sha256":"442e97362ce419f538f8af3778f184c24d4efb7b09a5c8a63912902c5aaea6dc"},"schema_version":"1.0"},"canonical_sha256":"e89b52c2d7348cfc05f6108ff0857272e38237fcd1380b45adb4b0a57f49e502","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:03:27.522018Z","signature_b64":"mrYscxOuSBaG+p+a9IJpE3jnMArZ8/QA4uE8AYw/SwpOzzGHAFiwtjz1FbpgmeJX1d/rmUnHv/d8fQNi2D8dCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e89b52c2d7348cfc05f6108ff0857272e38237fcd1380b45adb4b0a57f49e502","last_reissued_at":"2026-07-05T08:03:27.521515Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:03:27.521515Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.20620","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":"2026-07-05T08:03:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9Sa+75Yyl0QdV51cgQDEr15hgLIYDHXJcm6L+M5uSre4vtYjA8a2a/xF5VYydxSpz1gaQrKIsYE9SylN9KXfDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T08:22:00.438907Z"},"content_sha256":"4ac4029707dddb4e2537c4e266594ac4d4f9a59598b30cf5875fa53c6980b9f2","schema_version":"1.0","event_id":"sha256:4ac4029707dddb4e2537c4e266594ac4d4f9a59598b30cf5875fa53c6980b9f2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5CNVFQWXGSGPYBPWCCH7BBLSOL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Unreasonable Effectiveness of Random Target Embeddings for Continuous-Output Neural Machine Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Evgeniia Tokarchuk, Vlad Niculae","submitted_at":"2023-10-31T16:53:10Z","abstract_excerpt":"Continuous-output neural machine translation (CoNMT) replaces the discrete next-word prediction problem with an embedding prediction. The semantic structure of the target embedding space (i.e., closeness of related words) is intuitively believed to be crucial. We challenge this assumption and show that completely random output embeddings can outperform laboriously pretrained ones, especially on larger datasets. Further investigation shows this surprising effect is strongest for rare words, due to the geometry of their embeddings. We shed further light on this finding by designing a mixed strat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.20620","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/2310.20620/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":"2026-07-05T08:03:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kaKHIVL49MUjHbYo/VaBh4dF2R1b1g1Gveam5bRaohT6LYX11MEpBx6SFwEnuwIJtgwb5etugJBO/Gody2wuBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T08:22:00.439306Z"},"content_sha256":"ecfc22647a28fb99f425be68de812ee97ecace871a12adbed9bee2e1b184aca8","schema_version":"1.0","event_id":"sha256:ecfc22647a28fb99f425be68de812ee97ecace871a12adbed9bee2e1b184aca8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5CNVFQWXGSGPYBPWCCH7BBLSOL/bundle.json","state_url":"https://pith.science/pith/5CNVFQWXGSGPYBPWCCH7BBLSOL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5CNVFQWXGSGPYBPWCCH7BBLSOL/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":"2026-07-11T08:22:00Z","links":{"resolver":"https://pith.science/pith/5CNVFQWXGSGPYBPWCCH7BBLSOL","bundle":"https://pith.science/pith/5CNVFQWXGSGPYBPWCCH7BBLSOL/bundle.json","state":"https://pith.science/pith/5CNVFQWXGSGPYBPWCCH7BBLSOL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5CNVFQWXGSGPYBPWCCH7BBLSOL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5CNVFQWXGSGPYBPWCCH7BBLSOL","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":"442e97362ce419f538f8af3778f184c24d4efb7b09a5c8a63912902c5aaea6dc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-31T16:53:10Z","title_canon_sha256":"bef62037bdfba1bc39d4a8e30d6e6511a36fc1fa8b5ba6c37bf4b0cc522db67c"},"schema_version":"1.0","source":{"id":"2310.20620","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.20620","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"arxiv_version","alias_value":"2310.20620v2","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.20620","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"pith_short_12","alias_value":"5CNVFQWXGSGP","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"pith_short_16","alias_value":"5CNVFQWXGSGPYBPW","created_at":"2026-07-05T08:03:27Z"},{"alias_kind":"pith_short_8","alias_value":"5CNVFQWX","created_at":"2026-07-05T08:03:27Z"}],"graph_snapshots":[{"event_id":"sha256:ecfc22647a28fb99f425be68de812ee97ecace871a12adbed9bee2e1b184aca8","target":"graph","created_at":"2026-07-05T08:03:27Z","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/2310.20620/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Continuous-output neural machine translation (CoNMT) replaces the discrete next-word prediction problem with an embedding prediction. The semantic structure of the target embedding space (i.e., closeness of related words) is intuitively believed to be crucial. We challenge this assumption and show that completely random output embeddings can outperform laboriously pretrained ones, especially on larger datasets. Further investigation shows this surprising effect is strongest for rare words, due to the geometry of their embeddings. We shed further light on this finding by designing a mixed strat","authors_text":"Evgeniia Tokarchuk, Vlad Niculae","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-31T16:53:10Z","title":"The Unreasonable Effectiveness of Random Target Embeddings for Continuous-Output Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.20620","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":"sha256:4ac4029707dddb4e2537c4e266594ac4d4f9a59598b30cf5875fa53c6980b9f2","target":"record","created_at":"2026-07-05T08:03:27Z","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":"442e97362ce419f538f8af3778f184c24d4efb7b09a5c8a63912902c5aaea6dc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-31T16:53:10Z","title_canon_sha256":"bef62037bdfba1bc39d4a8e30d6e6511a36fc1fa8b5ba6c37bf4b0cc522db67c"},"schema_version":"1.0","source":{"id":"2310.20620","kind":"arxiv","version":2}},"canonical_sha256":"e89b52c2d7348cfc05f6108ff0857272e38237fcd1380b45adb4b0a57f49e502","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e89b52c2d7348cfc05f6108ff0857272e38237fcd1380b45adb4b0a57f49e502","first_computed_at":"2026-07-05T08:03:27.521515Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:03:27.521515Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mrYscxOuSBaG+p+a9IJpE3jnMArZ8/QA4uE8AYw/SwpOzzGHAFiwtjz1FbpgmeJX1d/rmUnHv/d8fQNi2D8dCg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:03:27.522018Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.20620","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4ac4029707dddb4e2537c4e266594ac4d4f9a59598b30cf5875fa53c6980b9f2","sha256:ecfc22647a28fb99f425be68de812ee97ecace871a12adbed9bee2e1b184aca8"],"state_sha256":"d250f058c436045f681989efbe7ee9cf95979905760f0c0c237b648e473cd09f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"024ePEdRgF3KhvOAEqCgbEwVy/f3uw+BDZ/n56WIeRPDOvOo7VsgF6f7e5qvLsRNlgCwWlw5/8dXTF4NQLycAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T08:22:00.441761Z","bundle_sha256":"7a8c5b36ac6e9fe0ed31481c1e5ce5e16d3002b33dc2a47f6578f1a58d235ca5"}}