{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:SUUGXSNIOLZ3GBLHOEKYKOL2RH","short_pith_number":"pith:SUUGXSNI","canonical_record":{"source":{"id":"1806.00913","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-04T01:20:59Z","cross_cats_sorted":[],"title_canon_sha256":"78f65c2a72910af48f1532e243060d2d7f6404a31dec9af1580d0c2442d95155","abstract_canon_sha256":"6801fe3bd9214f8aa7432d5bbc8c2b6b9f00727681bfdf0cc7c49834f9728c55"},"schema_version":"1.0"},"canonical_sha256":"95286bc9a872f3b30567711585397a89c39de3d8dc02993f23061e43239911cf","source":{"kind":"arxiv","id":"1806.00913","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.00913","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"arxiv_version","alias_value":"1806.00913v1","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00913","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"pith_short_12","alias_value":"SUUGXSNIOLZ3","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SUUGXSNIOLZ3GBLH","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SUUGXSNI","created_at":"2026-05-18T12:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:SUUGXSNIOLZ3GBLHOEKYKOL2RH","target":"record","payload":{"canonical_record":{"source":{"id":"1806.00913","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-04T01:20:59Z","cross_cats_sorted":[],"title_canon_sha256":"78f65c2a72910af48f1532e243060d2d7f6404a31dec9af1580d0c2442d95155","abstract_canon_sha256":"6801fe3bd9214f8aa7432d5bbc8c2b6b9f00727681bfdf0cc7c49834f9728c55"},"schema_version":"1.0"},"canonical_sha256":"95286bc9a872f3b30567711585397a89c39de3d8dc02993f23061e43239911cf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:18.029557Z","signature_b64":"ammzwtTeh3SGtpQA85BGzFdbvs+/dRc2Nv/F4LhAOde8WLSM+ErjmWhm+CGf6727XS5MxPdlB5NTKfXbPnqmCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95286bc9a872f3b30567711585397a89c39de3d8dc02993f23061e43239911cf","last_reissued_at":"2026-05-18T00:14:18.028901Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:18.028901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.00913","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":"2026-05-18T00:14:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2UnwCV/fa8G8M2meLybsXar+ErU/QuJmVHKzYcp+5BHIVLEHRBicmOI/Qtm0hkAgqbPLZetFXL5/7781nxF3DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T07:35:26.539237Z"},"content_sha256":"1b6889cc8c9d5e23a256a9c2f85b973c92d859749dd290f121129a044bf1c0bd","schema_version":"1.0","event_id":"sha256:1b6889cc8c9d5e23a256a9c2f85b973c92d859749dd290f121129a044bf1c0bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:SUUGXSNIOLZ3GBLHOEKYKOL2RH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Self-Normalization Properties of Language Modeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jacob Goldberger, Oren Melamud","submitted_at":"2018-06-04T01:20:59Z","abstract_excerpt":"Self-normalizing discriminative models approximate the normalized probability of a class without having to compute the partition function. In the context of language modeling, this property is particularly appealing as it may significantly reduce run-times due to large word vocabularies. In this study, we provide a comprehensive investigation of language modeling self-normalization. First, we theoretically analyze the inherent self-normalization properties of Noise Contrastive Estimation (NCE) language models. Then, we compare them empirically to softmax-based approaches, which are self-normal"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00913","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":"2026-05-18T00:14:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0wXQBhiwnbUxp/GYs6F87FHeZK3DvkwJ+xM4IgtXFC0VHwVLc12dzCwzvqzBdpBLeg89TsXhp32gKLnsxvaPCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T07:35:26.539794Z"},"content_sha256":"f61aa36f21e1fac54467f793ddac9d0a938eb8d446e4728420f3ca5fe23530e1","schema_version":"1.0","event_id":"sha256:f61aa36f21e1fac54467f793ddac9d0a938eb8d446e4728420f3ca5fe23530e1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SUUGXSNIOLZ3GBLHOEKYKOL2RH/bundle.json","state_url":"https://pith.science/pith/SUUGXSNIOLZ3GBLHOEKYKOL2RH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SUUGXSNIOLZ3GBLHOEKYKOL2RH/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":"2026-05-30T07:35:26Z","links":{"resolver":"https://pith.science/pith/SUUGXSNIOLZ3GBLHOEKYKOL2RH","bundle":"https://pith.science/pith/SUUGXSNIOLZ3GBLHOEKYKOL2RH/bundle.json","state":"https://pith.science/pith/SUUGXSNIOLZ3GBLHOEKYKOL2RH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SUUGXSNIOLZ3GBLHOEKYKOL2RH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:SUUGXSNIOLZ3GBLHOEKYKOL2RH","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":"6801fe3bd9214f8aa7432d5bbc8c2b6b9f00727681bfdf0cc7c49834f9728c55","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-04T01:20:59Z","title_canon_sha256":"78f65c2a72910af48f1532e243060d2d7f6404a31dec9af1580d0c2442d95155"},"schema_version":"1.0","source":{"id":"1806.00913","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.00913","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"arxiv_version","alias_value":"1806.00913v1","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00913","created_at":"2026-05-18T00:14:18Z"},{"alias_kind":"pith_short_12","alias_value":"SUUGXSNIOLZ3","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SUUGXSNIOLZ3GBLH","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SUUGXSNI","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:f61aa36f21e1fac54467f793ddac9d0a938eb8d446e4728420f3ca5fe23530e1","target":"graph","created_at":"2026-05-18T00:14:18Z","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":"Self-normalizing discriminative models approximate the normalized probability of a class without having to compute the partition function. In the context of language modeling, this property is particularly appealing as it may significantly reduce run-times due to large word vocabularies. In this study, we provide a comprehensive investigation of language modeling self-normalization. First, we theoretically analyze the inherent self-normalization properties of Noise Contrastive Estimation (NCE) language models. Then, we compare them empirically to softmax-based approaches, which are self-normal","authors_text":"Jacob Goldberger, Oren Melamud","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-04T01:20:59Z","title":"Self-Normalization Properties of Language Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00913","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":"sha256:1b6889cc8c9d5e23a256a9c2f85b973c92d859749dd290f121129a044bf1c0bd","target":"record","created_at":"2026-05-18T00:14:18Z","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":"6801fe3bd9214f8aa7432d5bbc8c2b6b9f00727681bfdf0cc7c49834f9728c55","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-04T01:20:59Z","title_canon_sha256":"78f65c2a72910af48f1532e243060d2d7f6404a31dec9af1580d0c2442d95155"},"schema_version":"1.0","source":{"id":"1806.00913","kind":"arxiv","version":1}},"canonical_sha256":"95286bc9a872f3b30567711585397a89c39de3d8dc02993f23061e43239911cf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95286bc9a872f3b30567711585397a89c39de3d8dc02993f23061e43239911cf","first_computed_at":"2026-05-18T00:14:18.028901Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:18.028901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ammzwtTeh3SGtpQA85BGzFdbvs+/dRc2Nv/F4LhAOde8WLSM+ErjmWhm+CGf6727XS5MxPdlB5NTKfXbPnqmCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:18.029557Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.00913","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b6889cc8c9d5e23a256a9c2f85b973c92d859749dd290f121129a044bf1c0bd","sha256:f61aa36f21e1fac54467f793ddac9d0a938eb8d446e4728420f3ca5fe23530e1"],"state_sha256":"a81482a3a5d415443fb3674e9104fb563ca318b972dc7cedf5982b78f177c347"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6ACS/EbpK+bzJOdePm7SIsz3dhzg5RkxqmVc+QsqqilGVjRltFcsrNKYurS8DgZtUEZPkW4faIH4Wr42Xe/5Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T07:35:26.544536Z","bundle_sha256":"938c5195f905a110063df12f41ca31bd40de7cd3a8f8419269c8317391021058"}}