{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:K2AXHRZVUSUSS5LDSBMV3XIM5X","short_pith_number":"pith:K2AXHRZV","canonical_record":{"source":{"id":"2106.00737","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-01T19:23:20Z","cross_cats_sorted":[],"title_canon_sha256":"a3f4358f9ef877d656932969347241508c7e60d00e700c6ebc6fb0adc53cff50","abstract_canon_sha256":"3d66448dc975d539d7260e753622c1f5eff0d06ae7e222e07e96fcf2de65d1ae"},"schema_version":"1.0"},"canonical_sha256":"568173c735a4a929756390595ddd0cede16907c378cced481b92888c7d17b45c","source":{"kind":"arxiv","id":"2106.00737","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.00737","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"arxiv_version","alias_value":"2106.00737v1","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.00737","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"pith_short_12","alias_value":"K2AXHRZVUSUS","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"pith_short_16","alias_value":"K2AXHRZVUSUSS5LD","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"pith_short_8","alias_value":"K2AXHRZV","created_at":"2026-07-05T02:45:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:K2AXHRZVUSUSS5LDSBMV3XIM5X","target":"record","payload":{"canonical_record":{"source":{"id":"2106.00737","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-01T19:23:20Z","cross_cats_sorted":[],"title_canon_sha256":"a3f4358f9ef877d656932969347241508c7e60d00e700c6ebc6fb0adc53cff50","abstract_canon_sha256":"3d66448dc975d539d7260e753622c1f5eff0d06ae7e222e07e96fcf2de65d1ae"},"schema_version":"1.0"},"canonical_sha256":"568173c735a4a929756390595ddd0cede16907c378cced481b92888c7d17b45c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:45:39.445890Z","signature_b64":"IboQ/f5NKB3h7T4+bmX9UHTgvv9M9IZuNGu/9pP1WzXEQVoQZU446YWm2S6N62QYiP8KlO9seVCKEqokprdqDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"568173c735a4a929756390595ddd0cede16907c378cced481b92888c7d17b45c","last_reissued_at":"2026-07-05T02:45:39.445504Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:45:39.445504Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.00737","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":"2026-07-05T02:45:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qta3NsWycWj6c7bSwLddj5MpjbcNscCKGExZmf0q/OTDz2TZEmvsLAEA9QXgbPxkyCpdA7nfgkfCCN80umd4Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T07:23:06.397597Z"},"content_sha256":"ad227eaad9f6ecfab304b50a43d61abae804d9ed9da57916c873336a6171ae57","schema_version":"1.0","event_id":"sha256:ad227eaad9f6ecfab304b50a43d61abae804d9ed9da57916c873336a6171ae57"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:K2AXHRZVUSUSS5LDSBMV3XIM5X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Implicit Representations of Meaning in Neural Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Belinda Z. Li, Jacob Andreas, Maxwell Nye","submitted_at":"2021-06-01T19:23:20Z","abstract_excerpt":"Does the effectiveness of neural language models derive entirely from accurate modeling of surface word co-occurrence statistics, or do these models represent and reason about the world they describe? In BART and T5 transformer language models, we identify contextual word representations that function as models of entities and situations as they evolve throughout a discourse. These neural representations have functional similarities to linguistic models of dynamic semantics: they support a linear readout of each entity's current properties and relations, and can be manipulated with predictable"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.00737","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2106.00737/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":"2026-07-05T02:45:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v75+Ek7kgrAql9RzjCXjfv5c+OjLmqnlApdPV2nQyXRLlB5R4rWwS2z7GPOECmmnEY5V27r5Rc2mFPJXepUWDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T07:23:06.398446Z"},"content_sha256":"143015b553d3a3d6444f9e5b9ff071d5f052a5be768039c14db1cef6197d578d","schema_version":"1.0","event_id":"sha256:143015b553d3a3d6444f9e5b9ff071d5f052a5be768039c14db1cef6197d578d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K2AXHRZVUSUSS5LDSBMV3XIM5X/bundle.json","state_url":"https://pith.science/pith/K2AXHRZVUSUSS5LDSBMV3XIM5X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K2AXHRZVUSUSS5LDSBMV3XIM5X/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":"2026-08-08T07:23:06Z","links":{"resolver":"https://pith.science/pith/K2AXHRZVUSUSS5LDSBMV3XIM5X","bundle":"https://pith.science/pith/K2AXHRZVUSUSS5LDSBMV3XIM5X/bundle.json","state":"https://pith.science/pith/K2AXHRZVUSUSS5LDSBMV3XIM5X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K2AXHRZVUSUSS5LDSBMV3XIM5X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:K2AXHRZVUSUSS5LDSBMV3XIM5X","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":"3d66448dc975d539d7260e753622c1f5eff0d06ae7e222e07e96fcf2de65d1ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-01T19:23:20Z","title_canon_sha256":"a3f4358f9ef877d656932969347241508c7e60d00e700c6ebc6fb0adc53cff50"},"schema_version":"1.0","source":{"id":"2106.00737","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.00737","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"arxiv_version","alias_value":"2106.00737v1","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.00737","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"pith_short_12","alias_value":"K2AXHRZVUSUS","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"pith_short_16","alias_value":"K2AXHRZVUSUSS5LD","created_at":"2026-07-05T02:45:39Z"},{"alias_kind":"pith_short_8","alias_value":"K2AXHRZV","created_at":"2026-07-05T02:45:39Z"}],"graph_snapshots":[{"event_id":"sha256:143015b553d3a3d6444f9e5b9ff071d5f052a5be768039c14db1cef6197d578d","target":"graph","created_at":"2026-07-05T02:45:39Z","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/2106.00737/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Does the effectiveness of neural language models derive entirely from accurate modeling of surface word co-occurrence statistics, or do these models represent and reason about the world they describe? In BART and T5 transformer language models, we identify contextual word representations that function as models of entities and situations as they evolve throughout a discourse. These neural representations have functional similarities to linguistic models of dynamic semantics: they support a linear readout of each entity's current properties and relations, and can be manipulated with predictable","authors_text":"Belinda Z. Li, Jacob Andreas, Maxwell Nye","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-01T19:23:20Z","title":"Implicit Representations of Meaning in Neural Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.00737","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:ad227eaad9f6ecfab304b50a43d61abae804d9ed9da57916c873336a6171ae57","target":"record","created_at":"2026-07-05T02:45:39Z","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":"3d66448dc975d539d7260e753622c1f5eff0d06ae7e222e07e96fcf2de65d1ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-01T19:23:20Z","title_canon_sha256":"a3f4358f9ef877d656932969347241508c7e60d00e700c6ebc6fb0adc53cff50"},"schema_version":"1.0","source":{"id":"2106.00737","kind":"arxiv","version":1}},"canonical_sha256":"568173c735a4a929756390595ddd0cede16907c378cced481b92888c7d17b45c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"568173c735a4a929756390595ddd0cede16907c378cced481b92888c7d17b45c","first_computed_at":"2026-07-05T02:45:39.445504Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:45:39.445504Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IboQ/f5NKB3h7T4+bmX9UHTgvv9M9IZuNGu/9pP1WzXEQVoQZU446YWm2S6N62QYiP8KlO9seVCKEqokprdqDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:45:39.445890Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.00737","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ad227eaad9f6ecfab304b50a43d61abae804d9ed9da57916c873336a6171ae57","sha256:143015b553d3a3d6444f9e5b9ff071d5f052a5be768039c14db1cef6197d578d"],"state_sha256":"988a9067dfaba02d41e557d889e4d9b6c10a466054fc7ab2a18a75a50fdcdff1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zK1e6xnPAil7rEm+7HKjPCMfxABP4ASM3hkWpPW2mZXuzpQPEiqZ/pyFUobZMxPCL8RX3YG8/FXXAmqV9cNgBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T07:23:06.405909Z","bundle_sha256":"01c04ba734053ca95a5421edd5ce669960eb98da2216cb2a00b3313b1a169541"}}