{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:CDKMB7NBF66N554P2XWO5J3OXL","short_pith_number":"pith:CDKMB7NB","canonical_record":{"source":{"id":"2406.04823","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T10:48:45Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"921020177fcd5c9530a70c922513022922ac2d7d9c3b69050e95c8aebab54cee","abstract_canon_sha256":"9e5a0518cffd6428ea4645cc9332cc79f428959c4923b9ea7d38348a9ff9dd42"},"schema_version":"1.0"},"canonical_sha256":"10d4c0fda12fbcdef78fd5eceea76ebaffc049cbd20b960e6f8559206e133fd8","source":{"kind":"arxiv","id":"2406.04823","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04823","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04823v2","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04823","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_12","alias_value":"CDKMB7NBF66N","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_16","alias_value":"CDKMB7NBF66N554P","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_8","alias_value":"CDKMB7NB","created_at":"2026-07-05T09:29:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:CDKMB7NBF66N554P2XWO5J3OXL","target":"record","payload":{"canonical_record":{"source":{"id":"2406.04823","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T10:48:45Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"921020177fcd5c9530a70c922513022922ac2d7d9c3b69050e95c8aebab54cee","abstract_canon_sha256":"9e5a0518cffd6428ea4645cc9332cc79f428959c4923b9ea7d38348a9ff9dd42"},"schema_version":"1.0"},"canonical_sha256":"10d4c0fda12fbcdef78fd5eceea76ebaffc049cbd20b960e6f8559206e133fd8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:29:14.769104Z","signature_b64":"nzK66w0wIYBmeIOU7Hcu/kT7BIgj8ojTm9eAUcORkw87ZRlK651GLyNI4j/e61YWg6iBWsCaQfv4AJU/t+0EAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"10d4c0fda12fbcdef78fd5eceea76ebaffc049cbd20b960e6f8559206e133fd8","last_reissued_at":"2026-07-05T09:29:14.768637Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:29:14.768637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.04823","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":"2026-07-05T09:29:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vldVygN8rpfQT3XzEwUuU2dGANV8kNIsQCFKKzHS5psT5cyHDoqZgupA02Wk3Bss9RdSZOuKTAiKSiYcU8JeAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T15:44:10.048738Z"},"content_sha256":"9f647ef8717d85bf2dc6cfa7fde51b59bd9861e2cbd87658216874ea2edbbf50","schema_version":"1.0","event_id":"sha256:9f647ef8717d85bf2dc6cfa7fde51b59bd9861e2cbd87658216874ea2edbbf50"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:CDKMB7NBF66N554P2XWO5J3OXL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BERTs are Generative In-Context Learners","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"David Samuel","submitted_at":"2024-06-07T10:48:45Z","abstract_excerpt":"While in-context learning is commonly associated with causal language models, such as GPT, we demonstrate that this capability also 'emerges' in masked language models. Through an embarrassingly simple inference technique, we enable an existing masked model, DeBERTa, to perform generative tasks without additional training or architectural changes. Our evaluation reveals that the masked and causal language models behave very differently, as they clearly outperform each other on different categories of tasks. These complementary strengths suggest that the field's focus on causal models for in-co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04823","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/2406.04823/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":"2026-07-05T09:29:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N1a8e/QX61a4T8GRuMXdGMWogaWE7bJV85cJ2BbKj7FNknd2F22cnkAvDulE8SCGIUuxUzPGD61Nz8kvEJtrDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T15:44:10.049767Z"},"content_sha256":"4413202cf26754123b096474e47b1f0d9caa2ecbd59eaa81a3c5227598c57f21","schema_version":"1.0","event_id":"sha256:4413202cf26754123b096474e47b1f0d9caa2ecbd59eaa81a3c5227598c57f21"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CDKMB7NBF66N554P2XWO5J3OXL/bundle.json","state_url":"https://pith.science/pith/CDKMB7NBF66N554P2XWO5J3OXL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CDKMB7NBF66N554P2XWO5J3OXL/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":"2026-08-07T15:44:10Z","links":{"resolver":"https://pith.science/pith/CDKMB7NBF66N554P2XWO5J3OXL","bundle":"https://pith.science/pith/CDKMB7NBF66N554P2XWO5J3OXL/bundle.json","state":"https://pith.science/pith/CDKMB7NBF66N554P2XWO5J3OXL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CDKMB7NBF66N554P2XWO5J3OXL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CDKMB7NBF66N554P2XWO5J3OXL","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":"9e5a0518cffd6428ea4645cc9332cc79f428959c4923b9ea7d38348a9ff9dd42","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T10:48:45Z","title_canon_sha256":"921020177fcd5c9530a70c922513022922ac2d7d9c3b69050e95c8aebab54cee"},"schema_version":"1.0","source":{"id":"2406.04823","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04823","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04823v2","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04823","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_12","alias_value":"CDKMB7NBF66N","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_16","alias_value":"CDKMB7NBF66N554P","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_8","alias_value":"CDKMB7NB","created_at":"2026-07-05T09:29:14Z"}],"graph_snapshots":[{"event_id":"sha256:4413202cf26754123b096474e47b1f0d9caa2ecbd59eaa81a3c5227598c57f21","target":"graph","created_at":"2026-07-05T09:29:14Z","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/2406.04823/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While in-context learning is commonly associated with causal language models, such as GPT, we demonstrate that this capability also 'emerges' in masked language models. Through an embarrassingly simple inference technique, we enable an existing masked model, DeBERTa, to perform generative tasks without additional training or architectural changes. Our evaluation reveals that the masked and causal language models behave very differently, as they clearly outperform each other on different categories of tasks. These complementary strengths suggest that the field's focus on causal models for in-co","authors_text":"David Samuel","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T10:48:45Z","title":"BERTs are Generative In-Context Learners"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04823","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":"sha256:9f647ef8717d85bf2dc6cfa7fde51b59bd9861e2cbd87658216874ea2edbbf50","target":"record","created_at":"2026-07-05T09:29:14Z","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":"9e5a0518cffd6428ea4645cc9332cc79f428959c4923b9ea7d38348a9ff9dd42","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T10:48:45Z","title_canon_sha256":"921020177fcd5c9530a70c922513022922ac2d7d9c3b69050e95c8aebab54cee"},"schema_version":"1.0","source":{"id":"2406.04823","kind":"arxiv","version":2}},"canonical_sha256":"10d4c0fda12fbcdef78fd5eceea76ebaffc049cbd20b960e6f8559206e133fd8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"10d4c0fda12fbcdef78fd5eceea76ebaffc049cbd20b960e6f8559206e133fd8","first_computed_at":"2026-07-05T09:29:14.768637Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:29:14.768637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nzK66w0wIYBmeIOU7Hcu/kT7BIgj8ojTm9eAUcORkw87ZRlK651GLyNI4j/e61YWg6iBWsCaQfv4AJU/t+0EAg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:29:14.769104Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.04823","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9f647ef8717d85bf2dc6cfa7fde51b59bd9861e2cbd87658216874ea2edbbf50","sha256:4413202cf26754123b096474e47b1f0d9caa2ecbd59eaa81a3c5227598c57f21"],"state_sha256":"695e9a2aedb4dc2b5a73f1dfc17a72fb4bfa2b00a3331e596bd33c58787ca264"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"McHxMpa1/F9gBCwc02S5JZ5aC37x/phZkGGJfej1302kFJMPdut+d0UnAPu6aO7RJM7wXvTqJCKNXExmj9NBDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T15:44:10.057119Z","bundle_sha256":"31ed7cbc19dc654a86ff8c1014966b6af780beefa76b38cf317126d94682d5a5"}}