{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:FDWBSYFX5H2TU6J7VSBNHEARAP","short_pith_number":"pith:FDWBSYFX","canonical_record":{"source":{"id":"2309.10105","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-18T19:28:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d3dbb70aae54e9f99fd252455f3a18c12fb77b0951b50a17c5d764bb2e08ee1b","abstract_canon_sha256":"9ccfef5b6d556b41f54777394e0fc8f961fef9d41210796dc578aeb56bf2cd96"},"schema_version":"1.0"},"canonical_sha256":"28ec1960b7e9f53a793fac82d3901103f17e414c1c3cb2fd935ece5ba651d5e3","source":{"kind":"arxiv","id":"2309.10105","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.10105","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"arxiv_version","alias_value":"2309.10105v2","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.10105","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"pith_short_12","alias_value":"FDWBSYFX5H2T","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"pith_short_16","alias_value":"FDWBSYFX5H2TU6J7","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"pith_short_8","alias_value":"FDWBSYFX","created_at":"2026-07-05T08:07:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:FDWBSYFX5H2TU6J7VSBNHEARAP","target":"record","payload":{"canonical_record":{"source":{"id":"2309.10105","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-18T19:28:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d3dbb70aae54e9f99fd252455f3a18c12fb77b0951b50a17c5d764bb2e08ee1b","abstract_canon_sha256":"9ccfef5b6d556b41f54777394e0fc8f961fef9d41210796dc578aeb56bf2cd96"},"schema_version":"1.0"},"canonical_sha256":"28ec1960b7e9f53a793fac82d3901103f17e414c1c3cb2fd935ece5ba651d5e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:07:29.346135Z","signature_b64":"TNUIbZPrPfdD/Y6KbSmvJOWl3aV1aDU+kicVKBEWl1OruvpRgX8L+Hx/D9NYxgwcZ5XFEiqCDPpYi1wObQqWBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"28ec1960b7e9f53a793fac82d3901103f17e414c1c3cb2fd935ece5ba651d5e3","last_reissued_at":"2026-07-05T08:07:29.345590Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:07:29.345590Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.10105","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":"2026-07-05T08:07:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i4HPztIXKoBEVZ5RV6/1XPzY+rvzJL1AXO0Les8SIeGvqJZ7zJ/i6DpYIorn4hjzBGFtabZaA1dhcdx2hescAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T05:55:07.584344Z"},"content_sha256":"d9142e6487f3241ef446bc8b596279968e88a75102e5edd6342df20a297122d2","schema_version":"1.0","event_id":"sha256:d9142e6487f3241ef446bc8b596279968e88a75102e5edd6342df20a297122d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:FDWBSYFX5H2TU6J7VSBNHEARAP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding Catastrophic Forgetting in Language Models via Implicit Inference","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Aditi Raghunathan, Jacob Mitchell Springer, Suhas Kotha","submitted_at":"2023-09-18T19:28:48Z","abstract_excerpt":"We lack a systematic understanding of the effects of fine-tuning (via methods such as instruction-tuning or reinforcement learning from human feedback), particularly on tasks outside the narrow fine-tuning distribution. In a simplified scenario, we demonstrate that improving performance on tasks within the fine-tuning data distribution comes at the expense of capabilities on other tasks. We hypothesize that language models implicitly infer the task of the prompt and that fine-tuning skews this inference towards tasks in the fine-tuning distribution. To test this, we propose Conjugate Prompting"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.10105","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/2309.10105/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":"2026-07-05T08:07:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FSyBxJvzKoa0pPBNgjI7VyKbpSBurlRumyvmrRnc0GYeJwDgBIRv5c/mInD1zMXFu88A7bEJQoAe0CE/WC/4Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T05:55:07.584854Z"},"content_sha256":"3a54b7a7526cc23e645b66a145d9df9cf8c4dfcf501ea99a83861ba30d6f3c45","schema_version":"1.0","event_id":"sha256:3a54b7a7526cc23e645b66a145d9df9cf8c4dfcf501ea99a83861ba30d6f3c45"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FDWBSYFX5H2TU6J7VSBNHEARAP/bundle.json","state_url":"https://pith.science/pith/FDWBSYFX5H2TU6J7VSBNHEARAP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FDWBSYFX5H2TU6J7VSBNHEARAP/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":"2026-08-08T05:55:07Z","links":{"resolver":"https://pith.science/pith/FDWBSYFX5H2TU6J7VSBNHEARAP","bundle":"https://pith.science/pith/FDWBSYFX5H2TU6J7VSBNHEARAP/bundle.json","state":"https://pith.science/pith/FDWBSYFX5H2TU6J7VSBNHEARAP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FDWBSYFX5H2TU6J7VSBNHEARAP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:FDWBSYFX5H2TU6J7VSBNHEARAP","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":"9ccfef5b6d556b41f54777394e0fc8f961fef9d41210796dc578aeb56bf2cd96","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-18T19:28:48Z","title_canon_sha256":"d3dbb70aae54e9f99fd252455f3a18c12fb77b0951b50a17c5d764bb2e08ee1b"},"schema_version":"1.0","source":{"id":"2309.10105","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.10105","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"arxiv_version","alias_value":"2309.10105v2","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.10105","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"pith_short_12","alias_value":"FDWBSYFX5H2T","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"pith_short_16","alias_value":"FDWBSYFX5H2TU6J7","created_at":"2026-07-05T08:07:29Z"},{"alias_kind":"pith_short_8","alias_value":"FDWBSYFX","created_at":"2026-07-05T08:07:29Z"}],"graph_snapshots":[{"event_id":"sha256:3a54b7a7526cc23e645b66a145d9df9cf8c4dfcf501ea99a83861ba30d6f3c45","target":"graph","created_at":"2026-07-05T08:07:29Z","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/2309.10105/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We lack a systematic understanding of the effects of fine-tuning (via methods such as instruction-tuning or reinforcement learning from human feedback), particularly on tasks outside the narrow fine-tuning distribution. In a simplified scenario, we demonstrate that improving performance on tasks within the fine-tuning data distribution comes at the expense of capabilities on other tasks. We hypothesize that language models implicitly infer the task of the prompt and that fine-tuning skews this inference towards tasks in the fine-tuning distribution. To test this, we propose Conjugate Prompting","authors_text":"Aditi Raghunathan, Jacob Mitchell Springer, Suhas Kotha","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-18T19:28:48Z","title":"Understanding Catastrophic Forgetting in Language Models via Implicit Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.10105","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:d9142e6487f3241ef446bc8b596279968e88a75102e5edd6342df20a297122d2","target":"record","created_at":"2026-07-05T08:07:29Z","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":"9ccfef5b6d556b41f54777394e0fc8f961fef9d41210796dc578aeb56bf2cd96","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-18T19:28:48Z","title_canon_sha256":"d3dbb70aae54e9f99fd252455f3a18c12fb77b0951b50a17c5d764bb2e08ee1b"},"schema_version":"1.0","source":{"id":"2309.10105","kind":"arxiv","version":2}},"canonical_sha256":"28ec1960b7e9f53a793fac82d3901103f17e414c1c3cb2fd935ece5ba651d5e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"28ec1960b7e9f53a793fac82d3901103f17e414c1c3cb2fd935ece5ba651d5e3","first_computed_at":"2026-07-05T08:07:29.345590Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:07:29.345590Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TNUIbZPrPfdD/Y6KbSmvJOWl3aV1aDU+kicVKBEWl1OruvpRgX8L+Hx/D9NYxgwcZ5XFEiqCDPpYi1wObQqWBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:07:29.346135Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.10105","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d9142e6487f3241ef446bc8b596279968e88a75102e5edd6342df20a297122d2","sha256:3a54b7a7526cc23e645b66a145d9df9cf8c4dfcf501ea99a83861ba30d6f3c45"],"state_sha256":"0e2e2b7328262581717faf64003f623f7abd86cd56c35a6abd641647c8ae8baf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"asOBrtqIJtSQZo/gTGqPz7tcc8Ahdt5Cchlihzr9562lU6+vk9Kk8LdUW/7ENdtfabRwHi95KcGFFbmh3i/LBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T05:55:07.589888Z","bundle_sha256":"ecf69c04ea4357327062a312ce9a02e2aba074213ade0acf346116c13119ddb1"}}