{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GXUN7LXVQ4R3TG2RFX6W74R6M7","short_pith_number":"pith:GXUN7LXV","canonical_record":{"source":{"id":"2402.01865","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T19:43:15Z","cross_cats_sorted":["cs.CL","stat.ML"],"title_canon_sha256":"fa678c4c764323379352e80474503086a8ff82f42279beb3a5ecc2ceafa0bf80","abstract_canon_sha256":"2106d6fa5fe100721c14f0448aaa5a49f7e4b7f06f9c1f87a78e896a3ce6f47d"},"schema_version":"1.0"},"canonical_sha256":"35e8dfaef58723b99b512dfd6ff23e67e1a7dff02e0d197e151332e977aa228e","source":{"kind":"arxiv","id":"2402.01865","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01865","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01865v3","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01865","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"pith_short_12","alias_value":"GXUN7LXVQ4R3","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"pith_short_16","alias_value":"GXUN7LXVQ4R3TG2R","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"pith_short_8","alias_value":"GXUN7LXV","created_at":"2026-07-05T09:46:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GXUN7LXVQ4R3TG2RFX6W74R6M7","target":"record","payload":{"canonical_record":{"source":{"id":"2402.01865","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T19:43:15Z","cross_cats_sorted":["cs.CL","stat.ML"],"title_canon_sha256":"fa678c4c764323379352e80474503086a8ff82f42279beb3a5ecc2ceafa0bf80","abstract_canon_sha256":"2106d6fa5fe100721c14f0448aaa5a49f7e4b7f06f9c1f87a78e896a3ce6f47d"},"schema_version":"1.0"},"canonical_sha256":"35e8dfaef58723b99b512dfd6ff23e67e1a7dff02e0d197e151332e977aa228e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:46:44.723602Z","signature_b64":"ZAZ2Qh5u/k/Rei21uDAVDZFMZpw95du7Y9IqRw3YVvwozDWseXXnHDwjzQ1Lxn3pPFaUfUdariRbSnAfuj2CBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"35e8dfaef58723b99b512dfd6ff23e67e1a7dff02e0d197e151332e977aa228e","last_reissued_at":"2026-07-05T09:46:44.723161Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:46:44.723161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.01865","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:46:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7B+KtyebPODjYVU/98zduilIHE12g1dc17Gn4mekcoxkbNrYK5pCsY5aq26YpGTtJRlYVDbfK3d3Ce4haRqGAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:47:26.533452Z"},"content_sha256":"b9b55ce470a5888cddd52169163ec9c190aa35c506ab95eb060352107d1681b9","schema_version":"1.0","event_id":"sha256:b9b55ce470a5888cddd52169163ec9c190aa35c506ab95eb060352107d1681b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GXUN7LXVQ4R3TG2RFX6W74R6M7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.CL","stat.ML"],"primary_cat":"cs.LG","authors_text":"Xiang Ren, Xisen Jin","submitted_at":"2024-02-02T19:43:15Z","abstract_excerpt":"Language models deployed in the wild make errors. However, simply updating the model with the corrected error instances causes catastrophic forgetting -- the updated model makes errors on instances learned during the instruction tuning or upstream training phase. Randomly replaying upstream data yields unsatisfactory performance and often comes with high variance and poor controllability. To this end, we try to forecast upstream examples that will be forgotten due to a model update for improved controllability of the replay process and interpretability. We train forecasting models given a coll"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01865","kind":"arxiv","version":3},"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/2402.01865/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":"2026-07-05T09:46:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ow+Nh6CYr/fPxNHLvpq9sP/VxJhKI4oNKZjYVxwWpmPtCFqIN8SngckX5wyKYwsjmOS9b5oln46wNMI0WD1DBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:47:26.533972Z"},"content_sha256":"25a862c87908461d132354c8b1de6772a9110e70ea0d47cb45d64fb0a977ffc4","schema_version":"1.0","event_id":"sha256:25a862c87908461d132354c8b1de6772a9110e70ea0d47cb45d64fb0a977ffc4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GXUN7LXVQ4R3TG2RFX6W74R6M7/bundle.json","state_url":"https://pith.science/pith/GXUN7LXVQ4R3TG2RFX6W74R6M7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GXUN7LXVQ4R3TG2RFX6W74R6M7/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":"2026-08-10T12:47:26Z","links":{"resolver":"https://pith.science/pith/GXUN7LXVQ4R3TG2RFX6W74R6M7","bundle":"https://pith.science/pith/GXUN7LXVQ4R3TG2RFX6W74R6M7/bundle.json","state":"https://pith.science/pith/GXUN7LXVQ4R3TG2RFX6W74R6M7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GXUN7LXVQ4R3TG2RFX6W74R6M7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GXUN7LXVQ4R3TG2RFX6W74R6M7","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":"2106d6fa5fe100721c14f0448aaa5a49f7e4b7f06f9c1f87a78e896a3ce6f47d","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T19:43:15Z","title_canon_sha256":"fa678c4c764323379352e80474503086a8ff82f42279beb3a5ecc2ceafa0bf80"},"schema_version":"1.0","source":{"id":"2402.01865","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01865","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01865v3","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01865","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"pith_short_12","alias_value":"GXUN7LXVQ4R3","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"pith_short_16","alias_value":"GXUN7LXVQ4R3TG2R","created_at":"2026-07-05T09:46:44Z"},{"alias_kind":"pith_short_8","alias_value":"GXUN7LXV","created_at":"2026-07-05T09:46:44Z"}],"graph_snapshots":[{"event_id":"sha256:25a862c87908461d132354c8b1de6772a9110e70ea0d47cb45d64fb0a977ffc4","target":"graph","created_at":"2026-07-05T09:46:44Z","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/2402.01865/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Language models deployed in the wild make errors. However, simply updating the model with the corrected error instances causes catastrophic forgetting -- the updated model makes errors on instances learned during the instruction tuning or upstream training phase. Randomly replaying upstream data yields unsatisfactory performance and often comes with high variance and poor controllability. To this end, we try to forecast upstream examples that will be forgotten due to a model update for improved controllability of the replay process and interpretability. We train forecasting models given a coll","authors_text":"Xiang Ren, Xisen Jin","cross_cats":["cs.CL","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T19:43:15Z","title":"What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01865","kind":"arxiv","version":3},"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:b9b55ce470a5888cddd52169163ec9c190aa35c506ab95eb060352107d1681b9","target":"record","created_at":"2026-07-05T09:46:44Z","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":"2106d6fa5fe100721c14f0448aaa5a49f7e4b7f06f9c1f87a78e896a3ce6f47d","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-02T19:43:15Z","title_canon_sha256":"fa678c4c764323379352e80474503086a8ff82f42279beb3a5ecc2ceafa0bf80"},"schema_version":"1.0","source":{"id":"2402.01865","kind":"arxiv","version":3}},"canonical_sha256":"35e8dfaef58723b99b512dfd6ff23e67e1a7dff02e0d197e151332e977aa228e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35e8dfaef58723b99b512dfd6ff23e67e1a7dff02e0d197e151332e977aa228e","first_computed_at":"2026-07-05T09:46:44.723161Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:46:44.723161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZAZ2Qh5u/k/Rei21uDAVDZFMZpw95du7Y9IqRw3YVvwozDWseXXnHDwjzQ1Lxn3pPFaUfUdariRbSnAfuj2CBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:46:44.723602Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.01865","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b9b55ce470a5888cddd52169163ec9c190aa35c506ab95eb060352107d1681b9","sha256:25a862c87908461d132354c8b1de6772a9110e70ea0d47cb45d64fb0a977ffc4"],"state_sha256":"eb16428e746708b5e06bfddbf245cbde50b31ea50841ec0e65299e724f1a6149"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0gvzEgOR1GmMhoajnOJPMPneMkHMKzU/tZRpZp05GeVGDEVwIJ4FFG3ZmGiMvqqvtlSLdcY4M7w5yTfV9TRiAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T12:47:26.539331Z","bundle_sha256":"0a72cfb991d3503d654e72485285917517eb74ede940c0ab41a9d8dcadb2b410"}}