{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4XHUVYNHMYHAKFH73GJOBCYVHD","short_pith_number":"pith:4XHUVYNH","canonical_record":{"source":{"id":"2507.08686","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-11T15:37:24Z","cross_cats_sorted":[],"title_canon_sha256":"55dbb279d85338b1c127b24c2eec2d823ccde4b36b6dd426339283eb0b0220cd","abstract_canon_sha256":"0763c8d870b572ed9e7f380890af76a1a963a8036ff352e4d2352b4fe91c5437"},"schema_version":"1.0"},"canonical_sha256":"e5cf4ae1a7660e0514ffd992e08b1538f1d229519628ab19558e1d81b81b3021","source":{"kind":"arxiv","id":"2507.08686","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.08686","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"arxiv_version","alias_value":"2507.08686v1","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08686","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"pith_short_12","alias_value":"4XHUVYNHMYHA","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"pith_short_16","alias_value":"4XHUVYNHMYHAKFH7","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"pith_short_8","alias_value":"4XHUVYNH","created_at":"2026-07-05T11:35:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4XHUVYNHMYHAKFH73GJOBCYVHD","target":"record","payload":{"canonical_record":{"source":{"id":"2507.08686","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-11T15:37:24Z","cross_cats_sorted":[],"title_canon_sha256":"55dbb279d85338b1c127b24c2eec2d823ccde4b36b6dd426339283eb0b0220cd","abstract_canon_sha256":"0763c8d870b572ed9e7f380890af76a1a963a8036ff352e4d2352b4fe91c5437"},"schema_version":"1.0"},"canonical_sha256":"e5cf4ae1a7660e0514ffd992e08b1538f1d229519628ab19558e1d81b81b3021","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:35:44.847335Z","signature_b64":"1UtfAA2+nOIKV0lUdE5FgmeRYvHNGNWRRkW21dbYdUKhx5tezkiO0Bmn9ozyq0bSyTWRVnrBQChU5u0iX2ezAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5cf4ae1a7660e0514ffd992e08b1538f1d229519628ab19558e1d81b81b3021","last_reissued_at":"2026-07-05T11:35:44.846810Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:35:44.846810Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.08686","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":"2026-07-05T11:35:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c12u+4xvrfuaLW0Y2zU8PTWVU1tXtZ8a7fL9BO2HZonIWgFOm+As/hHeTKWud/+4Ca50MXYQFWTNk9VGx7gbBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:49:48.385584Z"},"content_sha256":"46d7568f91727df712b91de4bf84ccc86237c3949b643225a55a4f6fec537fb9","schema_version":"1.0","event_id":"sha256:46d7568f91727df712b91de4bf84ccc86237c3949b643225a55a4f6fec537fb9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4XHUVYNHMYHAKFH73GJOBCYVHD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Daphna Weinshall, Eli Corn, Uri Stern","submitted_at":"2025-07-11T15:37:24Z","abstract_excerpt":"Overfitting in deep neural networks occurs less frequently than expected. This is a puzzling observation, as theory predicts that greater model capacity should eventually lead to overfitting -- yet this is rarely seen in practice. But what if overfitting does occur, not globally, but in specific sub-regions of the data space? In this work, we introduce a novel score that measures the forgetting rate of deep models on validation data, capturing what we term local overfitting: a performance degradation confined to certain regions of the input space. We demonstrate that local overfitting can aris"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08686","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/2507.08686/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":"2026-07-05T11:35:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"umiq+q7S0jGbXTqaUCeBo7bIxgp+GdWEHnW0Z8PzOGON5o81CzsbIt5fojCmZBKVNJD3uma9LnzjCKMnthr3DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T23:49:48.386126Z"},"content_sha256":"332feafd58051ed5306a29a24ecbbb272afff71c82c97a083f12be6dcb70a48b","schema_version":"1.0","event_id":"sha256:332feafd58051ed5306a29a24ecbbb272afff71c82c97a083f12be6dcb70a48b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4XHUVYNHMYHAKFH73GJOBCYVHD/bundle.json","state_url":"https://pith.science/pith/4XHUVYNHMYHAKFH73GJOBCYVHD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4XHUVYNHMYHAKFH73GJOBCYVHD/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":"2026-08-07T23:49:48Z","links":{"resolver":"https://pith.science/pith/4XHUVYNHMYHAKFH73GJOBCYVHD","bundle":"https://pith.science/pith/4XHUVYNHMYHAKFH73GJOBCYVHD/bundle.json","state":"https://pith.science/pith/4XHUVYNHMYHAKFH73GJOBCYVHD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4XHUVYNHMYHAKFH73GJOBCYVHD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4XHUVYNHMYHAKFH73GJOBCYVHD","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":"0763c8d870b572ed9e7f380890af76a1a963a8036ff352e4d2352b4fe91c5437","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-11T15:37:24Z","title_canon_sha256":"55dbb279d85338b1c127b24c2eec2d823ccde4b36b6dd426339283eb0b0220cd"},"schema_version":"1.0","source":{"id":"2507.08686","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.08686","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"arxiv_version","alias_value":"2507.08686v1","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08686","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"pith_short_12","alias_value":"4XHUVYNHMYHA","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"pith_short_16","alias_value":"4XHUVYNHMYHAKFH7","created_at":"2026-07-05T11:35:44Z"},{"alias_kind":"pith_short_8","alias_value":"4XHUVYNH","created_at":"2026-07-05T11:35:44Z"}],"graph_snapshots":[{"event_id":"sha256:332feafd58051ed5306a29a24ecbbb272afff71c82c97a083f12be6dcb70a48b","target":"graph","created_at":"2026-07-05T11:35:44Z","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/2507.08686/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Overfitting in deep neural networks occurs less frequently than expected. This is a puzzling observation, as theory predicts that greater model capacity should eventually lead to overfitting -- yet this is rarely seen in practice. But what if overfitting does occur, not globally, but in specific sub-regions of the data space? In this work, we introduce a novel score that measures the forgetting rate of deep models on validation data, capturing what we term local overfitting: a performance degradation confined to certain regions of the input space. We demonstrate that local overfitting can aris","authors_text":"Daphna Weinshall, Eli Corn, Uri Stern","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-11T15:37:24Z","title":"Forget Me Not: Fighting Local Overfitting with Knowledge Fusion and Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08686","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":"sha256:46d7568f91727df712b91de4bf84ccc86237c3949b643225a55a4f6fec537fb9","target":"record","created_at":"2026-07-05T11:35:44Z","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":"0763c8d870b572ed9e7f380890af76a1a963a8036ff352e4d2352b4fe91c5437","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-11T15:37:24Z","title_canon_sha256":"55dbb279d85338b1c127b24c2eec2d823ccde4b36b6dd426339283eb0b0220cd"},"schema_version":"1.0","source":{"id":"2507.08686","kind":"arxiv","version":1}},"canonical_sha256":"e5cf4ae1a7660e0514ffd992e08b1538f1d229519628ab19558e1d81b81b3021","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e5cf4ae1a7660e0514ffd992e08b1538f1d229519628ab19558e1d81b81b3021","first_computed_at":"2026-07-05T11:35:44.846810Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:35:44.846810Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1UtfAA2+nOIKV0lUdE5FgmeRYvHNGNWRRkW21dbYdUKhx5tezkiO0Bmn9ozyq0bSyTWRVnrBQChU5u0iX2ezAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:35:44.847335Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.08686","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46d7568f91727df712b91de4bf84ccc86237c3949b643225a55a4f6fec537fb9","sha256:332feafd58051ed5306a29a24ecbbb272afff71c82c97a083f12be6dcb70a48b"],"state_sha256":"387c4dda377673377772f7f331b27b00c0a1b99c2b23a265fa11fd780255bb64"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B2A5f0yxnhclYkuL8Qi6HsW3mJVVy2sT8F9R/hANJhBRjQi5sDCfD0nwq+VL53fSt1ZTCdlY4VrT5WVNvU9qDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T23:49:48.391651Z","bundle_sha256":"12955102c71f9d861dd322a5f8cdc6c2a8c1a80e29949dc9edba84634765e178"}}