{"as_of":"2026-08-05T11:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5c3ca1d2ab625d4a0560a3020ac8f1e25e2f8e52c72cbca2dffc72dc858926fe","coverage":[{"denominator":36,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":36,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-10T08:11:11.566370Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.08393/citation-record","integrity":"/paper/2607.08393/integrity","json":"/paper/2607.08393/citation-record.json","paper":"/paper/2607.08393"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.361495Z","title":null,"venue":null,"work_id":"5ef00664-bf92-4f66-98d2-3912d0aed251","year":1998},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:cd53ed4c8f2c5efbe344c3f075dee74732a1a0cb0ac58f772cc22396089444d5","observation_id":"41d3cf17-19a8-4434-ab71-04c903c78707","resolution":{"observed_at":"2026-07-10T08:16:59.362636Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.365206Z","title":"Understanding intermediate layers using linear classifier probes","venue":null,"work_id":"29f11975-3149-4341-b7a2-cd7a3f1c0fba","year":2017},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:809ef775b21a50bbfae161d6f3da181ec0c423ab81d102a7b0077409f422f5c9","observation_id":"fff37db9-4bde-4924-88be-5b4230fb18f3","resolution":{"observed_at":"2026-07-10T08:16:59.366561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.374648Z","title":"Physics of language models: Part 3.3, knowledge capacity scaling laws","venue":null,"work_id":"bbcc4b45-81fc-4ace-b22e-763b6d4f8abd","year":null},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:163420dd9e4d74e6562665cb14f57e1fc11c653412a230c635274ddb01b70cb2","observation_id":"0922f8d9-5744-454f-afbe-ab9f58d7ae37","resolution":{"observed_at":"2026-07-10T08:16:59.375760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1162/coli","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Cocarascu, F","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","work_id":"816c1e36-4060-4ea8-8f0b-b8c0efaf2db9","year":2022},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:1967b43c6049864a9078d032d0403b749d4ffc36d9b56bf20cc512e90175b630","observation_id":"3b9f4fc1-9cbc-4588-98ed-a333de0a1669","resolution":{"observed_at":"2026-07-10T08:16:58.534665Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.349994Z","title":"a is b” fail to learn “b is a","venue":null,"work_id":"8aeae470-dc69-4a06-a4a9-80f0d3aade56","year":null},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:74ee08d00f9fb09782b357fc2a01ba78c877d820ee766a65f743848f25e42651","observation_id":"c0dbd0c1-0629-49b8-95a9-619bfa9dd793","resolution":{"observed_at":"2026-07-10T08:16:59.351180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.367211Z","title":"Hopping too late: Exploring the limitations of large language models on multi-hop queries","venue":null,"work_id":"87ac1a91-d60b-4bf1-bf75-ac3ed9e79b0d","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:db4d119455a5cde337e9d116acb32f9296810f98514881d7b287c22b1b8d2b52","observation_id":"4c7aabc0-32fe-47af-9944-ee28fcff9154","resolution":{"observed_at":"2026-07-10T08:16:59.368429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.377843Z","title":"Evaluating the ripple effects of knowledge editing in language models","venue":null,"work_id":"fed634dd-518c-4a7a-b7ae-99e9473881fa","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:1fe0be3af611072f04da839a4476b2e2af7e4346aeb0d1a2c7852a9d4a3c6d5f","observation_id":"cf46e937-ead8-4d10-9590-cbcc9e7aff1e","resolution":{"observed_at":"2026-07-10T08:16:59.379209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2022.acl-long.581","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi: 10.18653/v1/2022.acl-long.581","venue":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","work_id":"e08c111e-12b3-4697-bdbb-3b107a7d76e3","year":2022},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:bfd253b75c6c1d5ee6c1b8eff5ef685dc7c9eac9c6e8de9ab192ee32d604b78f","observation_id":"8e1868b6-e4c8-42c2-9af0-9bdc298fa66c","resolution":{"observed_at":"2026-07-10T08:16:58.521192Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-18T08:51:26.684074+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-18T08:51:26.684074+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.370665Z","title":"Scaling and evaluating sparse autoencoders","venue":null,"work_id":"94f1ac22-9534-430a-bf8a-e2676e2d94c0","year":2025},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:38226ef76b8e0643c4f268d9d3362c6d5201d0e7f27e018d2d9bdcdb4942d946","observation_id":"35980cfc-7680-44dd-ba60-3c823b59802e","resolution":{"observed_at":"2026-07-10T08:16:59.372094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02950","last_updated":"2025-03-04T03:10:09Z","snapshot_observed_at":"2026-08-04T06:23:17.853986Z","submitted_at":"2025-01-06T11:46:40Z","title":"Key-value memory in the brain","version":2},"cited_work":{"arxiv_id":"2501.02950","doi":"10.48550/arxiv.2501.02950","metadata_source":"pith","pith_arxiv_id":"2501.02950","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Key-value memory in the brain","venue":"q-bio.NC","work_id":"62dd20d3-f4c2-4888-83d2-9cb687fe7fb5","year":2025},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"cited_paper":"/paper/2501.02950","citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:6ea594481d7da823539b272917d0d393813e3334fd10cc4f965717af17c958b3","observation_id":"ff7a7c0f-2342-4446-8fce-b5f3a6304966","resolution":{"observed_at":"2026-07-10T08:16:58.541359Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-18T08:51:26.908338+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-18T08:51:26.908338+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.392285Z","title":"Dissecting recall of factual associations in auto-regressive language models","venue":null,"work_id":"8f35376d-dcd3-4c75-b30d-60393724e0c1","year":2023},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:df50fe4164db1917ecf1680b8f0acce5529a6df415e042725ba2f868c4a0e0fd","observation_id":"321608e5-9b84-4e40-a544-2ab2565c6454","resolution":{"observed_at":"2026-07-10T08:16:59.393521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.394038Z","title":"Patchscopes: A unifying framework for inspecting hidden representations of language models","venue":null,"work_id":"c3161386-17d6-4d85-8d48-33b008a6165d","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:f021ae0a49a5b1622d6017ebe14a5f347851900fc9a3588d34e14e1ab9c38c52","observation_id":"6e67a8b4-9c0e-47aa-90f1-425f48988141","resolution":{"observed_at":"2026-07-10T08:16:59.395388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.390094Z","title":"Model editing at scale leads to gradual and catastrophic forgetting","venue":null,"work_id":"0117773a-a367-4b24-a18c-f71e823106d2","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:755f7f588319e3b4063cb02cf73391704f91474f3c651ad360ae06a60d0c5bf0","observation_id":"1862aa5d-2902-49b2-9a8e-538a223591c3","resolution":{"observed_at":"2026-07-10T08:16:59.391591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.388215Z","title":"Sparse autoencoders find highly interpretable features in language models","venue":null,"work_id":"4f2ab120-80c6-4ec7-b628-a8151d3615d9","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:66da4b055643628085844347e4d3d0e6317f518fb384ab61df6f13cf979db89c","observation_id":"0bfee5fe-cf15-43da-bac3-f45fda8aaeeb","resolution":{"observed_at":"2026-07-10T08:16:59.389609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2506.21551","doi":"10.48550/arxiv.2506.21551","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Where to find grokking in llm pretraining? monitor memorization-to-generalization without test.arXiv preprint arXiv:2506.21551, 2025k","venue":"arXiv (Cornell University)","work_id":"ecc45094-aa4e-42e2-b4dc-55b29a48181b","year":2025},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:ac1c3f27f3134da4c2d13dcd796647a1d6fe95a4ad2c8fc69c81289404e9f19c","observation_id":"e8b1ce0f-bdfb-4212-90e2-029a15c5bc11","resolution":{"observed_at":"2026-07-10T08:16:58.525175Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-18T08:51:27.128307+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-18T08:51:27.128307+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.395941Z","title":"Michaud, Max Tegmark, and Mike Williams","venue":null,"work_id":"2b64797d-c84f-4f6f-97f3-5baf2eba4c72","year":2022},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:69907c61e643749e6a6232ddd682df0955470176b6142aa28d9606ae10f1ae59","observation_id":"19395955-3524-4b73-953a-373ff4516a65","resolution":{"observed_at":"2026-07-10T08:16:59.397085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.386263Z","title":"Mass-editing memory in a transformer","venue":null,"work_id":"fc681c4c-48df-4de2-80a4-31e173dc762d","year":null},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:6d3f535e02c9ac32ebf70862b3023380b3c89ab96c4bbbb763dff2739f1e047d","observation_id":"23dc7490-8bd7-4e9c-a2ec-1fa6198d392e","resolution":{"observed_at":"2026-07-10T08:16:59.387522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.381884Z","title":"Locating and editing factual associations in GPT","venue":null,"work_id":"795139ec-a8c9-4d04-92d1-472133120ed0","year":2022},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:cb850ca648b750ca0ade437976470483d85ef1d5d8464ce875584f3db59a83a3","observation_id":"c19347d2-f0ff-43d8-878a-eb1f3bf34b6d","resolution":{"observed_at":"2026-07-10T08:16:59.383143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.24832","last_updated":"2025-06-18T15:27:03Z","snapshot_observed_at":"2026-08-01T21:38:41.511664Z","submitted_at":"2025-05-30T17:34:03Z","title":"How much do language models memorize?","version":3},"cited_work":{"arxiv_id":"2505.24832","doi":"10.48550/arxiv.2505.24832","metadata_source":"pith","pith_arxiv_id":"2505.24832","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Morris, Chawin Sitawarin, Chuan Guo, Narine Kokhlikyan, G","venue":"cs.CL","work_id":"3fce89d3-ba91-45d3-b552-814d74439058","year":2025},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"cited_paper":"/paper/2505.24832","citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:bbf85786d9c33b714e5cd99e538743a13c2702a4b029aaf135119f6ae285ee9f","observation_id":"996e8311-1e2e-4906-bc61-b1a41a5ca82e","resolution":{"observed_at":"2026-07-10T08:16:58.784744Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.383717Z","title":"Progress measures for grokking via mechanistic interpretability","venue":null,"work_id":"735097a4-22f5-4b90-9251-955709f1b926","year":2023},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:cc137a6c4c5fec1590a3ac4ea3c1e5a76e5e70a0904cb8fa9021cf2b8c43d470","observation_id":"de209e04-5640-4cdb-9367-bb3ce7211807","resolution":{"observed_at":"2026-07-10T08:16:59.385015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.397600Z","title":"interpreting GPT : the logit lens, August 2020","venue":null,"work_id":"0ba9cbb6-f72f-4a88-974b-e7f89064a3ed","year":2020},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:7fb599ea5b05236553fe510591767b9ff2b1db7963dc3162a7d6d7398ef849bb","observation_id":"ffa22f44-a852-4937-bbef-d94487c349c6","resolution":{"observed_at":"2026-07-10T08:16:59.398759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.11895","last_updated":"2022-09-24T00:43:19Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-09-24T00:43:19Z","title":"In-context Learning and Induction Heads","version":1},"cited_work":{"arxiv_id":"2209.11895","doi":"10.1145/3411763.3451760","metadata_source":"pith","pith_arxiv_id":"2209.11895","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"In-context Learning and Induction Heads","venue":"cs.LG","work_id":"db2b0911-2758-4a2a-99dc-15b14b91bd5e","year":2022},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"cited_paper":"/paper/2209.11895","citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:d4704f36ffe1e6fcc98b1d1a1d75fd5aaedb0e12ca1900b84007a2f2194617c1","observation_id":"0986e177-7118-4831-addd-39a99b2d85c6","resolution":{"observed_at":"2026-07-10T08:16:58.532280Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-23T02:23:10.795052+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T02:23:10.795052+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.379930Z","title":"Fine-tuning or retrieval? comparing knowledge injection in llms","venue":null,"work_id":"6501f446-f42f-450b-a6fe-c69ea34d1d95","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:07877ba39e79b7a51cd1a8efa1fd622a02bf839d65e2ac3e9dd0eb476b1d521a","observation_id":"7975282f-011f-40af-91ba-f1f09a2aa38c","resolution":{"observed_at":"2026-07-10T08:16:59.381236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"0793.2023","doi":"10.1109/iccvw60793.2023.00049","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Burbi, A","venue":null,"work_id":"2c9c5044-e4db-4f53-9693-8e265b920f71","year":2023},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:41a2a2418b2dfc35e1f84b2f1cf9ccd7d631fad8bec80975aabc97ab13b06daa","observation_id":"8f6d7fd8-3025-484e-bc32-c7128b553e60","resolution":{"observed_at":"2026-07-10T08:16:58.538181Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.368980Z","title":"The linear representation hypothesis and the geometry of large language models","venue":null,"work_id":"9d1d4ff3-0659-4e86-b64c-4052859e3c96","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:d187f4812368f575fbafc4d7dbe678a9ef03bd20197323b498efad92e932c2ee","observation_id":"39597c06-0e70-4d01-9d07-b368ea8226fa","resolution":{"observed_at":"2026-07-10T08:16:59.370107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.02177","last_updated":"2022-01-06T18:43:37Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-01-06T18:43:37Z","title":"Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets","version":1},"cited_work":{"arxiv_id":"2201.02177","doi":"10.1109/tit.2005.851722","metadata_source":"pith","pith_arxiv_id":"2201.02177","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets","venue":"cs.LG","work_id":"a3c30ead-1625-4c18-a9c1-e4928dcd0da6","year":2022},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"cited_paper":"/paper/2201.02177","citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:5fdee213b78b016e9f05905dc18bb99745acc3c826e608a6e13c62e1a6960c85","observation_id":"83343dee-8a08-4884-bf0a-d32f54f852fd","resolution":{"observed_at":"2026-07-10T08:16:58.779339Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.372909Z","title":"Fine-tuning enhances existing mechanisms: A case study on entity tracking","venue":null,"work_id":"856982e1-997f-4710-a05a-c333fd27afe6","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:1e2ccd5116bf290a05c5c93af4132ed02ca21f209056d4e63945fe2dd6bfcafc","observation_id":"16beef6b-5832-4a96-9f52-d4534bf35362","resolution":{"observed_at":"2026-07-10T08:16:59.374083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.376342Z","title":"Fine tuning vs","venue":null,"work_id":"983aeb94-07ea-4a19-8c21-5fa801e029f9","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:8a990d4b40b361ba7ebce83dab0b5b445c4c02c8d1f0ecef60294517c6b436f8","observation_id":"411fbf06-46bd-433e-b510-574d87d26c55","resolution":{"observed_at":"2026-07-10T08:16:59.377339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.359565Z","title":"Grokking of implicit reasoning in transformers: A mechanistic journey to the edge of generalization","venue":null,"work_id":"46a7c8dc-b077-48de-b246-4b147f4c9850","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:2f50ba1fbe48ebfb897bfc6cdbbcf0a1e2097c0ec3be40f42e918fb7c7efa7e3","observation_id":"fd9aeb94-0d09-4060-aa1e-3312f206b030","resolution":{"observed_at":"2026-07-10T08:16:59.360841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.363165Z","title":"Interpretability in the wild: a circuit for indirect object identification in GPT-2 small","venue":null,"work_id":"64a26e48-0364-40ac-9bbd-e1ae34805e56","year":2023},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:dad1bc5c2c78af255c621ff9a36c2a23fac932afb12f5415bf98ebd96f30c397","observation_id":"b08b8d1d-48da-4d85-be31-711c1973ec25","resolution":{"observed_at":"2026-07-10T08:16:59.364504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2024.acl-long.820","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi: 10.18653/v1/2024.acl-long.820","venue":null,"work_id":"fff0e589-45ad-4f4b-b760-63da64d82e24","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:db0e6205c8ffe8bac4c4938aad75015c6a08e2da0a31f74f2580c19c7963bbb7","observation_id":"592092ef-e7b6-4bbb-aeba-64c1e2568c39","resolution":{"observed_at":"2026-07-10T08:16:58.528926Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-18T08:51:27.841911+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-18T08:51:27.841911+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.355676Z","title":"Ioannidis, Karthik Subbian, James Y","venue":null,"work_id":"5db675d3-ea09-42e9-8606-bbf43077167d","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:e386bd1fbbeee011a6b8201895d060b6120c0df01db4975d9be086e5398ebbdb","observation_id":"338ffd4c-10eb-4fd2-9082-5d73c3db0274","resolution":{"observed_at":"2026-07-10T08:16:59.356928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.357479Z","title":"Knowledge circuits in pretrained transformers","venue":null,"work_id":"78b645a5-c386-438d-b3c6-e354b61434a2","year":2024},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:4b13e3aa520ff4805ab3d13c56e96ec8fd2189d8a38d5945d0b8c06d42312ab1","observation_id":"00a225be-897a-462d-baaf-9213f07ba4d2","resolution":{"observed_at":"2026-07-10T08:16:59.358871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2503.16356","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:58.780682Z","title":"Cake: Circuit-aware editing enables generalizable knowledge learners","venue":null,"work_id":"2e3dea23-42c3-4792-ae65-6ef4e8264ebf","year":2025},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:c9c9a0ac1d6e6b72ad587d44af8c1e203c523cb1e3f33cda098fe30b2c145d63","observation_id":"d0ccca99-2165-4800-9a68-a6c009df59fb","resolution":{"observed_at":"2026-07-10T08:16:58.782324Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.351806Z","title":"Towards best practices of activation patching in language models: Metrics and methods","venue":null,"work_id":"d5a90de9-0507-4b7b-b761-1806ab60263c","year":null},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:e044025ef1feed68ac51a0e20dac2fd747e17d38818b8796459209ebf671504f","observation_id":"5fc7136f-9f42-45b7-bc50-037e2d72611d","resolution":{"observed_at":"2026-07-10T08:16:59.353133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T08:16:59.353659Z","title":"Mquake: Assessing knowledge editing in language models via multi-hop questions","venue":null,"work_id":"8320fefa-3e2b-42bb-9e89-00f5a3eaf446","year":2023},"citing_paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-07-10T08:11:11.566370Z"},"links":{"citing_paper":"/paper/2607.08393"},"observation_digest":"sha256:8b738b3b6c341cb9e74e0a9847bdde0513461c45eb803a6543e78b2d51b0db1a","observation_id":"4169bc55-a310-4e20-9b64-9bfca67edadb","resolution":{"observed_at":"2026-07-10T08:16:59.354999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.08393","last_updated":"2026-07-09T12:17:28Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-31T10:30:57.767958Z","submitted_at":"2026-07-09T12:17:28Z","title":"Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning"},"reference_resolution":{"displayed":36,"state_counts":{"malformed_identifier":1,"metadata_mismatch":6,"parse_uncertain":0,"unresolved":1,"verified_exact":3,"verified_fuzzy":25},"total_outbound_references":36},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.08393."}