{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:TBGTC66KPCMFTHDGFSKIB3EAHC","short_pith_number":"pith:TBGTC66K","schema_version":"1.0","canonical_sha256":"984d317bca7898599c662c9480ec803883b99b6549c8db1ad787212a9723e626","source":{"kind":"arxiv","id":"2605.25680","version":1},"attestation_state":"computed","paper":{"title":"Simulating Human Memory with Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Brian Dillon, Michael Hu, Nicholas Tomlin, Qihan Wang, Tal Linzen","submitted_at":"2026-05-25T10:39:08Z","abstract_excerpt":"Language models are increasingly being deployed as user simulators, but their memory is far more reliable than that of real users. To measure this gap, we run a series of classic memory experiments from psychology on both humans and language models. Across tasks, we find that out-of-the-box language models exhibit better memory than humans, even when prompted to imitate human behavior. We then show that better prompting strategies and the use of a compactor can cause language models to forget content in a more human-like way. Using these methods, we show preliminary evidence that language mode"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.25680","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-25T10:39:08Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3da8e3e52fdd045465740229b6f8dc4ffa1aa229e404e6abb25fb3ec8dc9b50b","abstract_canon_sha256":"b90eef146fbdc2bd33d6519e8fa68f18f8f47be41e19ccff69d19b9485f3c550"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:04:49.866792Z","signature_b64":"+Z6eoHkiMRbTCBESF60Ku594Xq8zCtG1DBTMrvHowHOVIKS4ZJvN7DQqrDSb7Q60X2yGyAw8tiGQ8UHDxvMHBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"984d317bca7898599c662c9480ec803883b99b6549c8db1ad787212a9723e626","last_reissued_at":"2026-05-26T02:04:49.866221Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:04:49.866221Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Simulating Human Memory with Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Brian Dillon, Michael Hu, Nicholas Tomlin, Qihan Wang, Tal Linzen","submitted_at":"2026-05-25T10:39:08Z","abstract_excerpt":"Language models are increasingly being deployed as user simulators, but their memory is far more reliable than that of real users. To measure this gap, we run a series of classic memory experiments from psychology on both humans and language models. Across tasks, we find that out-of-the-box language models exhibit better memory than humans, even when prompted to imitate human behavior. We then show that better prompting strategies and the use of a compactor can cause language models to forget content in a more human-like way. Using these methods, we show preliminary evidence that language mode"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25680","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/2605.25680/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.25680","created_at":"2026-05-26T02:04:49.866298+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.25680v1","created_at":"2026-05-26T02:04:49.866298+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25680","created_at":"2026-05-26T02:04:49.866298+00:00"},{"alias_kind":"pith_short_12","alias_value":"TBGTC66KPCMF","created_at":"2026-05-26T02:04:49.866298+00:00"},{"alias_kind":"pith_short_16","alias_value":"TBGTC66KPCMFTHDG","created_at":"2026-05-26T02:04:49.866298+00:00"},{"alias_kind":"pith_short_8","alias_value":"TBGTC66K","created_at":"2026-05-26T02:04:49.866298+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC","json":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC.json","graph_json":"https://pith.science/api/pith-number/TBGTC66KPCMFTHDGFSKIB3EAHC/graph.json","events_json":"https://pith.science/api/pith-number/TBGTC66KPCMFTHDGFSKIB3EAHC/events.json","paper":"https://pith.science/paper/TBGTC66K"},"agent_actions":{"view_html":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC","download_json":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC.json","view_paper":"https://pith.science/paper/TBGTC66K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.25680&json=true","fetch_graph":"https://pith.science/api/pith-number/TBGTC66KPCMFTHDGFSKIB3EAHC/graph.json","fetch_events":"https://pith.science/api/pith-number/TBGTC66KPCMFTHDGFSKIB3EAHC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC/action/storage_attestation","attest_author":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC/action/author_attestation","sign_citation":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC/action/citation_signature","submit_replication":"https://pith.science/pith/TBGTC66KPCMFTHDGFSKIB3EAHC/action/replication_record"}},"created_at":"2026-05-26T02:04:49.866298+00:00","updated_at":"2026-05-26T02:04:49.866298+00:00"}