{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:YHOCY2TOOFS4RXNGD7TUWEJH26","short_pith_number":"pith:YHOCY2TO","canonical_record":{"source":{"id":"2602.13466","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T21:16:10Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"07fe29e8ecd80223620a315620ca50f0cdb4891f6ada79970bab346da645c329","abstract_canon_sha256":"78b755192d711a61a9b7de016a3b8e283e69639995952bfb52938b387ec2d8ca"},"schema_version":"1.0"},"canonical_sha256":"c1dc2c6a6e7165c8dda61fe74b1127d79eed98882225f44f777d417ce1e243ef","source":{"kind":"arxiv","id":"2602.13466","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.13466","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"arxiv_version","alias_value":"2602.13466v2","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.13466","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"pith_short_12","alias_value":"YHOCY2TOOFS4","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"pith_short_16","alias_value":"YHOCY2TOOFS4RXNG","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"pith_short_8","alias_value":"YHOCY2TO","created_at":"2026-05-20T01:05:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:YHOCY2TOOFS4RXNGD7TUWEJH26","target":"record","payload":{"canonical_record":{"source":{"id":"2602.13466","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T21:16:10Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"07fe29e8ecd80223620a315620ca50f0cdb4891f6ada79970bab346da645c329","abstract_canon_sha256":"78b755192d711a61a9b7de016a3b8e283e69639995952bfb52938b387ec2d8ca"},"schema_version":"1.0"},"canonical_sha256":"c1dc2c6a6e7165c8dda61fe74b1127d79eed98882225f44f777d417ce1e243ef","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:05:09.172746Z","signature_b64":"RFVzqrJNJRec4IETWwHeORtTIUZh+klKCMIqFn7NpSYfkD3RCXaMbLog8JjLIUTyCv7V4l7/dLG9eFowXT4kCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c1dc2c6a6e7165c8dda61fe74b1127d79eed98882225f44f777d417ce1e243ef","last_reissued_at":"2026-05-20T01:05:09.171801Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:05:09.171801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.13466","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":"2026-05-20T01:05:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"49eQO0bXoR09Qt1u9qIbNROgJq0SQZlurtzJsZVo1oamw4Qv+awL/5WJpbLKHjyHZna2FNYuIunqllvzuLgXBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T01:25:48.354481Z"},"content_sha256":"82b34d62c1ca852c0c683e1d3973b12feeace013fff5ca5d1b6a338e15a25e1c","schema_version":"1.0","event_id":"sha256:82b34d62c1ca852c0c683e1d3973b12feeace013fff5ca5d1b6a338e15a25e1c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:YHOCY2TOOFS4RXNGD7TUWEJH26","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Language Model Memory and Memory Models for Language","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Benjamin L. Badger","submitted_at":"2026-02-13T21:16:10Z","abstract_excerpt":"The ability of machine learning models to store input information in hidden layer vector embeddings, analogous to the concept of `memory', is widely employed but not well characterized. We find that language model embeddings typically contain relatively little input information regardless of data and compute scale during training. In contrast, embeddings from autoencoders trained for input regeneration are capable of nearly perfect memory formation. The substitution of memory embeddings for token sequences leads to substantial computational efficiencies, motivating the introduction of a parall"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.13466","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/2602.13466/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":"2026-05-20T01:05:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5Pvl17y9XrO0WJ5zdO+XJsZeeoXAjt/zU8IR0jKCLhhIul02aPSX8DQpnS2p7qfotwL9C3UQkgbgCP9zs0mdCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T01:25:48.355257Z"},"content_sha256":"6ef3eb830dcf43df1d2896055adf837cdb93a0a99bce67aa9681937c754e99ec","schema_version":"1.0","event_id":"sha256:6ef3eb830dcf43df1d2896055adf837cdb93a0a99bce67aa9681937c754e99ec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YHOCY2TOOFS4RXNGD7TUWEJH26/bundle.json","state_url":"https://pith.science/pith/YHOCY2TOOFS4RXNGD7TUWEJH26/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YHOCY2TOOFS4RXNGD7TUWEJH26/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":"2026-06-10T01:25:48Z","links":{"resolver":"https://pith.science/pith/YHOCY2TOOFS4RXNGD7TUWEJH26","bundle":"https://pith.science/pith/YHOCY2TOOFS4RXNGD7TUWEJH26/bundle.json","state":"https://pith.science/pith/YHOCY2TOOFS4RXNGD7TUWEJH26/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YHOCY2TOOFS4RXNGD7TUWEJH26/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:YHOCY2TOOFS4RXNGD7TUWEJH26","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":"78b755192d711a61a9b7de016a3b8e283e69639995952bfb52938b387ec2d8ca","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T21:16:10Z","title_canon_sha256":"07fe29e8ecd80223620a315620ca50f0cdb4891f6ada79970bab346da645c329"},"schema_version":"1.0","source":{"id":"2602.13466","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.13466","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"arxiv_version","alias_value":"2602.13466v2","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.13466","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"pith_short_12","alias_value":"YHOCY2TOOFS4","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"pith_short_16","alias_value":"YHOCY2TOOFS4RXNG","created_at":"2026-05-20T01:05:09Z"},{"alias_kind":"pith_short_8","alias_value":"YHOCY2TO","created_at":"2026-05-20T01:05:09Z"}],"graph_snapshots":[{"event_id":"sha256:6ef3eb830dcf43df1d2896055adf837cdb93a0a99bce67aa9681937c754e99ec","target":"graph","created_at":"2026-05-20T01:05:09Z","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/2602.13466/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The ability of machine learning models to store input information in hidden layer vector embeddings, analogous to the concept of `memory', is widely employed but not well characterized. We find that language model embeddings typically contain relatively little input information regardless of data and compute scale during training. In contrast, embeddings from autoencoders trained for input regeneration are capable of nearly perfect memory formation. The substitution of memory embeddings for token sequences leads to substantial computational efficiencies, motivating the introduction of a parall","authors_text":"Benjamin L. Badger","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T21:16:10Z","title":"Language Model Memory and Memory Models for Language"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.13466","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":"sha256:82b34d62c1ca852c0c683e1d3973b12feeace013fff5ca5d1b6a338e15a25e1c","target":"record","created_at":"2026-05-20T01:05:09Z","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":"78b755192d711a61a9b7de016a3b8e283e69639995952bfb52938b387ec2d8ca","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-02-13T21:16:10Z","title_canon_sha256":"07fe29e8ecd80223620a315620ca50f0cdb4891f6ada79970bab346da645c329"},"schema_version":"1.0","source":{"id":"2602.13466","kind":"arxiv","version":2}},"canonical_sha256":"c1dc2c6a6e7165c8dda61fe74b1127d79eed98882225f44f777d417ce1e243ef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c1dc2c6a6e7165c8dda61fe74b1127d79eed98882225f44f777d417ce1e243ef","first_computed_at":"2026-05-20T01:05:09.171801Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T01:05:09.171801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RFVzqrJNJRec4IETWwHeORtTIUZh+klKCMIqFn7NpSYfkD3RCXaMbLog8JjLIUTyCv7V4l7/dLG9eFowXT4kCw==","signature_status":"signed_v1","signed_at":"2026-05-20T01:05:09.172746Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.13466","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82b34d62c1ca852c0c683e1d3973b12feeace013fff5ca5d1b6a338e15a25e1c","sha256:6ef3eb830dcf43df1d2896055adf837cdb93a0a99bce67aa9681937c754e99ec"],"state_sha256":"7b090da705f0bcca33fd1c0f6c3290c87c086b1a6d6c93eba1e2116532ff0486"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KEWVZkQ5/AgIGUDFKMI1d9JjPXSjg7V5fOP7Yuh41seUHwwuE3UcAy4ebjLPVZOF7EeC6Q+A/NQEL2OE3Q4UCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T01:25:48.360038Z","bundle_sha256":"f9770a7699def81a33da5fdea8260c1a8278c6a6ae8a93e847d4204e527a8e9c"}}