{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:CD5C5NNFW7ZRWTWIWN523NGGWE","short_pith_number":"pith:CD5C5NNF","canonical_record":{"source":{"id":"2403.11901","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-18T16:01:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9ae8d9fc100339976ca546b54d7369d25055e7465f93996db4bdc3fa0a3e619d","abstract_canon_sha256":"33c32af40a6c5dec098bde7664952244eab27025e44e6a0ef8efd44748e2ac4d"},"schema_version":"1.0"},"canonical_sha256":"10fa2eb5a5b7f31b4ec8b37badb4c6b1000076f4e871850729ec156849e3efd0","source":{"kind":"arxiv","id":"2403.11901","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.11901","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"arxiv_version","alias_value":"2403.11901v4","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.11901","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"pith_short_12","alias_value":"CD5C5NNFW7ZR","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"pith_short_16","alias_value":"CD5C5NNFW7ZRWTWI","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"pith_short_8","alias_value":"CD5C5NNF","created_at":"2026-07-05T08:57:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:CD5C5NNFW7ZRWTWIWN523NGGWE","target":"record","payload":{"canonical_record":{"source":{"id":"2403.11901","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-18T16:01:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9ae8d9fc100339976ca546b54d7369d25055e7465f93996db4bdc3fa0a3e619d","abstract_canon_sha256":"33c32af40a6c5dec098bde7664952244eab27025e44e6a0ef8efd44748e2ac4d"},"schema_version":"1.0"},"canonical_sha256":"10fa2eb5a5b7f31b4ec8b37badb4c6b1000076f4e871850729ec156849e3efd0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:57:55.570152Z","signature_b64":"SddxTQbnbIhs+zA4dNtOuMsbNdaq0RRPG9tZKOX6dy/VB9ehQeVzJOJf12EVzz6gNyicPQJn10XuHQ3ZXcyRCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"10fa2eb5a5b7f31b4ec8b37badb4c6b1000076f4e871850729ec156849e3efd0","last_reissued_at":"2026-07-05T08:57:55.569603Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:57:55.569603Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.11901","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:57:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gB7NfKcoByg8FIzGluqeMKX8b9bTr0CE1FE/mw1NUfoLjp7bk2vUyvIj0iOxE1tjYKDNi2WzZOy6SUxM3NleBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T16:44:26.591078Z"},"content_sha256":"4e957258eec8a34a0db24ff32bb01c9d96267832ccd7d376410a77e9e038e3fa","schema_version":"1.0","event_id":"sha256:4e957258eec8a34a0db24ff32bb01c9d96267832ccd7d376410a77e9e038e3fa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:CD5C5NNFW7ZRWTWIWN523NGGWE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Larimar: Large Language Models with Episodic Memory Control","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Aur\\'elie Lozano, Elliot Nelson, Georgios Kollias, Igor Melnyk, Ji\\v{r}\\'i, Navr\\'atil, Payel Das, Pin-Yu Chen, Sarath Swaminathan, Sihui Dai, Soham Dan, Subhajit Chaudhury, Vijil Chenthamarakshan","submitted_at":"2024-03-18T16:01:42Z","abstract_excerpt":"Efficient and accurate updating of knowledge stored in Large Language Models (LLMs) is one of the most pressing research challenges today. This paper presents Larimar - a novel, brain-inspired architecture for enhancing LLMs with a distributed episodic memory. Larimar's memory allows for dynamic, one-shot updates of knowledge without the need for computationally expensive re-training or fine-tuning. Experimental results on multiple fact editing benchmarks demonstrate that Larimar attains accuracy comparable to most competitive baselines, even in the challenging sequential editing setup, but al"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.11901","kind":"arxiv","version":4},"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/2403.11901/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":"2026-07-05T08:57:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xz0lB24v4R0npNA3r+oSbpdSqfEqk6/ZsI6SZ8O2+x0w6ramE7ktzTMQ+uvj8lGLQXrKTgpV142ggM09yVJNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T16:44:26.591469Z"},"content_sha256":"167e64292744c0cc0ec5cea764b3d3e678718079be9a489de46da1ae27beb5d4","schema_version":"1.0","event_id":"sha256:167e64292744c0cc0ec5cea764b3d3e678718079be9a489de46da1ae27beb5d4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CD5C5NNFW7ZRWTWIWN523NGGWE/bundle.json","state_url":"https://pith.science/pith/CD5C5NNFW7ZRWTWIWN523NGGWE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CD5C5NNFW7ZRWTWIWN523NGGWE/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":"2026-07-22T16:44:26Z","links":{"resolver":"https://pith.science/pith/CD5C5NNFW7ZRWTWIWN523NGGWE","bundle":"https://pith.science/pith/CD5C5NNFW7ZRWTWIWN523NGGWE/bundle.json","state":"https://pith.science/pith/CD5C5NNFW7ZRWTWIWN523NGGWE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CD5C5NNFW7ZRWTWIWN523NGGWE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CD5C5NNFW7ZRWTWIWN523NGGWE","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":"33c32af40a6c5dec098bde7664952244eab27025e44e6a0ef8efd44748e2ac4d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-18T16:01:42Z","title_canon_sha256":"9ae8d9fc100339976ca546b54d7369d25055e7465f93996db4bdc3fa0a3e619d"},"schema_version":"1.0","source":{"id":"2403.11901","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.11901","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"arxiv_version","alias_value":"2403.11901v4","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.11901","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"pith_short_12","alias_value":"CD5C5NNFW7ZR","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"pith_short_16","alias_value":"CD5C5NNFW7ZRWTWI","created_at":"2026-07-05T08:57:55Z"},{"alias_kind":"pith_short_8","alias_value":"CD5C5NNF","created_at":"2026-07-05T08:57:55Z"}],"graph_snapshots":[{"event_id":"sha256:167e64292744c0cc0ec5cea764b3d3e678718079be9a489de46da1ae27beb5d4","target":"graph","created_at":"2026-07-05T08:57:55Z","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/2403.11901/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Efficient and accurate updating of knowledge stored in Large Language Models (LLMs) is one of the most pressing research challenges today. This paper presents Larimar - a novel, brain-inspired architecture for enhancing LLMs with a distributed episodic memory. Larimar's memory allows for dynamic, one-shot updates of knowledge without the need for computationally expensive re-training or fine-tuning. Experimental results on multiple fact editing benchmarks demonstrate that Larimar attains accuracy comparable to most competitive baselines, even in the challenging sequential editing setup, but al","authors_text":"Aur\\'elie Lozano, Elliot Nelson, Georgios Kollias, Igor Melnyk, Ji\\v{r}\\'i, Navr\\'atil, Payel Das, Pin-Yu Chen, Sarath Swaminathan, Sihui Dai, Soham Dan, Subhajit Chaudhury, Vijil Chenthamarakshan","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-18T16:01:42Z","title":"Larimar: Large Language Models with Episodic Memory Control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.11901","kind":"arxiv","version":4},"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":"sha256:4e957258eec8a34a0db24ff32bb01c9d96267832ccd7d376410a77e9e038e3fa","target":"record","created_at":"2026-07-05T08:57:55Z","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":"33c32af40a6c5dec098bde7664952244eab27025e44e6a0ef8efd44748e2ac4d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-18T16:01:42Z","title_canon_sha256":"9ae8d9fc100339976ca546b54d7369d25055e7465f93996db4bdc3fa0a3e619d"},"schema_version":"1.0","source":{"id":"2403.11901","kind":"arxiv","version":4}},"canonical_sha256":"10fa2eb5a5b7f31b4ec8b37badb4c6b1000076f4e871850729ec156849e3efd0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"10fa2eb5a5b7f31b4ec8b37badb4c6b1000076f4e871850729ec156849e3efd0","first_computed_at":"2026-07-05T08:57:55.569603Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:57:55.569603Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SddxTQbnbIhs+zA4dNtOuMsbNdaq0RRPG9tZKOX6dy/VB9ehQeVzJOJf12EVzz6gNyicPQJn10XuHQ3ZXcyRCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:57:55.570152Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.11901","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e957258eec8a34a0db24ff32bb01c9d96267832ccd7d376410a77e9e038e3fa","sha256:167e64292744c0cc0ec5cea764b3d3e678718079be9a489de46da1ae27beb5d4"],"state_sha256":"2c2910dabb3976be16dcc1112b8e7628fba73c8c4a249d9de9383a495cdad411"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"axRbnyvf1AuectuDY88zn6koXyc30Le6AGiu29+VkH7GBSFe4ER6mHUdR5aNToJI5AwbkWdizbr4MaKdgOjmAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-22T16:44:26.593979Z","bundle_sha256":"e8641dcaeafd2c895c779f008bf489457d6619f0610e83b8bf80ec0574a8d092"}}