{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:LVEOBLVNVDJSRZVH5QMRJFSNTN","short_pith_number":"pith:LVEOBLVN","canonical_record":{"source":{"id":"2605.03804","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-05T14:30:30Z","cross_cats_sorted":[],"title_canon_sha256":"7c77391bb2ede1aad0d1f6a2f3900b9fca862bc02bb10bbc2a7f73379a6b99a0","abstract_canon_sha256":"c9e60c6f3912befc56b2b39411b9519674c7df04953bc4b1469241bc0e50b30e"},"schema_version":"1.0"},"canonical_sha256":"5d48e0aeada8d328e6a7ec1914964d9b5a69169d60ac1ef1d9d2529ad90acf68","source":{"kind":"arxiv","id":"2605.03804","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.03804","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"arxiv_version","alias_value":"2605.03804v2","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.03804","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"pith_short_12","alias_value":"LVEOBLVNVDJS","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"pith_short_16","alias_value":"LVEOBLVNVDJSRZVH","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"pith_short_8","alias_value":"LVEOBLVN","created_at":"2026-05-26T02:04:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:LVEOBLVNVDJSRZVH5QMRJFSNTN","target":"record","payload":{"canonical_record":{"source":{"id":"2605.03804","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-05T14:30:30Z","cross_cats_sorted":[],"title_canon_sha256":"7c77391bb2ede1aad0d1f6a2f3900b9fca862bc02bb10bbc2a7f73379a6b99a0","abstract_canon_sha256":"c9e60c6f3912befc56b2b39411b9519674c7df04953bc4b1469241bc0e50b30e"},"schema_version":"1.0"},"canonical_sha256":"5d48e0aeada8d328e6a7ec1914964d9b5a69169d60ac1ef1d9d2529ad90acf68","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:04:11.968135Z","signature_b64":"s6Z1O2OAH8x4p4MoBzkqJfAu9SGPhV6GJlIfABqcJd6R1G239nJusOWEo+bP5ALDYQIv33BpHJ+3nKImF4tGCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d48e0aeada8d328e6a7ec1914964d9b5a69169d60ac1ef1d9d2529ad90acf68","last_reissued_at":"2026-05-26T02:04:11.967474Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:04:11.967474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.03804","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":"2026-05-26T02:04:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xMTgPCY1dOW+Yc7T8vjXaGMQXULK8r52DuUaB1C1KHQz3iWSu3apBcIv+3F/zyFjS+pCmTw96JxR6gLhRWwoDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T00:41:19.074459Z"},"content_sha256":"0ad778214fe491191afbf3a7ed7e3e3b98af9ed0ca8438c83db828d8152bc5bc","schema_version":"1.0","event_id":"sha256:0ad778214fe491191afbf3a7ed7e3e3b98af9ed0ca8438c83db828d8152bc5bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:LVEOBLVNVDJSRZVH5QMRJFSNTN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ScrapMem: A Bio-inspired Framework for On-device Personalized Agent Memory via Optical Forgetting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"ScrapMem lets LLM agents keep long-term multimodal memories on edge devices by progressively lowering the resolution of old entries.","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jiale Chang, Yuxiang Ren","submitted_at":"2026-05-05T14:30:30Z","abstract_excerpt":"Long-term personalized memory for LLM agents is challenging on resource-limited edge devices due to high storage costs and multimodal complexity. To address this, we propose ScrapMem, a framework that integrates multimodal data into \"Scrapbook Page.\" ScrapMem introduces Optical Forgetting, an optical compression mechanism that progressively reduces the resolution of older memories, lowering storage cost while suppressing low-value details. To maintain semantic consistency, we construct an Episodic Memory Graph (EM-Graph) that organizes key events into a causal-temporal structure. Extensive exp"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"ScrapMem provides three main benefits: (1) strong performance, achieving a new state-of-the-art with a 51.0% Joint@10 score; (2) high storage efficiency, reducing memory usage by up to 93% via optical forgetting; and (3) improved recall, increasing Recall@10 to 70.3% through structured aggregation.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That progressively lowering resolution of older memories via optical forgetting preserves semantic consistency and that the Episodic Memory Graph maintains causal-temporal structure without introducing errors or losing critical multimodal details.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"ScrapMem introduces optical forgetting to compress multimodal memories for LLM agents on edge devices, cutting storage by up to 93% while reaching 51.0% Joint@10 and 70.3% Recall@10 on ATM-Bench.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"ScrapMem lets LLM agents keep long-term multimodal memories on edge devices by progressively lowering the resolution of old entries.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"61a7b08ffaf66eb27b7ab0c05448e388c2e3a294d8e7630058a6140ff13936ee"},"source":{"id":"2605.03804","kind":"arxiv","version":2},"verdict":{"id":"7830c69a-b8e0-4c83-8e45-5f7832f01ecc","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-07T16:18:31.815932Z","strongest_claim":"ScrapMem provides three main benefits: (1) strong performance, achieving a new state-of-the-art with a 51.0% Joint@10 score; (2) high storage efficiency, reducing memory usage by up to 93% via optical forgetting; and (3) improved recall, increasing Recall@10 to 70.3% through structured aggregation.","one_line_summary":"ScrapMem introduces optical forgetting to compress multimodal memories for LLM agents on edge devices, cutting storage by up to 93% while reaching 51.0% Joint@10 and 70.3% Recall@10 on ATM-Bench.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That progressively lowering resolution of older memories via optical forgetting preserves semantic consistency and that the Episodic Memory Graph maintains causal-temporal structure without introducing errors or losing critical multimodal details.","pith_extraction_headline":"ScrapMem lets LLM agents keep long-term multimodal memories on edge devices by progressively lowering the resolution of old entries."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.03804/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-20T13:33:47.822302Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_title_agreement","ran_at":"2026-05-20T00:31:20.983519Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T15:01:59.196247Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"0cf58ec96c83ed6ca355764688967f8f2e4a513fc470d50d8108797e12fb021b"},"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":"7830c69a-b8e0-4c83-8e45-5f7832f01ecc"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-26T02:04:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"58AQXS+E3Pf4i89aUlcYe43DEvD15K9BxnXX2M/RnVQWwSqaJYBPOcmUYsotSo8Yi+CzjHLsEIOBi6xeEB9xDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T00:41:19.075420Z"},"content_sha256":"2de4a15c17b69e3506908f2f9a36dfe6abc9b42fb200ad42c80643bdb6dec9eb","schema_version":"1.0","event_id":"sha256:2de4a15c17b69e3506908f2f9a36dfe6abc9b42fb200ad42c80643bdb6dec9eb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LVEOBLVNVDJSRZVH5QMRJFSNTN/bundle.json","state_url":"https://pith.science/pith/LVEOBLVNVDJSRZVH5QMRJFSNTN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LVEOBLVNVDJSRZVH5QMRJFSNTN/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":"2026-06-01T00:41:19Z","links":{"resolver":"https://pith.science/pith/LVEOBLVNVDJSRZVH5QMRJFSNTN","bundle":"https://pith.science/pith/LVEOBLVNVDJSRZVH5QMRJFSNTN/bundle.json","state":"https://pith.science/pith/LVEOBLVNVDJSRZVH5QMRJFSNTN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LVEOBLVNVDJSRZVH5QMRJFSNTN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LVEOBLVNVDJSRZVH5QMRJFSNTN","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":"c9e60c6f3912befc56b2b39411b9519674c7df04953bc4b1469241bc0e50b30e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-05T14:30:30Z","title_canon_sha256":"7c77391bb2ede1aad0d1f6a2f3900b9fca862bc02bb10bbc2a7f73379a6b99a0"},"schema_version":"1.0","source":{"id":"2605.03804","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.03804","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"arxiv_version","alias_value":"2605.03804v2","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.03804","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"pith_short_12","alias_value":"LVEOBLVNVDJS","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"pith_short_16","alias_value":"LVEOBLVNVDJSRZVH","created_at":"2026-05-26T02:04:11Z"},{"alias_kind":"pith_short_8","alias_value":"LVEOBLVN","created_at":"2026-05-26T02:04:11Z"}],"graph_snapshots":[{"event_id":"sha256:2de4a15c17b69e3506908f2f9a36dfe6abc9b42fb200ad42c80643bdb6dec9eb","target":"graph","created_at":"2026-05-26T02:04:11Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"ScrapMem provides three main benefits: (1) strong performance, achieving a new state-of-the-art with a 51.0% Joint@10 score; (2) high storage efficiency, reducing memory usage by up to 93% via optical forgetting; and (3) improved recall, increasing Recall@10 to 70.3% through structured aggregation."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That progressively lowering resolution of older memories via optical forgetting preserves semantic consistency and that the Episodic Memory Graph maintains causal-temporal structure without introducing errors or losing critical multimodal details."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"ScrapMem introduces optical forgetting to compress multimodal memories for LLM agents on edge devices, cutting storage by up to 93% while reaching 51.0% Joint@10 and 70.3% Recall@10 on ATM-Bench."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"ScrapMem lets LLM agents keep long-term multimodal memories on edge devices by progressively lowering the resolution of old entries."}],"snapshot_sha256":"61a7b08ffaf66eb27b7ab0c05448e388c2e3a294d8e7630058a6140ff13936ee"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-20T13:33:47.822302Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_title_agreement","ran_at":"2026-05-20T00:31:20.983519Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_compliance","ran_at":"2026-05-19T15:01:59.196247Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.03804/integrity.json","findings":[],"snapshot_sha256":"0cf58ec96c83ed6ca355764688967f8f2e4a513fc470d50d8108797e12fb021b","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Long-term personalized memory for LLM agents is challenging on resource-limited edge devices due to high storage costs and multimodal complexity. To address this, we propose ScrapMem, a framework that integrates multimodal data into \"Scrapbook Page.\" ScrapMem introduces Optical Forgetting, an optical compression mechanism that progressively reduces the resolution of older memories, lowering storage cost while suppressing low-value details. To maintain semantic consistency, we construct an Episodic Memory Graph (EM-Graph) that organizes key events into a causal-temporal structure. Extensive exp","authors_text":"Jiale Chang, Yuxiang Ren","cross_cats":[],"headline":"ScrapMem lets LLM agents keep long-term multimodal memories on edge devices by progressively lowering the resolution of old entries.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-05T14:30:30Z","title":"ScrapMem: A Bio-inspired Framework for On-device Personalized Agent Memory via Optical Forgetting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.03804","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-07T16:18:31.815932Z","id":"7830c69a-b8e0-4c83-8e45-5f7832f01ecc","model_set":{"reader":"grok-4.3"},"one_line_summary":"ScrapMem introduces optical forgetting to compress multimodal memories for LLM agents on edge devices, cutting storage by up to 93% while reaching 51.0% Joint@10 and 70.3% Recall@10 on ATM-Bench.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"ScrapMem lets LLM agents keep long-term multimodal memories on edge devices by progressively lowering the resolution of old entries.","strongest_claim":"ScrapMem provides three main benefits: (1) strong performance, achieving a new state-of-the-art with a 51.0% Joint@10 score; (2) high storage efficiency, reducing memory usage by up to 93% via optical forgetting; and (3) improved recall, increasing Recall@10 to 70.3% through structured aggregation.","weakest_assumption":"That progressively lowering resolution of older memories via optical forgetting preserves semantic consistency and that the Episodic Memory Graph maintains causal-temporal structure without introducing errors or losing critical multimodal details."}},"verdict_id":"7830c69a-b8e0-4c83-8e45-5f7832f01ecc"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0ad778214fe491191afbf3a7ed7e3e3b98af9ed0ca8438c83db828d8152bc5bc","target":"record","created_at":"2026-05-26T02:04:11Z","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":"c9e60c6f3912befc56b2b39411b9519674c7df04953bc4b1469241bc0e50b30e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-05T14:30:30Z","title_canon_sha256":"7c77391bb2ede1aad0d1f6a2f3900b9fca862bc02bb10bbc2a7f73379a6b99a0"},"schema_version":"1.0","source":{"id":"2605.03804","kind":"arxiv","version":2}},"canonical_sha256":"5d48e0aeada8d328e6a7ec1914964d9b5a69169d60ac1ef1d9d2529ad90acf68","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d48e0aeada8d328e6a7ec1914964d9b5a69169d60ac1ef1d9d2529ad90acf68","first_computed_at":"2026-05-26T02:04:11.967474Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:04:11.967474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s6Z1O2OAH8x4p4MoBzkqJfAu9SGPhV6GJlIfABqcJd6R1G239nJusOWEo+bP5ALDYQIv33BpHJ+3nKImF4tGCA==","signature_status":"signed_v1","signed_at":"2026-05-26T02:04:11.968135Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.03804","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ad778214fe491191afbf3a7ed7e3e3b98af9ed0ca8438c83db828d8152bc5bc","sha256:2de4a15c17b69e3506908f2f9a36dfe6abc9b42fb200ad42c80643bdb6dec9eb"],"state_sha256":"623e9ed59835c4ad584a3e47c53a2bba46dd168b8f56fa9a1de68744d6af1ece"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DOHPuRQ6SP6YkwLcoBwJCrDD99XAXa1dIVgYgRxw7mRNscPPPWG17FS4by0g0K9/pvFDQlzJTr9fCK0BXaVjCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T00:41:19.080472Z","bundle_sha256":"3679248a92762e5200b2561a1b0c5e6f74a13acd0ffa168e504186682a454603"}}