{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:5ZLJE5QYHJCFNPCP6N7UD2GHND","short_pith_number":"pith:5ZLJE5QY","schema_version":"1.0","canonical_sha256":"ee569276183a4456bc4ff37f41e8c768d10cd389eb72cd917ccc3630481224d2","source":{"kind":"arxiv","id":"2607.29104","version":1},"attestation_state":"computed","paper":{"title":"Reproducing LightMem: Naive RAG Is Just as Good for Memory Management","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"2), (2) CSIRO, 3) ((1) The University of Queensland, (3) Google), Bevan Koopman (1, Guido Zuccon (1, Shuai Wang (1), Yongjie Zhou (1)","submitted_at":"2026-07-31T07:33:34Z","abstract_excerpt":"Long-term conversational agents require access to information from earlier interactions, such as a user's preferences, past requests, or previously mentioned facts. Repeatedly providing the full dialogue history can be expensive as conversations grow, so many memory approaches instead transform past interactions into compact entries that can be retrieved when needed. LightMem is a recent lightweight memory-management approach that reports strong effectiveness while maintaining relatively low construction cost. However, it still relies on a separate constructed memory representation and is eval"},"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":"2607.29104","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-07-31T07:33:34Z","cross_cats_sorted":[],"title_canon_sha256":"ba67cc3fa456ad54dba70e02a63a8673d49f1f3af87111e5165854a077a0dec7","abstract_canon_sha256":"5debaaa5f4fef89e641e3769f627bd8c3d35d78eedd3b08e8b42115165c3b6d2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:19:07.938542Z","signature_b64":"DMHLAkeSMhBYZkaeFjZ2TORg0WnUigwWo8Sny67C9QAbCHl2iKnDdHvkF2cwWhMv7o9T+XYjMf9OHQ6qeZUTDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee569276183a4456bc4ff37f41e8c768d10cd389eb72cd917ccc3630481224d2","last_reissued_at":"2026-08-03T01:19:07.937011Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:19:07.937011Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Reproducing LightMem: Naive RAG Is Just as Good for Memory Management","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"2), (2) CSIRO, 3) ((1) The University of Queensland, (3) Google), Bevan Koopman (1, Guido Zuccon (1, Shuai Wang (1), Yongjie Zhou (1)","submitted_at":"2026-07-31T07:33:34Z","abstract_excerpt":"Long-term conversational agents require access to information from earlier interactions, such as a user's preferences, past requests, or previously mentioned facts. Repeatedly providing the full dialogue history can be expensive as conversations grow, so many memory approaches instead transform past interactions into compact entries that can be retrieved when needed. LightMem is a recent lightweight memory-management approach that reports strong effectiveness while maintaining relatively low construction cost. However, it still relies on a separate constructed memory representation and is eval"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29104","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/2607.29104/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":"2607.29104","created_at":"2026-08-03T01:19:07.937974+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.29104v1","created_at":"2026-08-03T01:19:07.937974+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29104","created_at":"2026-08-03T01:19:07.937974+00:00"},{"alias_kind":"pith_short_12","alias_value":"5ZLJE5QYHJCF","created_at":"2026-08-03T01:19:07.937974+00:00"},{"alias_kind":"pith_short_16","alias_value":"5ZLJE5QYHJCFNPCP","created_at":"2026-08-03T01:19:07.937974+00:00"},{"alias_kind":"pith_short_8","alias_value":"5ZLJE5QY","created_at":"2026-08-03T01:19:07.937974+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/5ZLJE5QYHJCFNPCP6N7UD2GHND","json":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND.json","graph_json":"https://pith.science/api/pith-number/5ZLJE5QYHJCFNPCP6N7UD2GHND/graph.json","events_json":"https://pith.science/api/pith-number/5ZLJE5QYHJCFNPCP6N7UD2GHND/events.json","paper":"https://pith.science/paper/5ZLJE5QY"},"agent_actions":{"view_html":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND","download_json":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND.json","view_paper":"https://pith.science/paper/5ZLJE5QY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.29104&json=true","fetch_graph":"https://pith.science/api/pith-number/5ZLJE5QYHJCFNPCP6N7UD2GHND/graph.json","fetch_events":"https://pith.science/api/pith-number/5ZLJE5QYHJCFNPCP6N7UD2GHND/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND/action/storage_attestation","attest_author":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND/action/author_attestation","sign_citation":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND/action/citation_signature","submit_replication":"https://pith.science/pith/5ZLJE5QYHJCFNPCP6N7UD2GHND/action/replication_record"}},"created_at":"2026-08-03T01:19:07.937974+00:00","updated_at":"2026-08-03T01:19:07.937974+00:00"}