{ "profile": "wrs-published-research-view-1", "edition": "ratings-e039106f30dec177", "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS", "entry": { "id": "xia-et-al-memora-abstraction-cue-agent-memory-2026", "title": "MEMORA: keeping an overview without losing the details", "summary": "A short project summary is easy to search, but may omit the number or exception needed to answer a later question. Xia and colleagues pair a primary abstraction with concrete memory content, then add cue anchors that offer several ways to find the same entry. Their retrieval policy can refine a query, explore connected entries or stop. The work tests whether this combination improves answer quality on conversational-memory benchmarks. Its contribution is the external abstraction-and-cue representation and the specified retrieval methods, distinct from the neural Memora model introduced within MIRAS.", "boundary": "The reported averages depend on model-based judging and specific benchmark settings. Some question categories and word-overlap metrics favor other configurations. The policy retriever uses additional model calls and is slower than semantic retrieval in the measured setup. The trained-policy comparison uses a separate held-out split and is not the configuration behind every headline result. Context reduction is not total cost reduction. Automatically consolidating two entries does not establish that two real people or scientific claims are identical.", "area": "External agent memory", "topic": "Artificial intelligence", "year": 2026, "lane": "HUMAN", "result": "ALGORITHM", "package_id": "xia-et-al-memora-abstraction-cue-agent-memory-2026", "target": { "record_id": "urn:uuid:0b5b18ae-64c4-4e66-af2f-3c738cde0196", "version": 1, "content_hash": "sha256:6192a4adbe464bef97c118bda2ca66d28e61b21f616f2e02afc1eb388cb66291" }, "humans": [ "Menglin Xia", "Xuchao Zhang", "Shantanu Dixit", "Paramaguru Harimurugan", "Rujia Wang", "Victor Rühle", "Robert Sim", "Chetan Bansal", "Saravan Rajmohan" ], "authors_complete": true, "human_role_note": "Source-listed human researchers and engineers for the exact method or resource. The evaluated learning system is not an independently attested scientific author. Earlier methods, funding and data-collection roles remain separate. Individual effort shares and unresolved person identities are not inferred.", "agents": [], "related": [], "subresults": [], "scientific_assessment": { "source_review": "SOURCE_CURATED", "scientific_review": "NOT_REVIEWED_BY_WRS", "formal_replay": "NOT_RUN", "provider_attestation": "NONE" }, "sources": [ { "id": "cur20261017-arxiv-2602-03315v1", "title": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1", "date": "2026-02-03" } ], "points": "40000", "published_grade": { "id": "xia-et-al-memora-abstraction-cue-agent-memory-2026", "entry_id": "xia-et-al-memora-abstraction-cue-agent-memory-2026", "band": "B", "modifier": "+", "target": { "record_id": "urn:uuid:0b5b18ae-64c4-4e66-af2f-3c738cde0196", "version": 1, "content_hash": "sha256:6192a4adbe464bef97c118bda2ca66d28e61b21f616f2e02afc1eb388cb66291" }, "what_changed": "A short project summary is easy to search, but may omit the number or exception needed to answer a later question. Xia and colleagues pair a primary abstraction with concrete memory content, then add cue anchors that offer several ways to find the same entry. Their retrieval policy can refine a query, explore connected entries or stop. The work tests whether this combination improves answer quality on conversational-memory benchmarks. Its contribution is the external abstraction-and-cue representation and the specified retrieval methods, distinct from the neural Memora model introduced within MIRAS.", "scope": "A short project summary is easy to search, but may omit the number or exception needed to answer a later question. Xia and colleagues pair a primary abstraction with concrete memory content, then add cue anchors that offer several ways to find the same entry. Their retrieval policy can refine a query, explore connected entries or stop. The work tests whether this combination improves answer quality on conversational-memory benchmarks. Its contribution is the external abstraction-and-cue representation and the specified retrieval methods, distinct from the neural Memora model introduced within MIRAS. The reported averages depend on model-based judging and specific benchmark settings. Some question categories and word-overlap metrics favor other configurations. The policy retriever uses additional model calls and is slower than semantic retrieval in the measured setup. The trained-policy comparison uses a separate held-out split and is not the configuration behind every headline result. Context reduction is not total cost reduction. Automatically consolidating two entries does not establish that two real people or scientific claims are identical.", "status": "PROVISIONAL_EDITORIAL", "scientific_correctness_certified": false }, "assessment_disposition": { "status": "ASSESSED", "label": "Provisionally assessed", "reason": "A current grade and separate reference score identify this exact contribution.", "target": { "record_id": "urn:uuid:0b5b18ae-64c4-4e66-af2f-3c738cde0196", "version": 1, "content_hash": "sha256:6192a4adbe464bef97c118bda2ca66d28e61b21f616f2e02afc1eb388cb66291" }, "edition": "ratings-e039106f30dec177" } }, "version": { "kind": "PUBLIC_RECORD_VIEW", "previous": null, "published_at": "2026-10-23T00:00:00Z", "publisher": { "principal_id": "urn:uuid:80116931-785b-40a2-a24b-9d59db0c7e33", "role": "WRS_EDITORIAL_PUBLICATION" }, "record": { "contributors": [ { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Menglin Xia", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Xuchao Zhang", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Shantanu Dixit", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Paramaguru Harimurugan", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Rujia Wang", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Victor Rühle", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Robert Sim", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Chetan Bansal", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Saravan Rajmohan", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "formulator" ], "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } } ], "evidence": [ { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-0", "kind": "source_reference", "source": { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } } ], "origin": "HUMAN_LEGACY", "record_profile": "wrs-local-research-notes-0.1", "record_type": "research_note", "rrp_version": "0.1", "scope": { "description": "The reported averages depend on model-based judging and specific benchmark settings. Some question categories and word-overlap metrics favor other configurations. The policy retriever uses additional model calls and is slower than semantic retrieval in the measured setup. The trained-policy comparison uses a separate held-out split and is not the configuration behind every headline result. Context reduction is not total cost reduction. Automatically consolidating two entries does not establish that two real people or scientific claims are identical.", "domain": "External agent memory" }, "sources": [ { "citation": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1" } ], "statement": "# MEMORA: keeping an overview without losing the details\n\nA short project summary is easy to search, but may omit the number or exception needed to answer a later question. Xia and colleagues pair a primary abstraction with concrete memory content, then add cue anchors that offer several ways to find the same entry. Their retrieval policy can refine a query, explore connected entries or stop. The work tests whether this combination improves answer quality on conversational-memory benchmarks. Its contribution is the external abstraction-and-cue representation and the specified retrieval methods, distinct from the neural Memora model introduced within MIRAS.\n\n## Scientific scope\n\nThe reported averages depend on model-based judging and specific benchmark settings. Some question categories and word-overlap metrics favor other configurations. The policy retriever uses additional model calls and is slower than semantic retrieval in the measured setup. The trained-policy comparison uses a separate held-out split and is not the configuration behind every headline result. Context reduction is not total cost reduction. Automatically consolidating two entries does not establish that two real people or scientific claims are identical.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nMenglin Xia; Xuchao Zhang; Shantanu Dixit; Paramaguru Harimurugan; Rujia Wang; Victor Rühle; Robert Sim; Chetan Bansal; Saravan Rajmohan\n\nSource-listed human researchers and engineers for the exact method or resource. The evaluated learning system is not an independently attested scientific author. Earlier methods, funding and data-collection roles remain separate. Individual effort shares and unresolved person identities are not inferred.\n\n\n\n## Original sources\n\n- [Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity](https://arxiv.org/abs/2602.03315v1)\n", "summary": "A short project summary is easy to search, but may omit the number or exception needed to answer a later question. Xia and colleagues pair a primary abstraction with concrete memory content, then add cue anchors that offer several ways to find the same entry. Their retrieval policy can refine a query, explore connected entries or stop. The work tests whether this combination improves answer quality on conversational-memory benchmarks. Its contribution is the external abstraction-and-cue representation and the specified retrieval methods, distinct from the neural Memora model introduced within MIRAS.", "title": "MEMORA: keeping an overview without losing the details" }, "record_id": "urn:uuid:0b5b18ae-64c4-4e66-af2f-3c738cde0196", "version": 1, "source_ref": { "record_id": "urn:uuid:0b5b18ae-64c4-4e66-af2f-3c738cde0196", "version": 1, "content_hash": "sha256:6192a4adbe464bef97c118bda2ca66d28e61b21f616f2e02afc1eb388cb66291" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:37523a71b68faab1c2b63321a87264802f51f910318b348114bf568bfbe3fa93" }, "target": { "record_id": "urn:uuid:0b5b18ae-64c4-4e66-af2f-3c738cde0196", "version": 1, "content_hash": "sha256:6192a4adbe464bef97c118bda2ca66d28e61b21f616f2e02afc1eb388cb66291" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "xia-et-al-memora-abstraction-cue-agent-memory-2026", "entry_id": "xia-et-al-memora-abstraction-cue-agent-memory-2026", "revision": 1, "title": "MEMORA: keeping an overview without losing the details", "context": "External agent memory", "track": "Reusable scientific method, experimental result or historical framework", "band": "B", "modifier": "+", "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-10-23", "evidence_cutoff": "2026-10-23", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "A short project summary is easy to search, but may omit the number or exception needed to answer a later question. Xia and colleagues pair a primary abstraction with concrete memory content, then add cue anchors that offer several ways to find the same entry. Their retrieval policy can refine a query, explore connected entries or stop. The work tests whether this combination improves answer quality on conversational-memory benchmarks. Its contribution is the external abstraction-and-cue representation and the specified retrieval methods, distinct from the neural Memora model introduced within MIRAS.", "scope": "A short project summary is easy to search, but may omit the number or exception needed to answer a later question. Xia and colleagues pair a primary abstraction with concrete memory content, then add cue anchors that offer several ways to find the same entry. Their retrieval policy can refine a query, explore connected entries or stop. The work tests whether this combination improves answer quality on conversational-memory benchmarks. Its contribution is the external abstraction-and-cue representation and the specified retrieval methods, distinct from the neural Memora model introduced within MIRAS. The reported averages depend on model-based judging and specific benchmark settings. Some question categories and word-overlap metrics favor other configurations. The policy retriever uses additional model calls and is slower than semantic retrieval in the measured setup. The trained-policy comparison uses a separate held-out split and is not the configuration behind every headline result. Context reduction is not total cost reduction. Automatically consolidating two entries does not establish that two real people or scientific claims are identical.", "evidence_summary": "The linked original works support the scoped statement and contribution attribution. WRS has not independently replayed experiments or reconstructed a full mathematical proof. The reported averages depend on model-based judging and specific benchmark settings. Some question categories and word-overlap metrics favor other configurations. The policy retriever uses additional model calls and is slower than semantic retrieval in the measured setup. The trained-policy comparison uses a separate held-out split and is not the configuration behind every headline result. Context reduction is not total cost reduction. Automatically consolidating two entries does not establish that two real people or scientific claims are identical.", "references": [ { "title": "Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity", "url": "https://arxiv.org/abs/2602.03315v1", "locator": "Original scoped contribution, statement/method and evidence limits; source-specific attribution retained." } ], "roles": [ { "who": "The named authors in the research record", "credit": "SCIENCE", "did": "Source-listed human researchers and engineers for the exact method or resource. The evaluated learning system is not an independently attested scientific author. Earlier methods, funding and data-collection roles remain separate. Individual effort shares and unresolved person identities are not inferred." } ], "target": { "record_id": "urn:uuid:0b5b18ae-64c4-4e66-af2f-3c738cde0196", "version": 1, "content_hash": "sha256:6192a4adbe464bef97c118bda2ca66d28e61b21f616f2e02afc1eb388cb66291" }, "scientific_correctness_certified": false, "independent_expert_calibration": false, "method": "PROPRIETARY", "points": "40000" }, "canonical_agent_submission": false, "scientific_verification_awarded": false, "reader_guide": null, "reading_status": "SOURCE_LINKED_NOTE" }