ParetoOptimal/repro-memorybench
0
1{2 "schema_version": 1,3 "title": "Repro - MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems",4 "emoji": "🎯",5 "space_id": "ParetoOptimal/repro-memorybench",6 "paper": {7 "arxiv_id": "2510.17281"8 },9 "tags": [10 "icml2026-repro",11 "paper-If4X4W2HWx"12 ],13 "updated_at": "2026-07-16T20:48:07+00:00",14 "root": {15 "slug": "index",16 "title": "Repro - MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems",17 "file": "pages/index.md",18 "children": [19 {20 "slug": "paper-approach",21 "title": "Paper & approach",22 "file": "pages/paper-approach/page.md",23 "children": []24 },25 {26 "slug": "claim-1-three-module-framework",27 "title": "Claim 1: three-module framework",28 "file": "pages/claim-1-three-module-framework/page.md",29 "children": []30 },31 {32 "slug": "claim-2-dataset-composition",33 "title": "Claim 2: dataset composition",34 "file": "pages/claim-2-dataset-composition/page.md",35 "children": []36 },37 {38 "slug": "claim-3-memory-and-feedback-taxonomy",39 "title": "Claim 3: memory and feedback taxonomy",40 "file": "pages/claim-3-memory-and-feedback-taxonomy/page.md",41 "children": []42 },43 {44 "slug": "claim-4-advanced-memory-vs-simple-rag",45 "title": "Claim 4: advanced memory vs simple RAG",46 "file": "pages/claim-4-advanced-memory-vs-simple-rag/page.md",47 "children": []48 },49 {50 "slug": "claim-6-feedback-a-b",51 "title": "Claim 6: feedback A/B",52 "file": "pages/claim-6-feedback-a-b/page.md",53 "children": []54 },55 {56 "slug": "claim-5-efficiency-costs",57 "title": "Claim 5: efficiency costs",58 "file": "pages/claim-5-efficiency-costs/page.md",59 "children": []60 },61 {62 "slug": "conclusion",63 "title": "Conclusion",64 "file": "pages/conclusion/page.md",65 "children": []66 }67 ]68 },69 "agent_view_tokens": 12424,70 "revision": "1784234887582626392"71}