{"paper":{"title":"Cognifold: Always-On Proactive Memory via Cognitive Folding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"CogniFold folds event streams into self-organizing graph structures that surface proactive intents at concept density thresholds.","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Dai Shi, Rundong Zhao, Suli Wang, Xinliang Zhou, Yiqun Duan, Yu Deng","submitted_at":"2026-05-13T12:34:39Z","abstract_excerpt":"Existing agent memory remains predominantly reactive and retrieval-based, lacking the capacity to autonomously organize experience into persistent cognitive structure. Toward genuinely autonomous agents, we introduce Cognifold, a brain-inspired \"always-on\" agent memory designed for the next generation of proactive assistants. CogniFold continuously folds fragmented event streams into self-emerging cognitive structures, bootstrapping progressively higher-level cognition from incoming events and accumulated knowledge. We ground this by extending Complementary Learning Systems (CLS) theory from t"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"CogniFold continuously folds fragmented event streams into self-emerging cognitive structures, bootstrapping progressively higher-level cognition from incoming events and accumulated knowledge through graph-topology self-organization that assembles, merges, decays, relinks, and surfaces intents when concept-cluster density crosses a threshold.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the proposed graph-topology self-organization rules, including the density threshold for surfacing intents, will produce memory structures that genuinely match cognitive expectations and enable proactive behavior without additional human-specified rules or post-hoc tuning.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Cognifold is a new proactive memory architecture that folds event streams into emergent cognitive structures by extending complementary learning systems theory with a prefrontal intent layer and graph topology self-organization.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"CogniFold folds event streams into self-organizing graph structures that surface proactive intents at concept density thresholds.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"338a843bf7d7800e1f7731e3a1eea4164b374162492922ffaa5f5ca769006224"},"source":{"id":"2605.13438","kind":"arxiv","version":1},"verdict":{"id":"27bdb9e3-539a-4487-90dd-b41a0855f1e1","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T19:15:48.422416Z","strongest_claim":"CogniFold continuously folds fragmented event streams into self-emerging cognitive structures, bootstrapping progressively higher-level cognition from incoming events and accumulated knowledge through graph-topology self-organization that assembles, merges, decays, relinks, and surfaces intents when concept-cluster density crosses a threshold.","one_line_summary":"Cognifold is a new proactive memory architecture that folds event streams into emergent cognitive structures by extending complementary learning systems theory with a prefrontal intent layer and graph topology self-organization.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the proposed graph-topology self-organization rules, including the density threshold for surfacing intents, will produce memory structures that genuinely match cognitive expectations and enable proactive behavior without additional human-specified rules or post-hoc tuning.","pith_extraction_headline":"CogniFold folds event streams into self-organizing graph structures that surface proactive intents at concept density thresholds."},"references":{"count":77,"sample":[{"doi":"","year":1995,"title":"Cambridge university press, 1995","work_id":"d365e5b3-c426-4877-8311-fc19da26a3b5","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2024,"title":"Titans: Learning to Memorize at Test Time","work_id":"fb2b7625-b733-43cb-af52-00b0a31a8d7f","ref_index":2,"cited_arxiv_id":"2501.00663","is_internal_anchor":true},{"doi":"","year":1999,"title":"Time- dependent reorganization of brain circuitry underlying long-term memory storage.Nature, 400 (6745):671–675, 1999","work_id":"fe8c6069-27ef-4119-9d87-29e04e427c52","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1987,"title":"Harvard University Press, 1987","work_id":"b29274f6-5f21-4791-b481-8a664916fdd5","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2000,"title":"The origin of concepts.Journal of Cognition and Development, 1(1):37–41, 2000","work_id":"1bd64cf5-f1e1-42c1-9a05-2209385ac4ef","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":77,"snapshot_sha256":"fc1ff36c75c47856238a25e6aca9d9b0852a0515cf766855e17f00bff245e4a5","internal_anchors":12},"formal_canon":{"evidence_count":2,"snapshot_sha256":"d175ec73b62f17c436db7415c6bfb52de67af87291d4505c52c455de55e05135"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}