Cognitive Extensions for Dual-Process Language Agents: Memory and Self-Reflection in Interactive Environments
Paper recorded by Signals 4 on 2026-09-16 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17
Category: cs.AI · 人工智能 · first seen 2026-09-17
Abstract
Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery from failed steps. We extend SwiftSage, a dual-process agent that combines a fast action proposer with a slower planner, using two modular cognitive extensions: an Adaptive Memory Module (AMM) for salience-gated episodic storage and trigger-driven ret
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Cite this page: Cognitive Extensions for Dual-Process Language Agents: Memory and Self-Reflection in Interactive Environments: the #24 most recent of 300 cs.AI papers we have recorded (as of 2026-09-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/cognitive-extensions-for-dual-process-language-agents-memory-and-self-reflection.html
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