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Causal Episodic Memory for Feedback-Driven Agent Repair

arxiv.org/abs/2608.05906

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Updated 5 h ago · first seen 11 Sept 2026

paper_01M294G62CBSS2088P9Z6CGXN3

Published
11 Sept 2026
T1 · 5 h ago
arXiv
2608.05906
T1 · 5 h ago
Category
cs.CL
T1 · 5 h ago

Abstract

LLM agents that repair failures often discard successful corrections, forcing later episodes to rediscover similar solutions. We study whether finalized repair outcomes can improve subsequent Text-to-SQL episodes without parameter updates. We introduce MERIT, a training-free agent that maintains an online dual-polarity memory of oracle-verified corrections and observed unsuccessful directions. Under oracle-assisted benchmark feedback, only memories from earlier finalized episodes are eligible for retrieval. A deterministic classifier assigns a coarse failure type, which conditions a hybrid lexical-dense retriever before the frozen model generates each revision. Using Qwen2.5-7B-Instruct with identical initial predictions and repair budgets, \method{} improves execution accuracy over stateless iterative repair from \(66.34\%\) to \(69.79\%\) on Spider and from \(47.35\%\) to \(48.44\%\) on BIRD. Paired analyses provide clear evidence for the Spider gain but weaker evidence on BIRD. MERIT is not reliably separated from untyped dynamic retrieval on either benchmark, while Reflexion-style memory reaches \(51.24\%\) on BIRD at substantially higher inference cost. Ablations show that negative memory contributes modestly, the value of type conditioning and lexical-dense ranking is dataset dependent, and schema-local experience provides the most consistent benefit. These results clarify when causal cross-query memory improves repair and when broader memory representations remain preferable. Our implementation is available here:

Authors 5

Khang Nhat Hoang Vo, Tam Minh Chu, Anh Trac Duc Dinh, Thuyen Vinh Ha Bui, Tho Quan

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Official page

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Arxiv announce type
replace

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

arXiv id
2608.05906

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Categories
cs.CL

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Primary category
cs.CL

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 5 h agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

5 h ago

Conflicts

None