# Paper: ExpWeaver: LLM Agents Learn from Experience via Latent RAG

---
type: paper
title: "ExpWeaver: LLM Agents Learn from Experience via Latent RAG"
authors: Tao Feng, Tianyang Luo, Jingjun Xu, Zhigang Hua, Yan Xie, Shuang Yang, Ge Liu, Jiaxuan You
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2606.01041
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-05-31
updated_at: 2026-05-31
status: queued
relevance: high
topics:
  - agent-evaluation
  - coding-agent
  - planning
  - rag
  - reasoning
  - tool-use
methods:
  -
benchmarks:
  -
models:
  -
datasets:
  - cs.CL
related_concepts:
  -
related_jobs:
  -
related_experiments:
  -
related_projects:
  -
collection_score: 17
collection_queries: planning-agent, rag-agent
---

## One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

## Why Collected

- matched queries: planning-agent, rag-agent
- inferred topics: agent-evaluation, coding-agent, planning, rag, reasoning, tool-use
- arXiv categories: cs.CL
- collection score: 17

## Review Checklist

- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?

## Links

- arXiv: https://arxiv.org/abs/2606.01041