# Paper: A Novel Method for Differential-Algebraic Dynamic Model Discovery in Power Systems: An LLM-Based Multi-Agent Collaborative Framework

---
type: paper
title: "A Novel Method for Differential-Algebraic Dynamic Model Discovery in Power Systems: An LLM-Based Multi-Agent Collaborative Framework"
authors: Xinming Wang, Fan Tang, Yingli Wei, Yakun He, Zhe Liu, Ping Jiang, Haoyu Wu, Zihan Guo, et al.
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2606.31314
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-06-30
updated_at: 2026-06-30
status: queued
relevance: high
topics:
  - agent-evaluation
  - computer-use
  - multi-agent
methods:
  -
benchmarks:
  -
models:
  -
datasets:
  - eess.SY
related_concepts:
  -
related_jobs:
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related_experiments:
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related_projects:
  -
collection_score: 14
collection_queries: multi-agent-llm
---

## One-line Takeaway

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

## Why Collected

- matched queries: multi-agent-llm
- inferred topics: agent-evaluation, computer-use, multi-agent
- arXiv categories: eess.SY
- collection score: 14

## 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/2606.31314