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# Paper: MIMII-Agent: Leveraging LLMs with Function Calling for Relative Evaluation of Anomalous Sound Detection
---
type: paper
title: "MIMII-Agent: Leveraging LLMs with Function Calling for Relative Evaluation of Anomalous Sound Detection"
authors: Harsh Purohit, Tomoya Nishida, Kota Dohi, Takashi Endo, Yohei Kawaguchi
year: 2025
venue: arXiv
url: https://arxiv.org/abs/2507.20666
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2025-07-28
updated_at: 2025-07-28
status: queued
relevance: high
topics:
- agent-evaluation
- rag
- tool-use
methods:
-
benchmarks:
-
models:
-
datasets:
- eess.AS
- cs.AI
- cs.LG
- cs.SD
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 13
collection_queries: function-calling
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: function-calling
- inferred topics: agent-evaluation, rag, tool-use
- arXiv categories: eess.AS, cs.AI, cs.LG, cs.SD
- collection score: 13
## 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/2507.20666