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agent/papers/items/2026-2605-03328-llm-adam-a-generalizable-llm-agent-framework-for-pre-print-anomaly-detection-in-.md
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# Paper: LLM-ADAM: A Generalizable LLM Agent Framework for Pre-Print Anomaly Detection in Additive Manufacturing
---
type: paper
title: "LLM-ADAM: A Generalizable LLM Agent Framework for Pre-Print Anomaly Detection in Additive Manufacturing"
authors: Ahmadreza Eslaminia, Chuhan Cai, Cameron Smith, Ruo-Syuan Mei, Shichen Li, Rajiv Malhotra, Klara Nahrstedt, Chenhui Shao
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2605.03328
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-05-05
updated_at: 2026-05-05
status: queued
relevance: high
topics:
- agent-evaluation
- computer-use
- planning
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.LG
- cs.AI
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 13
collection_queries: planning-agent
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: planning-agent
- inferred topics: agent-evaluation, computer-use, planning
- arXiv categories: cs.LG, cs.AI
- 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/2605.03328