agent/papers/items/2026-2607-12122-an-agentic-ai-scientific-community-for-automated-neural-operator-discovery.md

Paper: An Agentic AI Scientific Community for Automated Neural Operator Discovery

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type: paper title: An Agentic AI Scientific Community for Automated Neural Operator Discovery authors: Luis Loo, Ulisses Braga-Neto year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.12122 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-13 updated_at: 2026-07-13 status: queued relevance: high topics:

• agent-evaluation
• planning
• world-model methods:

benchmarks:

models:

datasets:

• cs.LG related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 14 collection_queries: agentic-ai

One-line Takeaway

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

Why Collected

• matched queries: agentic-ai
• inferred topics: agent-evaluation, planning, world-model
• arXiv categories: cs.LG
• 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/2607.12122