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agent/papers/items/2026-2606-22495-grounded-scaling-why-agentic-ai-needs-deterministic-environments.md
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2026-07-08 12:25:30 +08:00

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Paper: Grounded Scaling: Why Agentic AI Needs Deterministic Environments


type: paper title: "Grounded Scaling: Why Agentic AI Needs Deterministic Environments" authors: Liang Ding, Xintong Wang year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.22495 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-21 updated_at: 2026-06-21 status: queued relevance: high topics:

  • agent-safety
  • embodied-agent
  • multi-agent
  • reasoning
  • tool-use methods:

benchmarks:

models:

datasets:

  • cs.AI related_concepts:

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-safety, embodied-agent, multi-agent, reasoning, tool-use
  • arXiv categories: cs.AI
  • 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?