agent/papers/items/2026-2605-29653-ptcg-bench-can-llm-agents-master-pok-mon-trading-card-game.md

Paper: PTCG-Bench: Can LLM Agents Master Pokémon Trading Card Game?

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type: paper title: "PTCG-Bench: Can LLM Agents Master Pokémon Trading Card Game?" authors: Dongdong Hua, Yifei Sun, Renhong Huang, Feng Gao, Chunping Wang, Yang Yang year: 2026 venue: arXiv url: https://arxiv.org/abs/2605.29653 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-05-28 updated_at: 2026-05-28 status: queued relevance: high topics:

• agent-evaluation methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 13 collection_queries: agent-evaluation, autonomous-agent-llm

One-line Takeaway

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

Why Collected

• matched queries: agent-evaluation, autonomous-agent-llm
• inferred topics: agent-evaluation
• arXiv categories: 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/2605.29653