# Paper: CausalGame: Benchmarking Causal Thinking of LLM Agents in Games

---
type: paper
title: "CausalGame: Benchmarking Causal Thinking of LLM Agents in Games"
authors: Zhenhao Chen, Yongqiang Chen, Chenxi Liu, Junchi Yu, Xiangchen Song, Zijian Li, Jialin Li, Philip Torr, et al.
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2607.04293
code_url:
source: arxiv
collected_at: 2026-07-08
published_at: 2026-07-05
updated_at: 2026-07-05
status: queued
relevance: high
topics:
  - agent-evaluation
  - computer-use
  - planning
  - reasoning
methods:
  -
benchmarks:
  -
models:
  -
datasets:
  - cs.CL
  - cs.AI
  - cs.LG
  - stat.ML
related_concepts:
  -
related_jobs:
  -
related_experiments:
  -
related_projects:
  -
collection_score: 17
collection_queries: llm-agent
---

## One-line Takeaway

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

## Why Collected

- matched queries: llm-agent
- inferred topics: agent-evaluation, computer-use, planning, reasoning
- arXiv categories: cs.CL, cs.AI, cs.LG, stat.ML
- collection score: 17

## 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/2607.04293