Paper: Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaboration

type: paper title: "Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaboration" authors: Jiaju Chen, Yuxuan Lu, Jiayi Su, Chaoran Chen, Songlin Xiao, Zheng Zhang, Yun Wang, Yunyao Li, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.06388 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-04 updated_at: 2026-06-06 status: queued relevance: high topics:

agent-evaluation
computer-use
multi-agent
planning
reasoning
tool-use methods:

benchmarks:

models:

datasets:

cs.AI
cs.CL related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 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, multi-agent, planning, reasoning, tool-use
arXiv categories: cs.AI, cs.CL
collection score: 16

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?

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