Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaboration
arXiv:2606.06388v1 Announce Type: cross Abstract: Recent advances in LLM agents have enabled complex cognitive capabilities, such as multi-step reasoning, planning, and tool use, that increasingly position these agents as human collaborators. Effective collaboration, however, requires collaborators to continuously maintain and align mental models of their own reasoning,partners' intentions, and shared goals during the collaborative process. Today's agents rarely develop such capabilities since they are primarily optimized for task completion, and the community lacks authentic human collaborati
The proliferation of advanced LLM agents necessitates human-agent collaboration benchmarks, aligning with current research priorities in AI. This release provides a critical dataset for evaluating and improving agent's collaborative capabilities.
Achieving effective human-AI collaboration is a significant hurdle for integrating AI agents into complex workflows, making datasets focused on mental model alignment crucial for AI system development. This directly impacts the scalability and reliability of AI agents in real-world applications.
The availability of this dataset directly enables researchers to develop and evaluate AI agents that can better understand and align with human intentions and goals during collaborative tasks. This shifts focus from mere task completion to genuine collaborative intelligence in agent design.
- · AI researchers
- · Developers of AI agents
- · Companies implementing AI in complex workflows
- · AI agent developers relying solely on task-completion metrics
- · AI solutions with poor human-agent interfaces
AI agents will develop improved capabilities for understanding human collaborative intent and mental models.
More sophisticated and reliable human-AI collaborative systems will emerge, leading to increased adoption of AI in diverse professional settings.
The definition of 'intelligence' in AI will expand to explicitly include collaborative and social reasoning, impacting future research directions and ethical considerations.
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