From Human-Human Collaboration to Human-Agent Collaboration: A Vision, Design Philosophy, and an Empirical Framework for Achieving Successful Partnerships Between Humans and LLM Agents
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
The emergence of Large Language Model (LLM) agents enables us to build agent-based intelligent systems that move beyond the role of a "tool" to become genuine collaborators with humans, thereby realizing a novel human-agent collaboration paradigm. Our vision is that LLM agents should resemble remote human collaborators, which allows HCI researchers to ground the future exploration in decades of research on trust, awareness, and common ground in remote human collaboration, while also revealing the unique opportunities and challenges that emerge when one or more partners are AI agents. This workshop establishes a foundational research agenda for the new era by posing the question: How can the rich understanding of remote human collaboration inspire and inform the design and study of human-agent collaboration? We will bring together an interdisciplinary group from HCI, CSCW, and AI to explore this critical transition. The 180-minute workshop will be highly interactive, featuring a keynote speaker, a series of invited lightning talks, and an exploratory group design session where participants will storyboard novel paradigms of human-agent partnership. Our goal is to enlighten the research community by cultivating a shared vocabulary and producing a research agenda that charts the future of collaborative agents.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 13 of its 39 references that are in the map. First posted on arXiv 5 Feb 2026.
Builds on
13 of 39 references.
Closest ancestors · 1
Same direction, newest first
Other references · 12
- 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
- 2020Extracting Training Data from Large Language Modelscited by 2,144
- 2025The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injectionscited by 55
- 2024CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applicationscited by 33
- 2025Towards a Design Guideline for RPA Evaluation: A Survey of Large Language Model-Based Role-Playing Agentscited by 22
- 2023An Empathy-Based Sandbox Approach to Bridge the Privacy Gap among Attitudes, Goals, Knowledge, and Behaviorscited by 18
- 2025Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversightcited by 15
- 2025Toward a Human-Centered Evaluation Framework for Trustworthy LLM-Powered GUI Agentscited by 11
- 2024Why am I seeing this: Democratizing End User Auditing for Online Content Recommendationscited by 7
- 2025DPRF: A Generalizable Dynamic Persona Refinement Framework for Optimizing Behavior Alignment Between Personalized LLM Role-Playing Agents and Humanscited by 5
- 2025My Favorite Streamer is an LLM: Discovering, Bonding, and Co-Creating in AI VTuber Fandomcited by 4
- 2026The Behavioral Fabric of LLM-Powered GUI Agents: Human Values and Interaction Outcomescited by 3
Built on by
Citing papers per year: 2026: 2.
2 papers.
Similar, not cited
Close in wording, no citation either way
- 2025Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration
- 2025LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey
- 2025A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy
- 2024Two Heads Are Better Than One: Collaborative LLM Embodied Agents for Human-Robot Interaction
- 2023Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents
- 2026HAS-Bench: Evaluating LLM-Based Human-Agent Systems under Configurable Human Participation
- 2025Multi-Agent Language Models: Advancing Cooperation, Coordination, and Adaptation
- 2026Toward Human-Centered Multi-Agent Systems: Integrating Cognition, Culture, Values, and Cooperation in AI Agents