mlsanityData to 14 Oct 2026

A Survey on Human-AI Collaboration with Large Foundation Models

arXiv 2403.04931 ↗First posted 7 Mar 2024cs.AI cs.CL cs.HCcited by 7

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Abstract (arXiv)

As the capabilities of artificial intelligence (AI) continue to expand rapidly, Human-AI (HAI) Collaboration, combining human intellect and AI systems, has become pivotal for advancing problem-solving and decision-making processes. The advent of Large Foundation Models (LFMs) has greatly expanded its potential, offering unprecedented capabilities by leveraging vast amounts of data to understand and predict complex patterns. At the same time, realizing this potential responsibly requires addressing persistent challenges related to safety, fairness, and control. This paper reviews the crucial integration of LFMs with HAI, highlighting both opportunities and risks. We structure our analysis around four areas: human-guided model development, collaborative design principles, ethical and governance frameworks, and applications in high-stakes domains. Our review shows that successful HAI systems are not the automatic result of stronger models but the product of careful, human-centered design. By identifying key open challenges, this survey aims to give insight into current and future research that turns the raw power of LFMs into partnerships that are reliable, trustworthy, and beneficial to society.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 66 of its 202 references that are in the map. First posted on arXiv 7 Mar 2024.

Builds on

66 of 202 references.

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38 more
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50 most cited of 66 All 66 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 1; 2026: 3.

7 papers.

  1. 2024Evaluating Human-AI Collaboration: A Review and Methodological Frameworkcited by 27
  2. 2026Feedback by Design: Understanding and Overcoming User Feedback Barriers in Conversational Agentscited by 4
  3. 2024Aligning Generalisation Between Humans and Machinescited by 2
  4. 2024Standardization Trends on Safety and Trustworthiness Technology for Advanced AIcited by 0
  5. 2025Simulating Teams with LLM Agents: Interactive 2D Environments for Studying Human-AI Dynamicscited by 0
  6. 2026ARC: Fair Relative Advantage Comparison in Open-Ended Real-World Interactioncited by 0
  7. 2026A three-dimensional typology of agency for advanced AI systemscited by 0