mlsanityData to 7 Oct 2026

Problem Solving Through Human-AI Preference-Based Cooperation

arXiv 2408.07461 ↗First posted 14 Aug 2024cs.AI cs.HCcited by 11

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Abstract (arXiv)

While there is a widespread belief that artificial general intelligence (AGI) -- or even superhuman AI -- is imminent, complex problems in expert domains are far from being solved. We argue that such problems require human-AI cooperation and that the current state of the art in generative AI is unable to play the role of a reliable partner due to a multitude of shortcomings, including difficulty to keep track of a complex solution artifact (e.g., a software program), limited support for versatile human preference expression and lack of adapting to human preference in an interactive setting. To address these challenges, we propose HAICo2, a novel human-AI co-construction framework. We take first steps towards a formalization of HAICo2 and discuss the difficult open research problems that it faces.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 65 of its 129 references that are in the map. First posted on arXiv 14 Aug 2024.

Builds on

65 of 129 references.

References · 65

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38 more
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50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 5.

11 papers.

  1. 2025LLM-Based Human-Agent Collaboration and Interaction Systems: A Surveycited by 28
  2. 2025Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Frameworkcited by 10
  3. 2025A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomycited by 9
  4. 2025Can LLMs Automate Fact-Checking Article Writing?cited by 7
  5. 2025Expert Preference-based Evaluation of Automated Related Work Generationcited by 6
  6. 2025Embracing Trustworthy Brain-Agent Collaboration as Paradigm Extension for Intelligent Assistive Technologiescited by 5
  7. 2026Preventing the Collapse of Peer Review Requires Verification-First AIcited by 3
  8. 2026When to Ask a Question: Understanding Communication Strategies in Generative AI Toolscited by 0
  9. 2026Judgment-Grounded Expansion for Peer Review Generationcited by 0
  10. 2026The FIL Hypothesis: Inductive Biases Help with Kernel Engineeringcited by 0
  11. 2026The Boundaries of Automation: A Theory of Persistent Human Participationcited by 0