mlsanityData to 14 Oct 2026

Beyond Prompts: Learning from Human Communication for Enhanced AI Intent Alignment

arXiv 2405.05678 ↗First posted 9 May 2024cs.HC cs.CLcited by 3

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Abstract (arXiv)

AI intent alignment, ensuring that AI produces outcomes as intended by users, is a critical challenge in human-AI interaction. The emergence of generative AI, including LLMs, has intensified the significance of this problem, as interactions increasingly involve users specifying desired results for AI systems. In order to support better AI intent alignment, we aim to explore human strategies for intent specification in human-human communication. By studying and comparing human-human and human-LLM communication, we identify key strategies that can be applied to the design of AI systems that are more effective at understanding and aligning with user intent. This study aims to advance toward a human-centered AI system by bringing together human communication strategies for the design of AI systems.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 3 of its 17 references that are in the map. First posted on arXiv 9 May 2024.

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3 of 17 references.

References · 3

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023Interactive AI Alignment: Specification, Process, and Evaluation Alignmentcited by 22
  3. 2022How do you Converse with an Analytical Chatbot? Revisiting Gricean Maxims for Designing Analytical Conversational Behaviorcited by 20

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Citing papers per year: 2025: 3.

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  1. 2026Evaluating 5W3H Structured Prompting for Intent Alignment in Human-AI Interaction
  2. 2024Position: Towards Bidirectional Human-AI Alignment
  3. 2025Conversational Alignment with Artificial Intelligence in Context
  4. 2025Implicature in Interaction: Understanding Implicature Improves Alignment in Human-LLM Interaction
  5. 2025Enhancing Conversational Agents with Theory of Mind: Aligning Beliefs, Desires, and Intentions for Human-Like Interaction
  6. 2025Evaluating AI Alignment in LLMs: Output Analysis of Value Priorities Across 75 Models with Human Benchmarking
  7. 2024Language Models in Dialogue: Conversational Maxims for Human-AI Interactions
  8. 2026Who Controls the Conversation? User Perspectives On Generative AI (LLM) System Prompts