# More Than 1v1: Human-AI Alignment in Early Developmental Communities with Multimodal LLMs

arXiv: https://arxiv.org/abs/2603.07134 · HTML: https://mlsanity.com/paper/2603.07134/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in MLLM training and visual instruction tuning, one of 16 directions in Multimodal LLMs / vision-language models.
- Builds on 4 of its 14 references that are in the map.
- First posted on arXiv 7 Mar 2026.

## Placed in

- Multimodal LLMs / vision-language models / [MLLM training and visual instruction tuning](https://mlsanity.com/mllm/mllm-training-and-visual-instruction-tuning/)

## Builds on (most cited first, 4 of 4)

- [Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences](https://mlsanity.com/paper/2404.12272/) (2024)
- [Aligning Large Language Models with Human Opinions through Persona Selection and Value--Belief--Norm Reasoning](https://mlsanity.com/paper/2311.08385/) (2023)
- [On the Alignment of Large Language Models with Global Human Opinion](https://mlsanity.com/paper/2509.01418/) (2025)
- [Towards Multimodal Large-Language Models for Parent-Child Interaction: A Focus on Joint Attention](https://mlsanity.com/paper/2502.19877/) (2025)

## Abstract (arXiv)

In early developmental contexts, particularly in parent-child interaction analysis, alignment involves families and professionals such as speech-language pathologists (SLPs) who interpret children's everyday interactions from different roles. When multimodal large language models (MLLMs) are introduced to support this process, alignment becomes a question of how authority, responsibility, and emotional risk are distributed across stakeholders. Through a three-part study with five families and three SLPs, we trace how MLLM-generated outputs move from expert-facing analysis to parent-facing feedback. We propose layered community alignment: grounding representations in expert-aligned structures, mediating translation through professional guardrails, and enabling family-level adaptation within those boundaries. We argue that alignment in developmental settings should be treated as a community-governed process rather than an individual optimisation problem.