# TRAIL: A Platform for Configurable Human--AI Teaming Experiments

arXiv: https://arxiv.org/abs/2607.12180 · HTML: https://mlsanity.com/paper/2607.12180/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 32 references that are in the map.
- First posted on arXiv 13 Jul 2026.

## Builds on (most cited first, 11 of 11)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits](https://mlsanity.com/paper/2305.02547/) (2023)
- [Evaluating and Inducing Personality in Pre-trained Language Models](https://mlsanity.com/paper/2206.07550/) (2022)
- [ConvoKit: A Toolkit for the Analysis of Conversations](https://mlsanity.com/paper/2005.04246/) (2020)
- [Empirica: a virtual lab for high-throughput macro-level experiments](https://mlsanity.com/paper/2006.11398/) (2020)
- [Group Communication Analysis: A Computational Linguistics Approach for Detecting Sociocognitive Roles in Multi-Party Interactions](https://mlsanity.com/paper/1801.03563/) (2018)
- [Catalyzing Equity in STEM Teams: Harnessing Generative AI for Inclusion and Diversity](https://mlsanity.com/paper/2402.00037/) (2024)
- [The AI Collaborator: Bridging Human-AI Interaction in Educational and Professional Settings](https://mlsanity.com/paper/2405.10460/) (2024)
- [Read the Room or Lead the Room: Understanding Socio-Cognitive Dynamics in Human-AI Teaming](https://mlsanity.com/paper/2510.09944/) (2025)
- [Personalities at Play: Probing Alignment in AI Teammates](https://mlsanity.com/paper/2603.00429/) (2026)

## Abstract (arXiv)

An AI teammate's design properties (personality, communication style, when it speaks) can shape a team's trust, coordination, and decisions. Studying this rigorously demands infrastructure no existing tool provides: reproducible configuration of an AI teammate embedded in instrumented, real-time collaboration sustained over time. We present the Team Research and AI Integration Lab (TRAIL), a web platform that makes the AI teammate a configurable, reproducible design object, pairing a Big Five persona with a selective-participation message pipeline, dual memory, chained longitudinal experiments, and export-ready analytics. In a real six-session classroom deployment (about 51 students), TRAIL sustained longitudinal chaining, held the AI to a stable minority of the conversation, and enabled export-driven AI-human text-similarity analysis. A single blind persona change produced a design-consistent double dissociation: a cognitive-scaffolding agent drew stronger contribution ratings and closer linguistic alignment; a socially-supportive agent, a warmer team climate and lower over-reliance.