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Maarten Sap

I am an assistant professor at CMU's LTI department with a courtesy appointment in HCII, and a part-time research scientist and AI safety lead at the Allen Institute for AI (AI2). My research focuses on (1) measuring and improving AI systems' social and interactional intelligence, (2) assessing and combatting social inequality, safety risks, and socio-cultural biases in human- or AI-generated language, and (3) building narrative language technologies for prosocial outcomes. I was named a 2025 Packard Fellow and a recipient of the 2025 Okawa Research Award.

I received my PhD from the University of Washington where I was advised by Noah Smith and Yejin Choi.
[bio for talks]

Recent updates:

December 2025 🏅📃: Very excited to have our paper Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond) selected for a Best Paper Award at NeurIPS 2025 (Datasets and Benchmarks Track)!! Huge congrats to the first author Liwei Jiang!!!

November 2025 💎🚀: Honored to be a Spring 2025 recipient of the Amazon Research Award for our project on measuring AI agentic safety!

October 2025 🏅⭐: I’m super excited and grateful to announce that I'm part of the 2025 class of Packard Fellows. The Packard Foundation and this fellowship will allow me to explore exciting research directions towards culturally responsible and safe AI 🌍🌈

October 2025 🔍🧑‍🎓: Due to my lab being quite full already, I'm not taking looking for any new students in this upcoming PhD application cycle 😟.

October 2025 🇨🇦🎉: Excited to be attending COLM 2025 in Montreal this October! I'll be giving a talk at the Social Sim Workshop on Unlocking Social Intelligence in AI agents. I'm also thrilled that five papers I co-authored will be presented by my amazing collaborators at COLM: HAICOSYSTEM: An Ecosystem for Sandboxing Safety Risks in Human-AI Interactions (led by Xuhui Zhou et al.), ALFA: Aligning LLMs to Ask Good Questions: A Case Study in Clinical Reasoning (co-led by Jimin Mun et al.), PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages, Fluid Language Model Benchmarking, and The Delta Learning Hypothesis: Preference Tuning on Weak Data can Yield Strong Gains.

August 2025 🌟: Incredibly honored to be one of 7 US recipients of the 2025 Okawa Research Grant from the Okawa Foundation!

August 2025 🧑‍🎓: Welcoming my first postdoc, Vasudha Varadarajan, to the lab!

[older news]

My research group:

Dan Chechelnitsky

CMU Portugal LTI PhD student
co-advised with Chrysoula Zerva

Joel Mire

LTI PhD student

Karina Halevy

LTI PhD student
co-advised with Mona Diab

Jimin Mun

LTI PhD student

Jocelyn Shen

MIT PhD student
co-advised with Cynthia Breazeal

Kynnedy Smith

HCII PhD student
co-advised with Motahhare Eslami

Vasudha Varadarajan

LTI Postdoc

Akhila Yerukola

LTI PhD student

Mingqian Zheng

LTI PhD student
co-advised with Carolyn Rosé

Xuhui Zhou

LTI PhD student

Overarching Research Themes

Themes extracted and images generated with the OpenAI API; there may be inconsistencies.

Ethics and Responsible AI

My research group explores the frameworks and methodologies for ensuring ethical considerations in AI development and deployment. One notable paper, [EVALUESTEER](https://arxiv.org/abs/2510.06370), presents a mechanism for measuring the steerability of reward models towards ethical values and preferences, thereby contributing to safer AI interactions. Additionally, the work titled [Let Them Down Easy!](https://arxiv.org/abs/2506.00195) examines how different contextual guardrails affect user perceptions of AI systems, highlighting the importance of ethical design in fostering trust. Our research also incorporates user-driven strategies, as seen in [Minion](https://arxiv.org/abs/2411.07042), which aims to reconcile conflicting values in AI companion applications.

Narrative Analysis and Empathy

My research group explores the impact of narratives on human experience and empathy in communication, especially through the lens of AI. A pivotal study, [Words Like Knives](https://arxiv.org/abs/2505.21451), investigates the personalized modeling of violent communication through the analysis of backstories, revealing how narrative context shapes the interpretation of aggressive language. Another important contribution, [HEART-felt Narratives](https://arxiv.org/abs/2405.17633), traces empathy and narrative style in personal stories using large language models (LLMs), enriching our understanding of storytelling's emotional impact. Additionally, our examination of the [Social Story Frames](https://aclanthology.org/2024.emnlp-main.1113/) further underlines how narrative perceptions vary across social media contexts.

Social Intelligence in AI Agents

My research group explores the development of AI agents that exhibit social intelligence and adaptability in human interactions. A significant work, [TOM-SWE](https://arxiv.org/abs/2510.21903), outlines methods for user mental modeling, crucial for software engineering agents' success. Similarly, the study on [OpenAgentSafety](https://arxiv.org/abs/2507.06134) proposes a comprehensive framework for evaluating the safety of AI agents in real-world interactions, ensuring their reliability and efficacy. Furthermore, our exploration of [SOTOPIA](https://arxiv.org/abs/2310.11667) showcases an interactive approach to assess social intelligence in language agents, pushing the boundaries of machine-human rapport.

Advances in Large Language Models

My research group explores innovative techniques to enhance the capabilities and safety of large language models (LLMs). The paper [Martingale Score](https://arxiv.org/abs/2512.02914) presents a new metric for evaluating Bayesian rationality in LLM reasoning, contributing to a deeper understanding of model behavior. Furthermore, we investigate effective alignment strategies in [ALFA](https://arxiv.org/abs/2502.14860), which focuses on improving LLMs' ability to ask pertinent questions in clinical scenarios. Additionally, the research presented in [PolyGuard](https://arxiv.org/abs/2504.04377) emphasizes the importance of multilingual safety moderation tools, ensuring safe and effective communication across languages.

More about me