Runqi Zou

Runqi Zou

I'm a researcher in human-computer interaction and computational cognitive science. I'm interested in cognition, behavior, and the ways intelligent systems influence how people perceive, decide, and interact. Across my projects, I focus on connecting technical implementation with questions about human cognition.

I'm a research assistant with Julian Togelius in the Game Innovation Lab at the NYU Department of Computer Science and Engineering, and with Laurence Maloney in the Decision Lab at the NYU Department of Psychology and Center for Neural Science.

News

  • Oct 2026

    Language as Trait, Politeness as Strategy, a follow-up to LURK Werewolf on linguistic effects in LLM social-deduction agents, was submitted to NAACL 2027.

  • Jun 2026

    LURK Werewolf was accepted for an oral presentation at the IEEE Conference on Games 2026.

  • Jun 2026

    A manuscript on structure detection and event prediction in binary sequences, with M. Dal Martello and L. Maloney, is in preparation.

  • Apr 2026

    Aligned Information Bottleneck for Multimodal Social Sentiment Analysis was published in IEEE Transactions on Computational Social Systems.

  • Dec 2025

    PureMetric received an Honorable Mention at the International Design Awards.

Publications & Manuscripts

† Equal contribution  ·  * Corresponding authors

  1. 2026

    Language as Trait, Politeness as Strategy: Controlled Tests of Linguistic Effects in LLM Social-Deduction Agents

    Li, Y.†, Liu, L.†, Zou, R., Kuang, S., Zhang, Q., & Togelius, J.*

    Manuscript submitted to NAACL 2027

  2. 2026

    What good is classifying the generator when the best prediction never changes?

    Zou, R., Dal Martello, M.*, & Maloney, L.*

    Manuscript in Preparation

  3. 2026

    LURK Werewolf: Evaluating Linguistic Bias in Large Language Models

    Zou, R.†, Liu, L.†, Kuang, S., Li, Y., Merino, T., & Togelius, J.*

    IEEE Conference on Games (CoG 2026) · Oral Presentation

  4. 2026

    Aligned Information Bottleneck for Multimodal Social Sentiment Analysis

    Zou, R., Zhang, J., Ren, A., Wang, W., Gao, Z., Wu, J.*, & He, K.*

    IEEE Transactions on Computational Social Systems

Research

2026
Language as Trait, Politeness as Strategy Coming Soon

Language as Trait, Politeness as Strategy: Controlled Tests of Linguistic Effects in LLM Social-Deduction Agents

A follow-up study on the LURK framework. It treats language as a fixed trait of an agent and politeness as a strategy an agent can choose, and runs controlled tests of how each changes credibility and voting when LLM agents play social deduction games.

LLM Bias Analysis Python Game Design Under Review · NAACL 2027
2026
Binary sequence prediction Coming Soon

What good is classifying the generator when the best prediction never changes?

Behavioral experiments and Markov chain models of how people detect structure in binary sequences and predict what comes next.

Sequential Prediction Cognitive Modeling Markov Models Python In Progress
2026
LURK Werewolf

LURK Werewolf: Evaluating Linguistic Bias in Large Language Models

→

A Werewolf framework for testing whether LLM agents react to meaning or to wording. Moving agents from logic predicates to natural language changed 52.6% of later decisions in 7-player games.

LLM Multi-Agent Social Deduction Python IEEE CoG 2026 Oral
Apr 2026
Aligned IB

Aligned Information Bottleneck for Multimodal Social Sentiment Analysis

→

A text-anchored information bottleneck for sentiment analysis across video, audio, and text. Improves over strong baselines on the MOSI and MOSEI benchmarks and stays more robust under modality noise and imbalance.

Affective Computing Multimodal Fusion PyTorch IEEE TCSS

Selected Design Work

Awards

  • 2025

    International Design Awards, Honorable Mention

    Product Design (Smart Home Products)

  • 2025

    A' Design Award, Winner

    Installation Design

  • 2024

    Muse Award, Silver Winner

    Product Design (Wearable Technologies)