Natalia Vélez

Datos Biográficos

ID1833409
NOMBRENatalia Vélez
NOMBRESNatalia
APELLIDOVélez
FIRMAVÉLEZ N
AFILIACIONESPrinceton University
ORCID0000-0002-6939-3282
VERIFICADOSí
TOTAL DE OBRAS8
TOTAL DE CITAS4
TOTAL COMO AUTOR8
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2020
AÑO MÁS RECIENTE DE PUBLICACIÓN2026
ÍNDICE H1

  • Embodied LLM Agents Learn to Cooperate in Organized Teams

    Open AccessXudong Guo, Kaixuan Huang et al.ARTICLEIEEE Transactions on Computational…2026

    Large language models (LLMs) have emerged as integral tools for reasoning, planning, and decision-making, drawing upon their extensive world knowledge and proficiency in language-related tasks. LLMs thus hold tremendous potential for natural language interaction within multiagent systems to foster cooperation. However, LLM agents tend to over-report and comply with any instruction, which may result in information redundancy and confusion in multi…

  • People evaluate idle collaborators based on their impact on task efficiency

    Open AccessElizabeth Mieczkowski, Cameron Rouse Turner et al.ARTICLECognition2025

    Humans collaborate to improve productivity, but when is it acceptable for a collaborator to remain idle? Theories from distributed computer systems suggest that, depending on the task structure, division of labor leads to diminishing returns in efficiency as group size increases. We examine whether people are aware of these limitations to collaboration, and how considerations of task efficiency may affect the perceived acceptability of idleness, …

  • Teaching Recombinable Motifs Through Simple Examples

    Open AccessHuang Ham, Bonan Zhao et al.ARTICLECognitive Science2025Referencias: 40

    A hallmark of effective teaching is that it grants learners not just a collection of facts about the world, but also a toolkit of abstractions that can be applied to solve new problems. How do humans teach abstractions from examples? Here, we applied Bayesian models of pedagogy to a necklace‐building task where teachers create necklaces to teach a learner “motifs” that can be flexibly recombined to create new necklaces. In Experiment 1 ( N = 151)…

  • Optimizing competence in the service of collaboration

    Open AccessYang Xiang, Natalia Vélez et al.ARTICLECognitive Psychology2024

  • People reward others based on their willingness to exert effort

    Open AccessYang Xiang, Jenna Landy et al.ARTICLEJournal of Experimental Social…2024Referencias: 2

  • Using games to understand the mind

    Open AccessKelsey Allen, Franziska Brändle et al.ARTICLENature Human Behaviour2024Citada por: 4Referencias: 65

  • Actual and counterfactual effort contribute to responsibility attributions in collaborative tasks

    Open AccessYang Xiang, Jenna Landy et al.ARTICLECognition2023

  • Learning from other minds

    Natalia Vélez, Hyowon GweonPREPRINT2020

    In the past decade, reinforcement learning models have been productively applied to examine neural signatures that track the value of social information over repeated observations. However, by operationalizing social information as a lean, reward-predictive cue, this literature underestimates the richness of human social learning: Humans readily go beyond action-outcome mappings and can draw flexible inferences even from a single observation. We …