12 citations · 45 across the 18 of their papers we have counts for
18 papers
FinTrace: Holistic Trajectory-Level Evaluation of LLM Tool Calling for Long-Horizon Financial Tasks
Yupeng Cao, Haohang Li, Weijin Liu +11
Recent studies demonstrate that tool-calling capability enables large language models (LLMs) to interact with external environments for long-horizon financial tasks. While existing…
Truth Neurons
Haohang Li, Yupeng Cao, Yangyang Yu +2
Despite their remarkable success and deployment across diverse workflows, language models sometimes produce untruthful responses. Our limited understanding of how truthfulness is m…
Replicating Human Social Perception in Generative AI: Evaluating the Valence-Dominance Model
Necdet Gurkan, Kimathi Njoki, Jordan W. Suchow
As artificial intelligence (AI) continues to advance--particularly in generative models--an open question is whether these systems can replicate foundational models of human social…
INVESTORBENCH: A Benchmark for Financial Decision-Making Tasks with LLM-based Agent
Haohang Li, Yupeng Cao, Yangyang Yu +12
Recent advancements have underscored the potential of large language model (LLM)-based agents in financial decision-making. Despite this progress, the field currently encounters tw…
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Jimin Huang, Mengxi Xiao, Dong Li +41
Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow ev…
FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making
Yangyang Yu, Zhiyuan Yao, Haohang Li +14
Large language models (LLMs) have demonstrated notable potential in conducting complex tasks and are increasingly utilized in various financial applications. However, high-quality…
Exploring Public Opinion on Responsible AI Through The Lens of Cultural Consensus Theory
Necdet Gurkan, Jordan W. Suchow
As the societal implications of Artificial Intelligence (AI) continue to grow, the pursuit of responsible AI necessitates public engagement in its development and governance proces…
Evaluating Large Language Models on the GMAT: Implications for the Future of Business Education
Vahid Ashrafimoghari, Necdet Gürkan, Jordan W. Suchow
The rapid evolution of artificial intelligence (AI), especially in the domain of Large Language Models (LLMs) and generative AI, has opened new avenues for application across vario…
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
Yangyang Yu, Haohang Li, Zhi Chen +6
Recent advancements in Large Language Models (LLMs) have exhibited notable efficacy in question-answering (QA) tasks across diverse domains. Their prowess in integrating extensive…
Harnessing Collective Intelligence Under a Lack of Cultural Consensus
Necdet Gürkan, Jordan W. Suchow
Harnessing collective intelligence to drive effective decision-making and collaboration benefits from the ability to detect and characterize heterogeneity in consensus beliefs. Thi…
Actively learning a Bayesian matrix fusion model with deep side information
Yangyang Yu, Jordan W. Suchow
High-dimensional deep neural network representations of images and concepts can be aligned to predict human annotations of diverse stimuli. However, such alignment requires the cos…
The Design and Operation of Digital Platform under Sociotechnical Folk Theories
Jordan W. Suchow, Lea Burton, Vahid Ashrafimoghari
We consider the problem of how a platform designer, owner, or operator can improve the design and operation of a digital platform by leveraging a computational cognitive model that…
Coincidental Generation
Jordan W. Suchow, Necdet Gürkan
Generative A.I. models have emerged as versatile tools across diverse industries, with applications in privacy-preserving data sharing, computational art, personalization of produc…
A Game-theoretic Model of the Consumer Behavior Under Pay-What-You-Want Pricing Strategy
Vahid Ashrafimoghari, Jordan W. Suchow
In a digital age where companies face rapid changes in technology, consumer trends, and business environments, there is a critical need for continual revision of the business model…
Evaluation of Human and Machine Face Detection using a Novel Distinctive Human Appearance Dataset
Necdet Gurkan, Jordan W. Suchow
Face detection is a long-standing challenge in the field of computer vision, with the ultimate goal being to accurately localize human faces in an unconstrained environment. There…
Adaptive Sampling for Convex Regression
Max Simchowitz, Kevin Jamieson, Jordan W. Suchow +1
In this paper, we introduce the first principled adaptive-sampling procedure for learning a convex function in the norm, a problem that arises often in the behavioral an…
Learning a face space for experiments on human identity
Jordan W. Suchow, Joshua C. Peterson, Thomas L. Griffiths
Generative models of human identity and appearance have broad applicability to behavioral science and technology, but the exquisite sensitivity of human face perception means that…
Capturing human category representations by sampling in deep feature spaces
Joshua C. Peterson, Jordan W. Suchow, Krisha Aghi +2
Understanding how people represent categories is a core problem in cognitive science. Decades of research have yielded a variety of formal theories of categories, but validating th…