51 citations · 122 across the 19 of their papers we have counts for
19 papers
Modeling Human Behavior with Type Vectors Using AI
Matthew O. Jackson, Benjamin S. Manning, Yutong Xie +2
We introduce a general, easy-to-implement AI-based modeling technique for analyzing human behavior. A key feature of this approach, which contrasts with existing modeling technique…
BehaviorBench: Benchmarking Foundation Models for Behavioral Science Tasks
Jin Huang, Yutong Xie, Wanli Song +5
Foundation models have been increasingly applied to behavioral science domains such as psychology, sociology, and economics. While these models show promise in tasks such as survey…
IRIS: time-structured manifold projections
Brian Ondov, Chia-Hsuan Chang, Weipeng Zhou +6
High-dimensional biomedical data, such as cell-by-gene matrices, are increasingly generated temporally. However, Manifold Learning algorithms, like t-SNE and UMAP, cannot incorpora…
MedViz: An Agent-based, Visual-guided Research Assistant for Navigating Biomedical Literature
Huan He, Xueqing Peng, Yutong Xie +6
Biomedical researchers face increasing challenges in navigating millions of publications in diverse domains. Traditional search engines typically return articles as ranked text lis…
Be.FM: Open Foundation Models for Human Behavior
Yutong Xie, Zhuoheng Li, Xiyuan Wang +10
Despite their success in numerous fields, the potential of foundation models for modeling and understanding human behavior remains largely unexplored. We introduce Be.FM, one of th…
Using Large Language Models to Categorize Strategic Situations and Decipher Motivations Behind Human Behaviors
Yutong Xie, Qiaozhu Mei, Walter Yuan +1
By varying prompts to a large language model, we can elicit the full range of human behaviors in a variety of different scenarios in classic economic games. By analyzing which prom…
How Different AI Chatbots Behave? Benchmarking Large Language Models in Behavioral Economics Games
Yutong Xie, Yiyao Liu, Zhuang Ma +5
The deployment of large language models (LLMs) in diverse applications requires a thorough understanding of their decision-making strategies and behavioral patterns. As a supplemen…
MapExplorer: New Content Generation from Low-Dimensional Visualizations
Xingjian Zhang, Ziyang Xiong, Shixuan Liu +6
Low-dimensional visualizations, or "projection maps," are widely used in scientific and creative domains to interpret large-scale and complex datasets. These visualizations not onl…
Bridging AI and Science: Implications from a Large-Scale Literature Analysis of AI4Science
Yutong Xie, Yijun Pan, Hua Xu +1
Artificial Intelligence has proven to be a transformative tool for advancing scientific research across a wide range of disciplines. However, a significant gap still exists between…
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows
Xingjian Zhang, Yutong Xie, Jin Huang +8
Scientific innovation relies on detailed workflows, which include critical steps such as analyzing literature, generating ideas, validating these ideas, interpreting results, and i…
Position: Towards Bidirectional Human-AI Alignment
Hua Shen, Tiffany Knearem, Reshmi Ghosh +21
Recent advances in general-purpose AI underscore the urgent need to align AI systems with human goals and values. Yet, the lack of a clear, shared understanding of what constitutes…
A Turing Test: Are AI Chatbots Behaviorally Similar to Humans?
Qiaozhu Mei, Yutong Xie, Walter Yuan +1
We administer a Turing Test to AI Chatbots. We examine how Chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairnes…
A Prompt Log Analysis of Text-to-Image Generation Systems
Yutong Xie, Zhaoying Pan, Jinge Ma +2
Recent developments in large language models (LLM) and generative AI have unleashed the astonishing capabilities of text-to-image generation systems to synthesize high-quality imag…
Diffusion Model for Generative Image Denoising
Yutong Xie, Minne Yuan, Bin Dong +1
In supervised learning for image denoising, usually the paired clean images and noisy images are collected or synthesised to train a denoising model. L2 norm loss or other distance…
Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation
Hexin Dong, Zifan Chen, Mingze Yuan +5
As one of the most challenging and practical segmentation tasks, open-world semantic segmentation requires the model to segment the anomaly regions in the images and incrementally…
Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection
Ting Long, Yutong Xie, Xianyu Chen +3
Program representation, which aims at converting program source code into vectors with automatically extracted features, is a fundamental problem in programming language processing…
How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules
Yutong Xie, Ziqiao Xu, Jiaqi Ma +1
Forming a molecular candidate set that contains a wide range of potentially effective compounds is crucial to the success of drug discovery. While most databases and machine-learni…
MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Yutong Xie, Chence Shi, Hao Zhou +4
Searching for novel molecules with desired chemical properties is crucial in drug discovery. Existing work focuses on developing neural models to generate either molecular sequence…
Visual Rhythm Prediction with Feature-Aligning Network
Yutong Xie, Haiyang Wang, Yan Hao +1
In this paper, we propose a data-driven visual rhythm prediction method, which overcomes the previous works' deficiency that predictions are made primarily by human-crafted hard ru…