activity
20242026
collaborators

10 papers

cs.CY2026

Mapping the Emerging Social Science of Large Language Models

Yi Yang, Xiao Jia, Zeyun Dong +2

Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these developments remains fragmented…

cs.CV2026

Revealing Training Data Exposure in Vision Language Large Models via Parameter Gradients

Zhihao Zhu, Hongyi Tang, Yi Yang +1

Vision-Language Large Models (VLLMs) trained on massive crawled corpora raise pressing copyright and data-provenance concerns. These concerns are particularly acute in healthcare,…

cs.AI2026

Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement

Jinyuan Wang, Ningyuan Deng, Yi Yang

Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables that can enter standard empirical…

cs.CV2026

A Picture is Worth a Thousand Words? An Empirical Study of Aggregation Strategies for Visual Financial Document Retrieval

Ho Hung Lim, Yi Yang

Visual RAG has offered an alternative to traditional RAG. It treats documents as images and uses vision encoders to obtain vision patch tokens. However, hundreds of patch tokens pe…

cs.LG2026

Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs

Jingzhou Jiang, Yi Yang, Kar Yan Tam

Hidden states change substantially across the layers of modern language models, but most layer-wise analyses focus on one aspect of that change. We propose Layer-wise Representatio…

cs.CV2026

DistractMIA: Black-Box Membership Inference on Vision-Language Models via Semantic Distraction

Hongyi Tang, Zhihao Zhu, Yi Yang

Vision-language models (VLMs) are trained on large-scale image-text corpora that may contain private, copyrighted, or otherwise sensitive data, motivating membership inference as a…

cs.LG2025

Ready2Unlearn: A Learning-Time Approach for Preparing Models with Future Unlearning Readiness

Hanyu Duan, Yi Yang, Ahmed Abbasi +1

Machine unlearning is the process of removing the imprint left by specific data samples during the training of a machine learning model. AI developers, including those building per…

econ.GN2025

Evaluating and Aligning Human Economic Risk Preferences in LLMs

Jiaxin Liu, Yixuan Tang, Yi Yang +1

Large Language Models (LLMs) are increasingly used in decision-making scenarios that involve risk assessment, yet their alignment with human economic rationality remains unclear. I…

cs.LG2025

Robust Predictive Modeling Under Unseen Data Distribution Shifts: A Methodological Commentary

Hanyu Duan, Yi Yang, Ahmed Abbasi +1

Most research designing novel predictive models, or employing existing ones, assumes that training and testing data are independent and identically distributed. In practice, the da…

cs.CL2024

LLM-Measure: Generating Valid, Consistent, and Reproducible Text-Based Measures for Social Science Research

Yi Yang, Hanyu Duan, Jiaxin Liu +1

The increasing use of text as data in social science research necessitates the development of valid, consistent, reproducible, and efficient methods for generating text-based conce…