2 citations · 2 across the 11 of their papers we have counts for
7 papers · 1 filter
MetaPersona: Task-Grounded Synthetic Populations from Empirical Social Science
Jinyi Ye, Yuangang Li, Chenxiao Yu +7
Personas used to seed LLM social simulations face a cold-start problem: existing methods lack a principled basis for deciding which attributes to include and how to assign their va…
De-conflating Preference and Qualification: Constrained Dual-Perspective Reasoning for Job Recommendation with Large Language Models
Bryce Kan, Wei Yang, Emily Nguyen +4
Professional job recommendation involves a complex bipartite matching process that must reconcile a candidate's subjective preference with an employer's objective qualification. Wh…
"Someone Hid It": Query-Agnostic Black-Box Attacks on LLM-Based Retrieval
Jiate Li, Defu Cao, Li Li +8
Large language models (LLMs) have been serving as effective backbones for retrieval systems, including Retrieval-Augmentation-Generation (RAG), Dense Information Retriever (IR), an…
Defenses Against Prompt Attacks Learn Surface Heuristics
Shawn Li, Chenxiao Yu, Zhiyu Ni +4
Large language models (LLMs) are increasingly deployed in security-sensitive applications, where they must follow system- or developer-specified instructions that define the intend…
Multimodal Generative Engine Optimization: Rank Manipulation for Vision-Language Model Rankers
Yixuan Du, Chenxiao Yu, Haoyan Xu +3
Vision-Language Models (VLMs) integrate visual and textual knowledge into unified representations that increasingly underpin modern retrieval and recommendation systems. However, i…
Tracing Moral Foundations in Large Language Models
Chenxiao Yu, Bowen Yi, Farzan Karimi-Malekabadi +5
Large language models often produce human-like moral judgments, but it is unclear whether this reflects an internal conceptual structure or superficial ``moral mimicry.'' Using Mor…
Value-Action Alignment in Large Language Models under Privacy-Prosocial Conflict
Guanyu Chen, Chenxiao Yu, Xiyang Hu
Large language models (LLMs) are increasingly used to simulate decision-making tasks involving personal data sharing, where privacy concerns and prosocial motivations can push choi…