most citedLLMR: Real-time Prompting of Interactive Worlds using Large Language Models

10 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

AI emotional support is better only when chosen, but shifts preferences even when it is not

Yaoxi Shi, Cathy Mengying Fang, Guy LabanPattie Maes +1

People increasingly face a novel decision when seeking emotional support: human or AI. In existing studies, AI's empathic messages are rated as well as or better than humans'. But…

cs.AI2026

Stumbling Into AI Emotional Dependence: How Routine AI Interactions Reshape Human Connection

Yaoxi Shi, Cathy Mengying Fang, Pattie Maez +1

Public discourse and emerging policy typically assume that AI emotional support is a deliberate act: a lonely user consciously seeking comfort from a dedicated companion chatbot. I…

cs.CL2026

ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions

Chuanyang Jin, Binze Li, Haopeng Xie +6

Conversational AI has now reached billions of users, yet existing datasets capture only what people say, not what they think. We introduce ThoughtTrace, the first large-scale datas…

cs.GR2023

Real-time Animation Generation and Control on Rigged Models via Large Language Models

Han Huang, Fernanda De La Torre, Cathy Mengying Fang +3

We introduce a novel method for real-time animation control and generation on rigged models using natural language input. First, we embed a large language model (LLM) in Unity to o…

cs.HC2023★ 10 cited

LLMR: Real-time Prompting of Interactive Worlds using Large Language Models

Fernanda De La Torre, Cathy Mengying Fang, Han Huang +3

We present Large Language Model for Mixed Reality (LLMR), a framework for the real-time creation and modification of interactive Mixed Reality experiences using LLMs. LLMR leverage…