1 citations · 2 across the 8 of their papers we have counts for
9 papers
RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agents
Shuai Bai, Jiayong Deng, Sicheng Fan +30
Computer-use agents (CUAs) have advanced along two separate lines: graphical interaction and software development through code and the command line. Real digital work requires both…
Multi-Turn Reflective Masking Elicits Reasoning in Mask Diffusion Models
Yanming Zhang, Yihan Bian, Jingyuan Qi +3
While reasoning on autoregressive (AR) models is often performed by chain-of-thought reasoning and reflection, their refinement of previous outputs still relies on fully sequential…
What-If Analysis of Large Language Models: Explore the Game World Using Proactive Thinking
Yuan Sui, Yanming Zhang, Yi Liao +5
LLMs struggle with decision-making in high-stakes environments like MOBA games, primarily due to a lack of proactive reasoning and limited understanding of complex game dynamics. T…
XplainAct: Visualization for Personalized Intervention Insights
Yanming Zhang, Krishnakumar Hegde, Klaus Mueller
Causality helps people reason about and understand complex systems, particularly through what-if analyses that explore how interventions might alter outcomes. Although existing met…
V2Edit: Versatile Video Diffusion Editor for Videos and 3D Scenes
Yanming Zhang, Jun-Kun Chen, Jipeng Lyu +1
This paper introduces VEdit, a novel training-free framework for instruction-guided video and 3D scene editing. Addressing the critical challenge of balancing original content…
A Novel Approach to Eliminating Hallucinations in Large Language Model-Assisted Causal Discovery
Grace Sng, Yanming Zhang, Klaus Mueller
The increasing use of large language models (LLMs) in causal discovery as a substitute for human domain experts highlights the need for optimal model selection. This paper presents…
CausalChat: Interactive Causal Model Development and Refinement Using Large Language Models
Yanming Zhang, Akshith Kota, Eric Papenhausen +1
Causal networks are widely used in many fields to model the complex relationships between variables. A recent approach has sought to construct causal networks by leveraging the wis…
An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development
Yanming Zhang, Brette Fitzgibbon, Dino Garofolo +3
Causal networks are widely used in many fields, including epidemiology, social science, medicine, and engineering, to model the complex relationships between variables. While it ca…
Controllable Textual Inversion for Personalized Text-to-Image Generation
Jianan Yang, Haobo Wang, Yanming Zhang +4
The recent large-scale generative modeling has attained unprecedented performance especially in producing high-fidelity images driven by text prompts. Text inversion (TI), alongsid…