6 citations · 7 across the 14 of their papers we have counts for
17 papers
WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation
Peterson Co, Sicheng Hu, Chunxuan Jiao +17
Action-conditioned world models (ACWMs) promise to provide embodied AI with scalable predictive simulators for planning, policy evaluation, and data generation. Realizing this prom…
Decoupling Intention from Trajectory: A Representational Deduction Framework for World Action Models
Xiangkai Ma, Yue Ma, Junjie Wang +6
World Action Models (WAMs) aim to construct a unified architecture capable of understanding world state evolution and guiding to generative motion planning. However, existing visua…
JoyAI-Sim: A Simulation-Enabled Interconversion Toolchain for the Embodied Data Pyramid
Peidong Liu, Yongce Liu, Songyan Guo +34
Generalist robot policies require trustworthy evaluation and robot-usable training data, but both are difficult to scale with physical robots alone. Real-robot trials and demonstra…
Towards Valid Student Simulation with Large Language Models
Zhihao Yuan, Yunze Xiao, Ming Li +4
This paper presents a conceptual and methodological framework for large language model (LLM) based student simulation in educational settings. The authors identify a core failure m…
Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM Agents
Yueqi Song, Ketan Ramaneti, Zaid Sheikh +18
Public research results on large-scale supervised finetuning of AI agents remain relatively rare, since the collection of agent training data presents unique challenges. In this wo…
See the Forest and the Trees: A Synergistic Reasoning Framework for Knowledge-Based Visual Question Answering
Junjie Wang, Yunhan Tang, Yijie Wang +4
Multimodal Large Language Models (MLLMs) have pushed the frontiers of Knowledge-Based Visual Question Answering (KBVQA), yet their reasoning is fundamentally bottlenecked by a reli…