53 citations · 121 across the 9 of their papers we have counts for
9 papers
Data-Efficient Multitask DAgger
Haotian Fu, Ran Gong, Xiaohan Zhang +3
Generalist robot policies that can perform many tasks typically require extensive expert data or simulations for training. In this work, we propose a novel Data-Efficient multitask…
MindAgent: Emergent Gaming Interaction
Ran Gong, Qiuyuan Huang, Xiaojian Ma +8
Large Language Models (LLMs) have the capacity of performing complex scheduling in a multi-agent system and can coordinate these agents into completing sophisticated tasks that req…
LEMMA: Learning Language-Conditioned Multi-Robot Manipulation
Ran Gong, Xiaofeng Gao, Qiaozi Gao +3
Complex manipulation tasks often require robots with complementary capabilities to collaborate. We introduce a benchmark for LanguagE-Conditioned Multi-robot MAnipulation (LEMMA) f…
ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenes
Ran Gong, Jiangyong Huang, Yizhou Zhao +9
Understanding the continuous states of objects is essential for task learning and planning in the real world. However, most existing task learning benchmarks assume discrete (e.g.,…
DialFRED: Dialogue-Enabled Agents for Embodied Instruction Following
Xiaofeng Gao, Qiaozi Gao, Ran Gong +3
Language-guided Embodied AI benchmarks requiring an agent to navigate an environment and manipulate objects typically allow one-way communication: the human user gives a natural la…
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning
Pan Lu, Ran Gong, Shibiao Jiang +4
Geometry problem solving has attracted much attention in the NLP community recently. The task is challenging as it requires abstract problem understanding and symbolic reasoning wi…
SMART: A Situation Model for Algebra Story Problems via Attributed Grammar
Yining Hong, Qing Li, Ran Gong +3
Solving algebra story problems remains a challenging task in artificial intelligence, which requires a detailed understanding of real-world situations and a strong mathematical rea…
Joint Mind Modeling for Explanation Generation in Complex Human-Robot Collaborative Tasks
Xiaofeng Gao, Ran Gong, Yizhou Zhao +3
Human collaborators can effectively communicate with their partners to finish a common task by inferring each other's mental states (e.g., goals, beliefs, and desires). Such mind-a…
VRKitchen: an Interactive 3D Virtual Environment for Task-oriented Learning
Xiaofeng Gao, Ran Gong, Tianmin Shu +3
One of the main challenges of advancing task-oriented learning such as visual task planning and reinforcement learning is the lack of realistic and standardized environments for tr…