6 papers
When Robots Do the Chores: A Benchmark and Agent for Long-Horizon Household Task Execution
Zilin Zhu, Longteng Guo, Yanghong Mei +5
Long-horizon household tasks demand robust high-level planning and sustained reasoning capabilities, which are largely overlooked by existing embodied AI benchmarks that emphasize…
Temper and Tilt Lead to SLOP: Reward Hacking Mitigation with Inference-Time Alignment
Ye Wang, Jing Liu, Toshiaki Koike-Akino
Inference-time alignment techniques offer a lightweight alternative or complement to costly reinforcement learning, while enabling continual adaptation as alignment objectives and…
Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems
Jing Liu, Yangyang Yang, Luca Ballotta +3
This paper studies multi-agent reinforcement learning with submodular team utilities for online distributed task allocation. In this setting, each agent selects one action from a l…
Embedding Morphology into Transformers for Cross-Robot Policy Learning
Kei Suzuki, Jing Liu, Ye Wang +4
Cross-robot policy learning -- training a single policy to perform well across multiple embodiments -- remains a central challenge in robot learning. Transformer-based policies, su…
COSMO: Combination of Selective Memorization for Low-cost Vision-and-Language Navigation
Siqi Zhang, Yanyuan Qiao, Qunbo Wang +4
Vision-and-Language Navigation (VLN) tasks have gained prominence within artificial intelligence research due to their potential application in fields like home assistants. Many co…
FlexVLN: Flexible Adaptation for Diverse Vision-and-Language Navigation Tasks
Siqi Zhang, Yanyuan Qiao, Qunbo Wang +3
The aspiration of the Vision-and-Language Navigation (VLN) task has long been to develop an embodied agent with robust adaptability, capable of seamlessly transferring its navigati…