2 papers
cs.CL2026
HiNS: Hierarchical Negative Sampling for More Comprehensive Memory Retrieval Embedding Model
Motong Tian, Allen P. Wong, Mingjun Mao +1
Memory-augmented language agents rely on embedding models for effective memory retrieval. However, existing training data construction overlooks a critical limitation: the hierarch…
cs.CL2025
OceanGym: A Benchmark Environment for Underwater Embodied Agents
Yida Xue, Mingjun Mao, Xiangyuan Ru +9
We introduce OceanGym, the first comprehensive benchmark for ocean underwater embodied agents, designed to advance AI in one of the most demanding real-world environments. Unlike t…