Reward modeling often requires jointly representing and reasoning over multiple evaluation criteria, yet verbalizing this process token by token can incur substantial inference cost. Recent work on latent reasoning suggests that continuous states may support this computation more compactly. We introduce LatentGRM, a la...
Ming-Qing Yuan, Xiao-Bo Liang, Jun-Wei Yang et al.· 0 citations
Urban navigation requires embodied agents to pursue long-horizon goals through local decisions based on egocentric observations. However, existing agentic navigation methods often struggle to translate distant goals into coherent local decisions in large-scale physical environments. Their reliance on linguistic reasoni...
Jing Xie, Shou-Wei Ruan, Yu-Bin Wang et al.· 0 citations
Experiments show that existing GUI-WMs exhibit systematic failures under observation-only condition, while predictive-state augmentation substantially restores state-sensitive pre- diction across evaluated WMs, preserves generative fidelity, and improves down- stream performance of GUI agents on AndroidWorld.
Dong-Sheng Liu, Chao Jin, Wen-Kui Yang et al.· 0 citations
PerceptionBench provides a capability-level standard for measuring and diagnosing the visual perception boundaries of MLLMs, by diagnosing the earliest failure points in the responses of frontier MLLMs across 42 existing benchmarks and constructing an error taxonomy whose perception branch defines ten atomic perceptual...
