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 across various datasets indicate that the proposed method achieves superior reasoning accuracy without compromising, and even facilitating, the overall accuracy, and ablation studies show that the proposed mechanisms can provide flexible control interfaces for the tradeoff between the reasoning accuracy and...
Yufeng Shi, Weilin Luo, Yuxiang Zhang et al.· Annual Meeting of the Associ...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.