Author

Zhao-Kai Luo

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Jul 2026

Hierarchical Latent Reasoning for LLM-based Recommendation

To further optimize the reasoning trajectory, HiLaR combines final recommendation feedback with layer-aware process rewards derived from the marginal target-likelihood gain of each state, and generally outperforms strong sequential, generative, and LLM-based recommendation baselines.

Pei-Yu Hu, Si-Ying Gu, Wei-Hai Lu et al. · arXiv.org · 1 citation

Preprint Jul 2026

Akashic: A Low-Overhead LLM Inference Service with MemAttention

This work proposes Akashic, a low-overhead memory system built around MemAttention, which organizes context into bounded chunks and models semantic relationships across chunks, preserving cross-chunk evidence without repeatedly rewriting the full history.

Yang Liu, ZhaoKai Luo, Huayi Jin et al. · 0 citations