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Jun-Hao Hu

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Preprint Aug 2026

GDPevo: Evaluating Agent Self-Evolution on Real Business Tasks

Agent self-evolution updates an agent's persistent state from prior experience and reuses it to solve related tasks more effectively. Evaluating self-evolution is difficult: existing benchmarks provide limited coverage of economically valuable task domains, do not always design training and test tasks such that test-ti...

Leijun Zhou, Zhihao Liu, Xiang Qu et al. · 1 citation
Preprint Aug 2026

CoRun: Padding is Simple and Efficient for Deterministic LLM Inference

CoRun is presented, a scheduling-based system that achieves deterministic inference without requiring batch invariance, and employs isolated prefill and fixed-shape batched decode to handle the two stages of LLM inference, respectively, leveraging CUDA graphs for efficient execution and simplified implementation.

Shiju Zhao, Jiacheng Yang, Qi-Hang Chen et al. · 0 citations
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

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