Author

Jun-Cheng Yang

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#artificial intelligence Preprint Sep 2026

HeadWiseKV: Budgeted Per-Head Cache Residency for Hybrid Long-Context Language Models

This work introduces HeadWiseKV, a training-free framework that compresses the residual global KV caches of hybrid language models while preserving their native local, recurrent, and linear paths and proposes SeqCalib as the core policy-generation algorithm in HeadWiseKV.

Ren-Jie Xie, Jun-Cheng Yang, Ao-Ting Hu et al. · 0 citations

Preprint Jul 2026

A Year in LLM Serving: Workload Evolution, Caching and Load-Balancing

This work further the understanding of real-world LLM serving workloads through both a global characterization and a longitudinal study of a one-year production trace from Chutes, revealing workload evolution and user-model structure that are typically hidden behind aggregate views.

William Nixon, Jon Durbin, Florian Standhartinger et al. · 0 citations