arXiv Machine Learning
Sep 16

Divergence Timing and Cumulative Disagreement under KV-Cache Eviction

The paper studies how evicting entries from a KV‑cache affects the token distributions used in autoregressive language models. It derives an exact decomposition showing that the expected fraction of mismatched tokens equals a first‑mismatch contribution plus a post‑divergence exposure term weighted by its mismatch rate. Experiments on Meta‑Llama‑3.1‑8B‑Instruct and Qwen2.5‑7B‑Instruct demonstrate that a 50% retention strategy (SnapKV) delays divergence and reduces its frequency compared to other retention schemes, while post‑divergence total variation remains high and dominates the overall mismatch gap.

By Xinyue Luo, Fei Yu
arXiv AI
Oct 7

Monte Carlo Estimation for KV Cache Eviction

arXiv:2610.07643v1 Announce Type: cross Abstract: Most KV-cache eviction methods ask, in effect, which memory appeared important while reading the prompt? We instead ask, which memory will matter whi...

By Ahsan Bilal, Muhammad Ahmed Mohsin, Muhammad Umer, Wajih Hassan Raza, Atta Ul Asad, Young D. Kwon, Michal Valko, Dean F. Hougen
arXiv Machine Learning
Sep 30

Tail-Influence Sampling for CVaR Policy Evaluation

arXiv:2609.38096v1 Announce Type: new Abstract: Policies with similar mean returns can differ sharply in rare failures, yet estimating lower-tail conditional value-at-risk (CVaR) accurately can requi...

By Pauline Bourigault, Xiaotong Ji, Matthieu Zimmer, Rasul Tutunov, Haitham Bou-Ammar