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#machine learning Preprint Sep 2026

Budgeted Cache Repair for Cross-Context KV-Cache Reuse

Cross-context KV-cache reuse predicts a shared segment's keys and values under a new prefix instead of recomputing them, and has been reported to do so without quality loss. We find otherwise, and identify two problems. (1) A hidden cost: on MMLU and GSM8K, reuse costs substantial accuracy. (2) A decision at the wrong...

Haeyong Kang, C. D. Yoo · 0 citations
#small language model Preprint Sep 2026

Event-Driven Refresh and Recurrence Memory to Reduce Stale Grounding in Referring Video Object Segmentation

End-to-end runtime analysis further confirms that the overhead introduced by tracking, CLIP-based recurrence matching, and the identifiability gate remains modest relative to the dominant Sa2VA inference cost, thereby validating the efficiency of the proposed pipeline.

Abu Hanif Muhammad Syarubany, Jaehyun Jang, Si-Woo Lim et al. · 0 citations
#machine learning Preprint Sep 2026

When to Evict, Not What to Keep: Draft-Guided Eviction for Training-Free KV-Cache Compression

Training-free KV-cache compression methods such as SnapKV, H2O, and PyramidKV evict tokens at the end of prefill, aiming to preserve the attention mass that future queries are expected to use -optimizing what to keep. We show that this objective fails in two distinct ways. (1) Compensation: restoring the evicted attent...

Haeyong Kang, C. D. Yoo · 0 citations

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