Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective
Quick summary
arXiv:2604.25975v2 Announce Type: replace-cross Abstract: Key-Value (KV) caching is essential for large language model inference, yet its memory overhead poses a critical bottleneck for long-context generation. Existing eviction policies predominantly rely on empirical heuristics, lacking a rigorous theoretical foundation. This work rethinks KV cache eviction through the lens of the Information Bottleneck principle. Under a linear-Gaussian surrogate of attention, we derive a closed-form mutual information objective that characterizes the effective information capacity of a retained KV cache su
Key takeaways
- arXiv:2604.25975v2 Announce Type: replace-cross Abstract: Key-Value (KV) caching is essential for large language model inference, yet its memory overhead poses a critical bottleneck for long-context generation.
- Existing eviction policies predominantly rely on empirical heuristics, lacking a rigorous theoretical foundation.
- This work rethinks KV cache eviction through the lens of the Information Bottleneck principle.
Why it matters
This model development creates a new option for users and a new testing obligation for developers. A fixed evaluation set comparing quality, cost and failure behavior is more useful than launch claims.
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