RDKV derives per-token and per-channel weights from attention distortion, then uses reverse water-filling to assign bit-widths from full precision to zero after prefilling, recovering 97.81% accuracy with 2.48% cache retention on LongBench.
LongBench: A bilingual, multitask benchmark for long context understanding
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A fixed-contract probe shows value-aware KV eviction recovers needed evidence in 72.6% of accuracy-improving cases on LongBench but only 32.4% otherwise, suggesting an order of recover evidence, rank value, then preserve couplings.
citing papers explorer
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RDKV: Rate-Distortion Bit Allocation for Joint Eviction and Quantization of the KV Cache
RDKV derives per-token and per-channel weights from attention distortion, then uses reverse water-filling to assign bit-widths from full precision to zero after prefilling, recovering 97.81% accuracy with 2.48% cache retention on LongBench.
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When Does Value-Aware KV Eviction Help? A Fixed-Contract Diagnostic for Non-Monotone Cache Compression
A fixed-contract probe shows value-aware KV eviction recovers needed evidence in 72.6% of accuracy-improving cases on LongBench but only 32.4% otherwise, suggesting an order of recover evidence, rank value, then preserve couplings.