Transactional Attention: Semantic Sponsorship for KV-Cache Retention

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1. Verfasser: Basu, Abhinaba
Format: Preprint
Veröffentlicht: 2026
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author Basu, Abhinaba
author_facet Basu, Abhinaba
contents At K=16 tokens (0.4% of a 4K context), every existing KV-cache compression method achieves 0% on credential retrieval. The failure mode is dormant tokens: credentials, API keys, and configuration values that receive near-zero attention but become essential at generation time. Because these tokens lack the statistical signals that eviction policies rely on, no method based on attention scores, reconstruction loss, or learned retention gates retains them. We introduce Transactional Attention (TA), a sponsorship mechanism in which structural anchor patterns (e.g., "key:", "password:") protect adjacent value-bearing tokens from eviction. TA achieves 100% credential retrieval at K=16 where six baselines (H2O, TOVA, SnapKV, StreamingLLM, PyramidKV, DynamicKV) achieve 0%, and sustains 100% accuracy across 200 function-calling trials. TA-Fast, an attention-free variant, reduces memory overhead by 52% and is compatible with SDPA and FlashAttention. TA is orthogonal to existing compression methods and adds less than 1% latency overhead.
format Preprint
id arxiv_https___arxiv_org_abs_2604_11288
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Transactional Attention: Semantic Sponsorship for KV-Cache Retention
Basu, Abhinaba
Computation and Language
Machine Learning
68T50, 68T05
I.2.7; I.2.6
At K=16 tokens (0.4% of a 4K context), every existing KV-cache compression method achieves 0% on credential retrieval. The failure mode is dormant tokens: credentials, API keys, and configuration values that receive near-zero attention but become essential at generation time. Because these tokens lack the statistical signals that eviction policies rely on, no method based on attention scores, reconstruction loss, or learned retention gates retains them. We introduce Transactional Attention (TA), a sponsorship mechanism in which structural anchor patterns (e.g., "key:", "password:") protect adjacent value-bearing tokens from eviction. TA achieves 100% credential retrieval at K=16 where six baselines (H2O, TOVA, SnapKV, StreamingLLM, PyramidKV, DynamicKV) achieve 0%, and sustains 100% accuracy across 200 function-calling trials. TA-Fast, an attention-free variant, reduces memory overhead by 52% and is compatible with SDPA and FlashAttention. TA is orthogonal to existing compression methods and adds less than 1% latency overhead.
title Transactional Attention: Semantic Sponsorship for KV-Cache Retention
topic Computation and Language
Machine Learning
68T50, 68T05
I.2.7; I.2.6
url https://arxiv.org/abs/2604.11288