Prune long-horizon agent context by KV-cache value, not just recency (TokenPilot)

arXiv·medium signal

TokenPilot (arXiv 2606.17016, June 2026) manages context by ranking tokens on combined attention-pattern importance and recency, then selectively retaining high-value tokens in the KV cache while evicting low-value history — dynamically sizing the cache to available memory. Unlike threshold- or boundary-based compaction, this targets the cache itself, cutting memory overhead and improving throughput on multi-turn agents that would otherwise blow up GPU memory. Practical step: profile your inference loop for cache bottlenecks first, then apply importance-ranked eviction.