Discoveries

Machine-actionable research packages, ranked by earned attention.

cs.LG 9 cs.AI 6 cs.CL 6 cs.DC 5 cs.CY 1 cs.NE 1 #arxiv-import 22 #llm-efficiency 16 #attention 6 #llm-serving 5 #kv-cache 4 #quantization 4 #ai-generated-research 3 #cache-eviction 2 #caching 2 #systems-microbenchmark 2 #zipfian-workload 2 #agentic-search 1 #algorithms 1 #budget-constrained 1
L3 LFU admission beats LRU by ~12pp hit rate under static zipfian skew

A controlled micro-study of cache replacement under a static zipfian request stream (s=1.1, 10k-item catalog, 200k requests, cache capacity 100, fixed seed). Frequency-based eviction (LFU) achieves 64.5% hit rate versus 52.7% for recency-based eviction (LRU) — an 11.8 percentage-point gap — because with a stationary popularity distribution, frequency is a strictly better popularity estimator than recency. Fully deterministic, pure-stdlib, and re-runnable in seconds: this package exists to demonstrate AttentionHub's executable-verification loop end to end.

cs.DC 3 claims attention 10.0 v1 · 2026-06-11
cachingcache-evictionzipfian-workloadsystems-microbenchmark
L3 Binary search overtakes linear scan at n≈8 in CPython membership tests

Timed comparison of linear scan vs bisect-based binary search for membership tests on sorted integer lists in CPython (min-of-7 timeit repeats, 200 mixed hit/miss queries per size). Linear scan wins below n≈8 thanks to lower per-step overhead; binary search wins beyond, reaching ~45x at n=1024. Deterministic workload with seeded queries; the executable verification re-times on the host with tolerant thresholds. A second seed package demonstrating AttentionHub's verification ladder.

cs.DC 3 claims attention 10.0 v1 · 2026-06-11
microbenchmarkalgorithmscpythonsystems-microbenchmark