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Release v2.0.0

Summary

Version 2 is a research update to the accompanying manuscript, strengthening its scholarly positioning and statistical grounding. The empirical findings, methodology, and conclusions from v1 are unchanged; this release adds the context and rigor a peer-review process would expect around them.

Highlights

  • Added a comprehensive Related Work section, positioning SmartEvict against classical cache eviction (LRU-K, 2Q, ARC, LIRS, GDSF), learned cache eviction (Cold-RL, Learning Relaxed Belady), semantic response caches (GPTCache), and KV-cache eviction in LLM serving (StreamingLLM, H2O, Scissorhands, vLLM, SGLang).
  • Expanded the Discussion with a dedicated caveat on embedding-model choice, surfacing a limitation that previously lived only in Threats to Validity.
  • Added a compact feature/architecture ablation table (Table 4) directly in the manuscript, alongside the existing full ablation write-up in results/ABLATIONS.md.
  • Added a statistical significance check (paired t-test) supporting the "statistically tied" reading of the WildChat-1M three-way comparison.
  • Substantially expanded the bibliography to properly cite every system and prior work discussed in Related Work.
  • Minor wording refinements for precision (e.g., the abstract's characterization of the reuse-density relationship now explicitly notes it is drawn from three real-world traces).

Notes

  • No changes to the simulator, policies, training pipeline, or reported experimental results — this release is limited to the manuscript's framing, citations, and statistical support.

Release v1.0.0

Summary

SmartEvict v1.0.0 introduces the first published release of the repository alongside a GitHub release. This release highlights the project's empirical comparison between learned and heuristic eviction policies for semantic LLM caches.

Highlights

  • Learned vs heuristic comparison: benchmarked learned eviction against LRU, FIFO, and cost-aware heuristics.
  • Benchmark suite: reproducible experiments for synthetic and real workloads, including LMSYS-Chat-1M, WildChat-1M, and Bitext.
  • Reproducibility: reproduce.sh regenerates every benchmark table and figure from the repository.
  • Accompanying paper: a full manuscript with results, methods, and discussion.

Notes

  • This release marks the repository's first stable public snapshot as v1.0.0.
  • DOI, arXiv, and GitHub Actions badges will be added once the respective artifacts exist.