{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreigqknvdbovtlqvnpkdvhgoi3y34iakulepd23dgroelu5opuzplsy",
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  "path": "/t/seeking-arxiv-endorsement-for-cs-lg-qeac-paper-on-kv-cache-co-optimization/175962#post_1",
  "publishedAt": "2026-05-13T02:37:57.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "Hi, I’m an independent ML researcher seeking an arXiv endorsement for cs.LG. My paper introduces QEAC, a closed-loop co-optimization framework for sparse attention and KV cache quantization. Tested on Mistral-7B and TinyLlama-1.1B with strong results (2% perplexity degradation at 4x compression vs 20% for uniform 4-bit).\n\nMy endorsement code is: Q9NXPT\nHappy to share the PDF. Thank you!",
  "title": "Seeking arXiv endorsement for cs.LG — QEAC paper on KV cache co-optimization"
}