logbook.json

{
  "schema_version": 1,
  "title": "Repro - POET-X: Memory-efficient LLM Training by Scaling Orthogonal Transformation",
  "emoji": "\ud83d\udd2c",
  "space_id": "bertfil/et8jpWLUuD",
  "paper": {
    "arxiv_id": "2603.05500",
    "openreview_id": "et8jpWLUuD",
    "title": "POET-X: Memory-efficient LLM Training by Scaling Orthogonal Transformation",
    "url": "https://arxiv.org/abs/2603.05500"
  },
  "tags": [
    "icml2026-repro",
    "paper-et8jpWLUuD"
  ],
  "updated_at": "2026-07-20T03:52:37+00:00",
  "root": {
    "slug": "index",
    "title": "Repro - POET-X: Memory-efficient LLM Training by Scaling Orthogonal Transformation",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "00-scored-evidence-summary",
        "title": "00 - Scored evidence summary",
        "file": "pages/00-scored-evidence-summary/page.md",
        "children": []
      },
      {
        "slug": "claim-1-poet-x-achieves-a-3x-gpu-memory-reduction-and-8x-r",
        "title": "Claim 1 - POET-X achieves a 3x GPU memory reduction and 8x runtime spe\u2026",
        "file": "pages/claim-1-poet-x-achieves-a-3x-gpu-memory-reduction-and-8x-r/page.md",
        "children": []
      },
      {
        "slug": "claim-2-poet-x-enables-pretraining-of-an-llm-with-up-to-13",
        "title": "Claim 2 - POET-X enables pretraining of an LLM with up to 13B paramete\u2026",
        "file": "pages/claim-2-poet-x-enables-pretraining-of-an-llm-with-up-to-13/page.md",
        "children": []
      },
      {
        "slug": "claim-3-on-llama-3b-pretraining-on-c4-with-l-max-256-poet",
        "title": "Claim 3 - On Llama-3B pretraining on C4 with L_max=256, POET-X with bl\u2026",
        "file": "pages/claim-3-on-llama-3b-pretraining-on-c4-with-l-max-256-poet/page.md",
        "children": []
      },
      {
        "slug": "claim-4-for-a-llama-13b-model-at-sequence-length-2048-poet",
        "title": "Claim 4 - For a Llama-13B model at sequence length 2048, POET-X_mem wi\u2026",
        "file": "pages/claim-4-for-a-llama-13b-model-at-sequence-length-2048-poet/page.md",
        "children": []
      },
      {
        "slug": "claim-5-a-customized-cuda-kernel-for-poet-x-s-permutation",
        "title": "Claim 5 - A customized CUDA kernel for POET-X's permutation operations\u2026",
        "file": "pages/claim-5-a-customized-cuda-kernel-for-poet-x-s-permutation/page.md",
        "children": []
      },
      {
        "slug": "claim-6-quantized-poet-xq-with-block-size-512-achieves-the",
        "title": "Claim 6 - Quantized POET-XQ with block size 512 achieves the best vali\u2026",
        "file": "pages/claim-6-quantized-poet-xq-with-block-size-512-achieves-the/page.md",
        "children": []
      },
      {
        "slug": "reproduction-protocol-and-provenance",
        "title": "Reproduction protocol and provenance",
        "file": "pages/reproduction-protocol-and-provenance/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
  "agent_view_tokens": 8121,
  "revision": "1784519557844500700"
}