Cite arxiv.org/abs/2607.23806 to link dataset to the paper

README.md

@@ -1,60 +1,67 @@
----
-license: cc-by-4.0
-pretty_name: Galahad — SHA-256 Proof (measured benchmark results)
-tags:
-  - benchmark
-  - kv-cache
-  - llm-inference
-  - reproducibility
-configs:
-  - config_name: default
-    data_files: index.jsonl
----
-
-# Galahad — SHA-256 Proof
-
-Timestamped, independently verifiable **measured** benchmark results behind the Galahad paper.
-
-📄 **Paper:** https://huggingface.co/papers/2607.23806
-🧪 **Live testbench (Space):** https://huggingface.co/spaces/Corbenic/galahad-bench
-💾 **Proof mirror (GitHub):** https://github.com/corbenicai/galahad-bench/tree/main/proof
-
-## What this is
-
-This dataset is the **integrity proof** for the paper's claims: the raw measured outputs (pure numbers —
-token counts, latency in ms, VRAM in MB, accuracy, pass/fail) plus a full SHA-256 manifest. It contains
-**no source code, no engine internals, and no solver contents** — only measurements.
-
-- **`results/`** — the raw measured benchmark JSON files.
-- **`index.jsonl`** — one row per result file (filename, its SHA-256, key numeric measurements) so the
-  dataset viewer renders a quick overview.
-- **`results.sha256`** — the hashes in `sha256sum -c` format.
-- **`SHA256_PROOF.txt`** — the full manifest: verifiable hashes **plus sealed commitments** to files kept
-  private (source, verified-solver memory, internal notes, engine binaries). A sealed hash proves a file
-  existed and was fixed on the stated date **without revealing its contents**.
-
-## Verify it yourself
-
-```bash
-git clone https://huggingface.co/datasets/Corbenic/galahad-bench-proof
-cd galahad-bench-proof
-sha256sum -c results.sha256          # expect: every line "OK"
-```
-
-## Highlights (measured, single GPU)
-
-- **Movable window** — `results/window6m.json`: a **6,000,000-token** context on one GPU at **flat VRAM**
-  (base ≈ peak MB), correct retrieval at every depth, passing negative control.
-- **Head-to-head** — `results/bench_vllm.json`, `results/bench_sglang.json`: same GPU / model class; vLLM
-  hard-stops at ~30k tokens, SGLang truncates past ~32k, Galahad runs to millions.
-- **Verified reuse** — `results/reuse_*.json`, `results/frommem_*.json`: 0-decode-token reuse across four
-  model families; `frommem_EMPTY.json` is the negative control (empty memory solves nothing).
-
-## Scope & honesty
-
-These are **measurements**, not the method. The engine, the verified-solver memory, and the internal
-method notes are intentionally **not** published — their SHA-256 commitments are in `SHA256_PROOF.txt` so
-the record is complete and tamper-evident. No trade-secret content is exposed by a hash.
-
-`load_dataset("Corbenic/galahad-bench-proof")` loads the `index.jsonl` overview; the full result files live
-under `results/`.
+---
+license: cc-by-4.0
+pretty_name: Galahad — SHA-256 Proof (measured benchmark results)
+tags:
+  - benchmark
+  - kv-cache
+  - llm-inference
+  - reproducibility
+configs:
+  - config_name: default
+    data_files: index.jsonl
+---
+
+# Galahad — SHA-256 Proof
+
+Timestamped, independently verifiable **measured** benchmark results behind the Galahad paper.
+
+📄 **Paper:** https://huggingface.co/papers/2607.23806
+📚 **arXiv:** https://arxiv.org/abs/2607.23806
+🧪 **Live testbench (Space):** https://huggingface.co/spaces/Corbenic/galahad-bench
+💾 **Proof mirror (GitHub):** https://github.com/corbenicai/galahad-bench/tree/main/proof
+
+## What this is
+
+This dataset is the **integrity proof** for the paper's claims: the raw measured outputs (pure numbers —
+token counts, latency in ms, VRAM in MB, accuracy, pass/fail) plus a full SHA-256 manifest. It contains
+**no source code, no engine internals, and no solver contents** — only measurements.
+
+- **`results/`** — the raw measured benchmark JSON files.
+- **`index.jsonl`** — one row per result file (filename, its SHA-256, key numeric measurements) so the
+  dataset viewer renders a quick overview.
+- **`results.sha256`** — the hashes in `sha256sum -c` format.
+- **`SHA256_PROOF.txt`** — the full manifest: verifiable hashes **plus sealed commitments** to files kept
+  private (source, verified-solver memory, internal notes, engine binaries). A sealed hash proves a file
+  existed and was fixed on the stated date **without revealing its contents**.
+
+## Verify it yourself
+
+```bash
+git clone https://huggingface.co/datasets/Corbenic/galahad-bench-proof
+cd galahad-bench-proof
+sha256sum -c results.sha256          # expect: every line "OK"
+```
+
+## Highlights (measured, single GPU)
+
+- **Movable window** — `results/window6m.json`: a **6,000,000-token** context on one GPU at **flat VRAM**
+  (base ≈ peak MB), correct retrieval at every depth, passing negative control.
+- **Head-to-head** — `results/bench_vllm.json`, `results/bench_sglang.json`: same GPU / model class; vLLM
+  hard-stops at ~30k tokens, SGLang truncates past ~32k, Galahad runs to millions.
+- **Verified reuse** — `results/reuse_*.json`, `results/frommem_*.json`: 0-decode-token reuse across four
+  model families; `frommem_EMPTY.json` is the negative control (empty memory solves nothing).
+
+## Scope & honesty
+
+These are **measurements**, not the method. The engine, the verified-solver memory, and the internal
+method notes are intentionally **not** published — their SHA-256 commitments are in `SHA256_PROOF.txt` so
+the record is complete and tamper-evident. No trade-secret content is exposed by a hash.
+
+`load_dataset("Corbenic/galahad-bench-proof")` loads the `index.jsonl` overview; the full result files live
+under `results/`.
+
+## Cite
+
+```
+arxiv.org/abs/2607.23806
+```