DecodeShare

Large artifacts for DecodeShare: Tracing the Shared Pathways of LLM Decode-Time Decisions.

The corresponding GitHub release branch is:

https://github.com/Zishan-Shao/decodeshare/tree/Halo

This Hugging Face repository is intended for files that should not live in Git history:

• decode-time activation caches
• shared-subspace bases
• patchback result archives
• downstream compression outputs, with oversized profiling caches stored as .pt.part-* chunks
• selected steering vectors and cached candidate pools
• rebuttal mechanism and scaling artifacts that are too bulky for the main GitHub branch

The GitHub branch tracks compact code, scripts, summaries, and the full artifact manifest at:

docs/artifact_manifest.tsv

Suggested layout:

artifacts/
  Hype1/results/acts/
  patch_back/results/
  downstream/outputs/
  rebuttal/
  results/rebuttal_mechanism/
  results/rebuttal_scaling/

The 2026-05-10 rebuttal upload is summarized in:

docs/REBUTTAL_UPLOAD_2026-05-10.md

Install the Hugging Face CLI and upload from the original workspace:

pip install -U huggingface_hub[hf_transfer]
hf auth login
cd /path/to/decodeshare
hf upload Zishan-Shao/decodeshare Hype1/results/acts artifacts/Hype1/results/acts
hf upload Zishan-Shao/decodeshare patch_back/results artifacts/patch_back/results

For downstream profiling caches, use the split-file workflow in docs/HUGGINGFACE_UPLOAD.md. Reassembly notes are included under artifacts/downstream/outputs/SPLIT_FILES.md after upload.

Model and dataset licenses remain governed by their upstream providers.