Datasets:

ericrcwu
/

LUT_SLM_interpreter_cache

pretty_name: LUT-SLM — Interpreter Corpus & Teacher Caches
license: other
language:
  - en
task_categories:
  - text-generation
  - text-classification
size_categories:
  - 10K<n<100K
tags:
  - color-grading
  - lut
  - instruction-following
  - routing
  - refusal
  - captioning
  - synthetic

LUT-SLM — Interpreter Corpus & Teacher Caches

Training data and teacher-LLM caches for the Stage-1 interpreter/router of the LUT-SLM project (the model itself: ericrcwu/LUT_SLM_interpreter). It supplies the (free-text request → route + attribute spec) supervision that teaches the router to choose grade / clarify / refuse for a photo-editing instruction.

This is a companion to the source corpus ericrcwu/LUT_SLM: the grade rows here are teacher captions of that corpus's real, measured LUTs, and every row is stamped with its source LUT's leakage-safe split_unit_id so no near-duplicate straddles the train/eval boundary.

Files

data/
├── interpreter/
│   ├── interpreter_rows.jsonl           # UNIFIED interpreter corpus (the training target)
│   └── interpreter_corpus_manifest.json # counts + provenance for the unified corpus
└── active_sft/
    ├── caption_rows.jsonl               # teacher captions of real LUTs -> grade rows
    ├── caption_cache.jsonl              # raw teacher caption generations (resume cache)
    ├── caption_gen_manifest.json        # caption run manifest
    ├── route_supplement_rows.jsonl      # clarify + out_of_gamut supplement rows
    ├── route_supplement_cache.jsonl     # raw teacher generations for the supplement
    └── route_supplement_manifest.json   # supplement run manifest

The unified corpus (`interpreter_rows.jsonl`)

interpreter_corpus_version: interpreter_v1 — built by build_interpreter_corpus.py, which joins the grade captions, the refuse corpus, and the clarify supplement, stamping each with the source LUT's split_unit_id.


Total rows	15,077
By route	grade 13,805 · refuse 772 · clarify 500
Refuse kinds	out_of_scope 272 · out_of_gamut 500
Source families	caption 13,805 · unsupported_teacher 1,272
Distinct split units	2,869
Caption styles (×2,761 each)	`concept`, `literal`, `metaphor`, `mood`, `slang`

The 13,805 grade rows are 2,761 real LUTs each captioned in 5 stylistic registers (concept / literal / metaphor / mood / slang), so the router sees the same underlying edit phrased many ways. The refuse rows reuse the unsupported teacher corpus (edits a global LUT cannot express); the clarify / out_of_gamut rows are an additive supplement validated by absence-of-direction cues.

How captions are made

Grade captions are synthetic and behavior-grounded: a teacher LLM (Claude) is shown a real LUT's measured behavior (the CIEDE2000/Lab delta vector from the source corpus) and writes a natural request that describes it, cross-checked so the phrasing matches the measured direction. See the LUT_SLM card for the full measurement + teacher/judge methodology. The *_cache.jsonl files are the raw resume-safe generation logs behind the curated *_rows.jsonl.

Intended use

Train / evaluate the Stage-1 interpreter as a router (grade / clarify / refuse) over free-text color-editing requests.
Study instruction phrasing vs. routing robustness across the 5 caption styles.

Licensing & provenance

license: other. These rows are teacher-LLM text derived from the mixed-provenance LUT_SLM corpus, some of whose sources are personal-use / non-redistribution (see that dataset's licensing section). This repository makes no license claim over the underlying content. Research use; verify source terms before any redistribution or commercial use.