Would an EvalPort-format export of MT-Bench be welcome?
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Description
Hi FastChat team — I maintain [EvalPort](https://github.com/adhabnr-ux/evalport), an open, framework-agnostic JSON spec for portable LLM eval datasets (Apache 2.0, `TestCase`/`Suite` schema with a real JSON Schema validator). It has a `benchmarks/` directory converting well-known public benchmarks into validated EvalPort suites, each with attribution and license preserved, so someone using a different harness can still run the same questions without a bespoke converter.
I read the actual data files rather than guessing at fields. `fastchat/llm_judge/data/mt_bench/question.jsonl`:
```json
{"question_id": 81, "category": "writing", "turns": ["Compose an engaging travel blog post about a recent trip to Hawaii...", "Rewrite your previous response. Start every sentence with the letter A."]}
```
plus `fastchat/llm_judge/data/mt_bench/reference_answer/gpt-4.jsonl` (reference answers keyed by `question_id`), and `fastchat/llm_judge/data/judge_prompts.jsonl` for the LLM-judge rubric.
This maps onto EvalPort cleanly: `turns` → a multi-turn `TestCase.input` list, `question_id`/`category` → `metadata`, the matching `reference_answer` entry → `expected_output` where present, and the judge prompt → an EvalPort `llm_judge` grader definition (MT-Bench's pairwise/single-answer grading is exactly the kind of grader EvalPort's spec has a slot for).
Would your maintainers be open to an EvalPort-format export of MT-Bench (and/or Vicuna-Bench, same structure) living in EvalPort's `benchmarks/` directory, with attribution to this repo/paper and the Apache-2.0 license preserved? I'd do the conversion work and validate it against EvalPort's real schema — filing this as a heads-up issue first rather than sending a PR out of nowhere. Also happy to link back to FastChat from EvalPort's benchmark listing either way. Let me know if this is of interest, or not a priority right now — no worries either way.
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing fastchat/llm_judge/data/mt_bench/question.jsonl, the matching reference_answer/gpt-4.jsonl file, and judge_prompts.jsonl, then compare their contents with EvalPort's TestCase, Suite, and llm_judge schema. Done would require maintainer agreement on the proposed external export and a validated EvalPort benchmark with attribution and license information preserved.
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Assessment
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100