v1.1/README.md

SurveyReview

A Reviewer-Aligned Benchmark for Survey Evaluators

SurveyReview is a reviewer-aligned benchmark for evaluating survey papers. It converts real peer-review reports into multidimensional evaluation labels and rationales, allowing models to be tested against how human reviewers judge survey quality.

This directory is the v1.1 release. It keeps the original SurveyReview evaluation metrics while using cleaned article texts and XML-like rationale prompts.

The benchmark focuses on four survey-review dimensions: Readability, Criticalness, Comprehensiveness, and Structure. It provides standardized train/test splits, article metadata, prompt files, and an API-based evaluation pipeline.

Quick Start

Create an environment and install dependencies:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Configure the API client:

cp .env.example .env

Then edit .env:

API_KEY=your-api-key-here
BASE_URL=https://api.openai.com/v1
MODEL_NAME=gpt-5.2
JUDGE_MODEL=gpt-5.2
EVALUATE_REASONS=True

Run the default test-set evaluation:

python src/api_base_evaluate.py

The v1.1 evaluator defaults to:

data/v1.1-paper

Run on the train split:

EVAL_SPLIT=train python src/api_base_evaluate.py

Outputs are written to result/<timestamp>/:

File	Description
results.csv	MSE, MAE, accuracy, and sample counts for each dimension.
predictions_<dimension>.jsonl	Per-sample prediction records.
run_config.json	Runtime configuration and split statistics.
rqs_<dimension>.json	Rationale quality results when EVALUATE_REASONS=True.

Leaderboard

Lower MSE/MAE is better. Higher HAS/RQS is better.

Rank	Model	HAS	Read.		Crit.		Comp.		Stru.		Average		RQS
			MSE	MAE	MSE	MAE	MSE	MAE	MSE	MAE	MSE	MAE
1	SurveyReviewer	0.74	1.43	0.72	1.52	0.82	1.26	0.56	1.29	0.65	1.38	0.69	0.36
2	GPT-5.2	0.68	2.13	1.07	1.97	0.97	2.04	1.08	2.98	1.47	2.28	1.15	0.42
3	Claude-Opus-4.5	0.68	2.91	1.29	1.88	0.88	2.66	1.23	3.65	1.58	2.77	1.25	0.48
4	Qwen3-32B	0.61	3.05	1.45	3.24	1.51	3.22	1.54	3.35	1.53	3.21	1.51	0.36
5	GLM-4.7	0.60	3.43	1.50	2.58	1.21	3.66	1.57	4.83	1.95	3.62	1.56	0.37
6	gemini-3-pro	0.58	3.84	1.52	2.25	1.00	3.91	1.49	5.76	2.11	3.94	1.53	0.29
7	DeepSeek-v3.2	0.58	4.78	1.88	2.49	1.15	4.59	1.82	4.02	1.76	3.97	1.65	0.37

Notes

• articles/ is split into multiple JSON shards to stay within GitHub file-size limits.
• v1.1-paper uses cleaned article texts and prompts that output <reason>...</reason> <score>X</score>.
• If you only want to verify the pipeline, set EVALUATE_REASONS=False to skip the judge-model stage.