image imagewidth (px) 900 1k | caption stringclasses 2
values | name stringclasses 2
values |
|---|---|---|
LLM Coding Performance vs Language Popularity — Extra Hard Tier, zero-shot GPT-5.2 | gradient_chart | |
Problem x Language Pass Rates (zero-shot) — Extra Hard tier | heatmap |
sdc-gradient-chart-xhard-v1
Gradient chart and heatmap — Extra Hard tier
Dataset Info
- Rows: 2
- Columns: 3
Columns
| Column | Type | Description |
|---|---|---|
| image | Image(mode=None, decode=True) | Chart PNG |
| caption | Value('string') | Description |
| name | Value('string') | Chart ID |
Generation Parameters
{
"script_name": "run_extra_hard_zero_shot.py",
"model": "gpt-5-2",
"description": "Gradient chart and heatmap \u2014 Extra Hard tier",
"experiment_id": "semantic-distance-coding",
"artifact_type": "processed_data",
"visualizer_type": "image",
"hyperparameters": {},
"input_datasets": []
}
Experiment Documentation
For complete experiment details, see https://github.com/Zayne-sprague/SC-Research-Notes/tree/main/experiments/semantic-distance-coding
Usage
from datasets import load_dataset
dataset = load_dataset("reasoning-degeneration-dev/sdc-gradient-chart-xhard-v1", split="train")
print(f"Loaded {len(dataset)} rows")
This dataset is tracked in reasoning-degeneration-dev/PROJECT-MANIFEST
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