RPCBench - Error Group - Underspecified Premise - Evidence Distortion: leaderboard
RPCBench tests proactive premise critique in recommendation requests. This series measures evidence distortion on the Underspecified Premise subset (1,300 questions), using the same eleven-model, three-judge experiment as the headline paper. Published F1R fractions from the authors' per-model CSV are scaled once to Evidence Distortion Rate (%). Lower is better; domains and nested premise-error groups are related slices of the same experiment.
Metric: Evidence Distortion Rate (%). Source: github.com. 11 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Llama 3.1 8B Instruct | 27.77 | #4318 |
| 2 | Llama 3.1 70B Instruct | 29.23 | #1629 |
| 3 | Gemini 3.1 Pro (Preview) | 33.46 | #93 |
| 4 | GPT-5.5 | 40.38 | #48 |
| 5 | Claude Sonnet 4.6 | 43.08 | #159 |
| 6 | Qwen 3.5 35B A3B | 47.15 | #492 |
| 7 | Qwen 3.5 122B A10B | 48.31 | #335 |
| 8 | DeepSeek V4 Flash | 48.69 | #259 |
| 9 | DeepSeek V4 Pro | 48.92 | #188 |
| 10 | Qwen 3.5 397B A17B | 49.38 | #245 |
| 11 | Qwen 3.5 Plus | 51.08 | #232 |
Interactive version: theaggregate.ai/benchmark?slug=rpcbench-error-group-underspecified-premise-evidence-distortion · How It Works · Data refreshed daily, snapshot 2026-11-08.