RPCBench - Domain - Yelp Local - Evidence Distortion: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures evidence distortion on the Yelp Local subset (1,310 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. Saturation forecast: Around February 2027. 11 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.510.23#34
2Gemini 3.1 Pro (Preview)12.21#66
3Qwen 3.5 122B A10B16.26#186
4Qwen 3.5 397B A17B17.25#155
5Qwen 3.5 Plus17.79#136
6Qwen 3.5 35B A3B17.86#270
7Llama 3.1 8B Instruct18.17#1021
8DeepSeek V4 Pro22.14#113
9Claude Sonnet 4.622.75#97
10Llama 3.1 70B Instruct22.82#570
11DeepSeek V4 Flash23.44#156

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #6 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=rpcbench-domain-yelp-local-evidence-distortion · How It Works · Data refreshed daily, snapshot 2026-11-07.