AbstentionBench - underspecified context - BBQ - Recall: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports underspecified context - BBQ - Recall as Abstention Recall (%); values converted from 0-1 to percent. Precision and recall must be read together: always abstaining is not necessarily useful. Scenario/dataset pairs and SFT/DPO/RL checkpoints remain separate; no synthetic overall average. Source: facebookresearch/AbstentionBench analysis/abstention_performance.csv.

Metric: Abstention Recall (%). Source: github.com. Saturation forecast: Estimated already saturated. 20 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 2.5 32B Instruct95.05#509
2Gemini 1.5 Pro92.41#454
3Mistral 7B Instruct (v0.3)90.78#1255
4GPT-4o90.04#357
5Llama 3.1 8B Instruct89.93#1017
6Llama 3.1 405B Instruct89.82#470
7Llama-3.1-Tulu-3-70B88.08#499
8Llama-3.1-Tulu-3-70B-DPO87.85#732
9Llama 3.1 70B Instruct84.2#567
10Llama 3.3 70B Instruct79.75#541
11OLMo-7B-0724-Instruct-hf76.72#1441
12Llama-3.1-Tulu-3-8B-DPO65.86#992
13DeepSeek R1 Distill Llama 70B63.05#614
14Llama-3.1-Tulu-3-8B62.09#848
15O154.78#190

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=abstentionbench-underspecified-context-bbq-recall · How It Works · Data refreshed daily, snapshot 2026-11-05.