AbstentionBench - false premise - CoCoNot/False presumptions - F1: leaderboard

AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports false premise - CoCoNot/False presumptions - F1 as Abstention F1 (%); 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 F1 (%). Source: github.com. Saturation forecast: Estimated already saturated. 20 models tracked.

Top models

#ModelScoreOverall rank
1O189.57#190
2Llama-3.1-Tulu-3-70B88.16#499
3Llama-3.1-Tulu-3-70B-DPO86.84#732
4GPT-4o84.35#357
5Llama 3.1 405B Instruct83.54#470
6Qwen 2.5 32B Instruct83.22#509
7Llama 3.3 70B Instruct82.99#541
8Llama-3.1-Tulu-3-8B-DPO82.89#992
9Llama-3.1-Tulu-3-8B81.63#848
10Mistral 7B Instruct (v0.3)80.82#1255
11Llama 3.1 70B Instruct80#567
12DeepSeek R1 Distill Llama 70B79.14#614
13Gemini 1.5 Pro78.91#454
14OLMo-7B-0724-Instruct-hf77.46#1441
15Llama-3.1-Tulu-3-8B-SFT77.37#977

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

Interactive version: theaggregate.ai/benchmark?slug=abstentionbench-false-premise-coconot-false-presumptions-f1 · How It Works · Data refreshed daily, snapshot 2026-11-05.