AbstentionBench - underspecified intent - SituatedQA/Geo - Precision: leaderboard
AbstentionBench evaluates whether a model appropriately declines unanswerable or underspecified questions. This slice reports underspecified intent - SituatedQA/Geo - Precision as Abstention Precision (%); 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 Precision (%). Source: github.com. Saturation forecast: Estimated already saturated. 20 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | DeepSeek R1 Distill Llama 70B | 86.21 | #614 |
| 2 | GPT-4o | 69.92 | #357 |
| 3 | Llama 3.3 70B Instruct | 69.03 | #541 |
| 4 | Llama 3.1 70B | 59.57 | #588 |
| 5 | O1 | 59.04 | #190 |
| 6 | Llama 3.1 8B Instruct | 58.67 | #1017 |
| 7 | Mistral 7B Instruct (v0.3) | 58.52 | #1255 |
| 8 | Llama 3.1 8B | 55.79 | #1130 |
| 9 | Llama 3.1 70B Instruct | 55.74 | #567 |
| 10 | Llama-3.1-Tulu-3-8B | 52.94 | #848 |
| 11 | Gemini 1.5 Pro | 50.35 | #454 |
| 12 | Llama-3.1-Tulu-3-70B-DPO | 50.22 | #732 |
| 13 | Llama-3.1-Tulu-3-70B | 49.78 | #499 |
| 14 | Llama 3.1 405B Instruct | 49.68 | #470 |
| 15 | Llama-3.1-Tulu-3-8B-DPO | 49.04 | #992 |
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-intent-situatedqa-geo-precision · How It Works · Data refreshed daily, snapshot 2026-11-05.