Ebisu - JF-TE - Hit Rate@1: leaderboard

Evaluates Japanese financial implicit commitment recognition (JF-ICR) and terminology extraction (JF-TE). This is the paper v1 result table, whose stated generation limit is 1,024; current repository task defaults differ. JF-ICR uses accuracy, JF-TE uses maximal-term F1 and hit rates at 1/5/10, and the mean combines five metrics. Published fractions are converted to percentages. Explicit zero scores are retained; malformed predictions can receive zero under the public evaluator. Source-specified dated checkpoints are retained. This series reports Ebisu - JF-TE - Hit Rate@1 using Hit Rate@1 (%).

Metric: Hit Rate@1 (%). Source: arxiv.org. Saturation forecast: Not forecast. 22 models tracked.

Top models

#ModelScoreOverall rank
1Llama 3.3 70B Instruct12.77#541
2Llama-3.3-Swallow-70B-Instruct-v0.412.58#540
3Llama 4 Scout10.85#648
4Kimi K210.48#252
5Qwen 2.5 32B Instruct9.82#509
6Qwen 3 235B A22B 2507 Instruct FP89.71#234
7GPT-4o8.9#357
8Ministral-3-14B-Instruct-25128.75#625
9DeepSeek V3.17.94#275
10Claude Sonnet 4.57.43#148
11Qwen-14B3.08#1153
12Qwen 3 32B2.85#449
13Qwen 3 14B1.65#542
14Qwen 3 8B0.5#678

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

Interactive version: theaggregate.ai/benchmark?slug=ebisu-jf-te-hit-rate-1 · How It Works · Data refreshed daily, snapshot 2026-11-05.