FiQA
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Financial Question Answering | FiQA | Accuracy82.7 | 85 | |
| Retrieval Attack Defense | FiQA | ASR0 | 64 | |
| Information Retrieval | FIQA | MRR54 | 22 | |
| Information Retrieval | FiQA benign retrieval | Success Rate (SR)79 | 16 | |
| Privacy-utility tradeoff | FIQA | Leakage8.48 | 16 | |
| Information Retrieval | FIQA BEIR (test) | nDCG@1048.1 | 15 | |
| Question Answering Retrieval | FiQA | nDCG@1038.6 | 9 | |
| Information Retrieval | FiQA 2018 (test) | NDCG@100.364 | 9 | |
| Financial Question Answering | FIQA Synthetic NIID 1.0 (test) | Win Rate82.1 | 6 | |
| Financial Question Answering | FIQA Synthetic IID 1.0 (test) | Win Rate72.1 | 6 | |
| Adversarial Attack | FiQA 2018 | Contriever86.54 | 6 | |
| Information Retrieval | FiQA 2018 | Accuracy42.05 | 6 | |
| Information Retrieval | FiQA Financial | MRR99 | 4 | |
| Dense Retrieval | FiQA | Relative Improvement14.6 | 4 | |
| Information Retrieval | FiQA 2018 | MRR@100.7205 | 4 | |
| Information Retrieval | FIQA | QPS507.03 | 4 | |
| Sentiment Analysis | FiQA SA | Score75.07 | 4 | |
| Sentiment Classification | FiQA (test) | Accuracy0.87 | 3 | |
| Sentiment Scoring | FiQA Sentiment Dataset 2018 (test) | MSE0.07 | 3 | |
| RAG (Retrieval-Augmented Generation) | FiQA 57K docs | Context Precision15.62 | 1 | |
| Financial Question Answering | fiqa v1 (test) | Accuracy- | 0 |
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