artefactory/abstention-reranking-benchmark
收藏Hugging Face2024-10-02 更新2026-05-10 收录
下载链接:
https://hf-mirror.com/datasets/artefactory/abstention-reranking-benchmark
下载链接
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资源简介:
---
dataset_info:
features:
- name: model_name
dtype: string
- name: dataset_path
dtype: string
- name: num_docs_pr
dtype: int64
- name: random_seed
dtype: int64
- name: queries
sequence: string
- name: positives
sequence:
sequence: string
- name: negatives
sequence:
sequence: string
- name: scores
sequence:
sequence: float64
- name: targets
sequence:
sequence: float64
splits:
- name: test
num_bytes: 2218701030
num_examples: 132
download_size: 1121022682
dataset_size: 2218701030
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism
## Dataset
This dataset provides the evaluation benchmark used in the paper "Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism", accepted at TMLR (September 2024).
## Paper
For more details on this work, you can read the full paper [here](https://arxiv.org/pdf/2402.12997).
**Citation:**
```
@article{gisserot2024towards,
title={Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism},
author={Gisserot-Boukhlef, Hippolyte and Faysse, Manuel and Malherbe, Emmanuel and Hudelot, C{\'e}line and Colombo, Pierre},
journal={arXiv preprint arXiv:2402.12997},
year={2024}
}
```
dataset_info:
数据集元信息:
特征:
- 名称:model_name
数据类型:字符串(string)
- 名称:dataset_path
数据类型:字符串(string)
- 名称:num_docs_pr
数据类型:64位整数(int64)
- 名称:random_seed
数据类型:64位整数(int64)
- 名称:queries
数据类型:字符串序列(sequence)
- 名称:positives
数据类型:字符串序列的序列(sequence of sequence)
- 名称:negatives
数据类型:字符串序列的序列(sequence of sequence)
- 名称:scores
数据类型:64位浮点数序列的序列(sequence of sequence of float64)
- 名称:targets
数据类型:64位浮点数序列的序列(sequence of sequence of float64)
数据集划分:
- 名称:test
数据字节数:2218701030
样本数量:132
下载总大小:1121022682
数据集总大小:2218701030
配置:
- 配置名称:default
数据文件:
- 划分集:test
路径:data/test-*
---
# 迈向可信赖重排序:一种简洁高效的弃权机制
## 数据集
本数据集为收录于TMLR(2024年9月)的论文《迈向可信赖重排序:一种简洁高效的弃权机制》中所使用的评估基准。
## 论文
如需了解此项研究的更多细节,可点击[此处](https://arxiv.org/pdf/2402.12997)查阅完整论文。
**引用格式:**
@article{gisserot2024towards,
title={迈向可信赖重排序:一种简洁高效的弃权机制},
author={Gisserot-Boukhlef, Hippolyte and Faysse, Manuel and Malherbe, Emmanuel and Hudelot, Céline and Colombo, Pierre},
journal={arXiv preprint arXiv:2402.12997},
year={2024}
}
提供机构:
artefactory


