BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Paper • 2104.08663 • Published • 3
Datasets:
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A hybrid of genetic algorithm and particle swarm optimization for recurrent network design | An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), and is thus called HGAPSO.... | 632589828c8b9fca2c3a59e97451fde8fa7d188d | {
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A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function | Dynamic economic dispatch (DED) is one of the main functions of power generation operation and control. It determines the optimal settings of generator units with predicted load demand over a certain period of time. The objective is to operate an electric power system most economically while the system is operating wit... | 86e87db2dab958f1bd5877dc7d5b8105d6e31e46 | {
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Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases | It's not surprisingly when entering this site to get the book. One of the popular books now is the genetic fuzzy systems evolutionary tuning and learning of fuzzy knowledge bases. You may be confused because you can't find the book in the book store around your city. Commonly, the popular book will be sold quickly. And... | 2a047d8c4c2a4825e0f0305294e7da14f8de6fd3 | {
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Separate face and body selectivity on the fusiform gyrus. | "Recent reports of a high response to bodies in the fusiform face area (FFA) challenge the idea that(...TRUNCATED) | 857a8c6c46b0a85ed6019f5830294872f2f1dcf5 | {"authors":["2981413","2074160","1931482"],"cited_by":["34bf37eb7a34ac4efc57254303f65429a3ccdd85","f(...TRUNCATED) |
Scheduling for Reduced CPU Energy | "The energy usage of computer systems is becoming more important, especially for battery operated sy(...TRUNCATED) | 12f107016fd3d062dff88a00d6b0f5f81f00522d | {"authors":["1800362","9036495","1686255","1753148"],"cited_by":["c3ce0da75953dd041152c1757d18647fe0(...TRUNCATED) |
A data mining approach for location prediction in mobile environments | "Mobility prediction is one of the most essential issues that need to be explored for mobility manag(...TRUNCATED) | 1ae0ac5e13134df7a0d670fc08c2b404f1e3803c | {"authors":["2108906","22789555","1801322","1796253"],"cited_by":["f1f25228e0285e615b84a150dec227978(...TRUNCATED) |
$\mathsf {pSCAN}$ : Fast and Exact Structural Graph Clustering | "We study the problem of structural graph clustering, a fundamental problem in managing and analyzin(...TRUNCATED) | 7d3c9c4064b588d5d8c7c0cb398118aac239c71b | {"authors":["38736958","35660624","36838704","19262604","47569211"],"cited_by":[],"references":["dd3(...TRUNCATED) |
Synthesis, properties, and applications of iron nanoparticles. | "Iron, the most ubiquitous of the transition metals and the fourth most plentiful element in the Ear(...TRUNCATED) | 305c45fb798afdad9e6d34505b4195fa37c2ee4f | {"authors":["5701357"],"cited_by":["82b17ab50e8d80c81f28c22e43631fa7ec6cbef2","649ad261855d2854f2509(...TRUNCATED) |
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YAML Metadata Warning:The task_categories "information-retrieval" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
BEIR SCIDOCS Dataset (Migrated)
This is a migrated version of BeIR/scidocs that is compatible with datasets library 4.0.0+.
Dataset Description
This dataset contains the scidocs dataset from the BEIR benchmark, converted from the old script-based format to Parquet format.
Dataset Structure
Queries
Split 'queries': 1,000 examples
- Features: ['_id', 'text', 'metadata']
Total examples: 1,000
Corpus
Split 'corpus': 25,657 examples
- Features: ['_id', 'title', 'text', 'metadata']
Total examples: 25,657
Usage
from datasets import load_dataset
# Load queries (split: queries)
queries = load_dataset("Hyukkyu/beir-scidocs", "queries", split="queries")
# Load corpus (split: corpus)
corpus = load_dataset("Hyukkyu/beir-scidocs", "corpus", split="corpus")
Available Splits
Queries
queries: 1,000 examples
Corpus
corpus: 25,657 examples
Original Dataset
This dataset is migrated from: BeIR/scidocs
Citation
If you use this dataset, please cite the original BEIR paper:
@article{thakur2021beir,
title={BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
author={Thakur, Nandan and Reimers, Nils and Ruckle, Andreas and Srivastava, Abhishek and Gurevych, Iryna},
journal={arXiv preprint arXiv:2104.08663},
year={2021}
}
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