Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Sub-tasks:
multiple-choice-qa
Languages:
English
Size:
10K - 100K
ArXiv:
License:
metadata
annotations_creators:
- derived
language:
- eng
license: cc-by-nc-4.0
multilinguality: monolingual
source_datasets:
- KaLM-Embedding/LMEB
task_categories:
- text-retrieval
task_ids:
- multiple-choice-qa
dataset_info:
- config_name: adversarial-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 1382724
num_examples: 5882
download_size: 527934
dataset_size: 1382724
- config_name: adversarial-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 24884
num_examples: 460
download_size: 7311
dataset_size: 24884
- config_name: adversarial-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 35956
num_examples: 446
download_size: 20069
dataset_size: 35956
- config_name: adversarial-top_ranked
features:
- name: query-id
dtype: string
- name: corpus-ids
list: string
splits:
- name: test
num_bytes: 7850967
num_examples: 446
download_size: 7848727
dataset_size: 7850967
- config_name: multi_hop-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 1382724
num_examples: 5882
download_size: 527934
dataset_size: 1382724
- config_name: multi_hop-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 46223
num_examples: 875
download_size: 9258
dataset_size: 46223
- config_name: multi_hop-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 18905
num_examples: 280
download_size: 11066
dataset_size: 18905
- config_name: multi_hop-top_ranked
features:
- name: query-id
dtype: string
- name: corpus-ids
list: string
splits:
- name: test
num_bytes: 4880303
num_examples: 280
download_size: 4879876
dataset_size: 4880303
- config_name: open_domain-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 1382724
num_examples: 5882
download_size: 527934
dataset_size: 1382724
- config_name: open_domain-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 10417
num_examples: 197
download_size: 3856
dataset_size: 10417
- config_name: open_domain-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 7031
num_examples: 89
download_size: 5785
dataset_size: 7031
- config_name: open_domain-top_ranked
features:
- name: query-id
dtype: string
- name: corpus-ids
list: string
splits:
- name: test
num_bytes: 1604889
num_examples: 89
download_size: 1605918
dataset_size: 1604889
- config_name: single_hop-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 1382724
num_examples: 5882
download_size: 527934
dataset_size: 1382724
- config_name: single_hop-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 48075
num_examples: 893
download_size: 12100
dataset_size: 48075
- config_name: single_hop-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 67582
num_examples: 840
download_size: 33613
dataset_size: 67582
- config_name: single_hop-top_ranked
features:
- name: query-id
dtype: string
- name: corpus-ids
list: string
splits:
- name: test
num_bytes: 14956745
num_examples: 840
download_size: 14951483
dataset_size: 14956745
- config_name: temporal_reasoning-corpus
features:
- name: id
dtype: string
- name: text
dtype: string
- name: title
dtype: string
splits:
- name: test
num_bytes: 1382724
num_examples: 5882
download_size: 527934
dataset_size: 1382724
- config_name: temporal_reasoning-qrels
features:
- name: query-id
dtype: string
- name: corpus-id
dtype: string
- name: score
dtype: int64
splits:
- name: test
num_bytes: 19792
num_examples: 375
download_size: 6004
dataset_size: 19792
- config_name: temporal_reasoning-queries
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: test
num_bytes: 22134
num_examples: 321
download_size: 12436
dataset_size: 22134
- config_name: temporal_reasoning-top_ranked
features:
- name: query-id
dtype: string
- name: corpus-ids
list: string
splits:
- name: test
num_bytes: 5536253
num_examples: 321
download_size: 5535431
dataset_size: 5536253
configs:
- config_name: adversarial-corpus
data_files:
- split: test
path: adversarial-corpus/test-*
- config_name: adversarial-qrels
data_files:
- split: test
path: adversarial-qrels/test-*
- config_name: adversarial-queries
data_files:
- split: test
path: adversarial-queries/test-*
- config_name: adversarial-top_ranked
data_files:
- split: test
path: adversarial-top_ranked/test-*
- config_name: multi_hop-corpus
data_files:
- split: test
path: multi_hop-corpus/test-*
- config_name: multi_hop-qrels
data_files:
- split: test
path: multi_hop-qrels/test-*
- config_name: multi_hop-queries
data_files:
- split: test
path: multi_hop-queries/test-*
- config_name: multi_hop-top_ranked
data_files:
- split: test
path: multi_hop-top_ranked/test-*
- config_name: open_domain-corpus
data_files:
- split: test
path: open_domain-corpus/test-*
- config_name: open_domain-qrels
data_files:
- split: test
path: open_domain-qrels/test-*
- config_name: open_domain-queries
data_files:
- split: test
path: open_domain-queries/test-*
- config_name: open_domain-top_ranked
data_files:
- split: test
path: open_domain-top_ranked/test-*
- config_name: single_hop-corpus
data_files:
- split: test
path: single_hop-corpus/test-*
- config_name: single_hop-qrels
data_files:
- split: test
path: single_hop-qrels/test-*
- config_name: single_hop-queries
data_files:
- split: test
path: single_hop-queries/test-*
- config_name: single_hop-top_ranked
data_files:
- split: test
path: single_hop-top_ranked/test-*
- config_name: temporal_reasoning-corpus
data_files:
- split: test
path: temporal_reasoning-corpus/test-*
- config_name: temporal_reasoning-qrels
data_files:
- split: test
path: temporal_reasoning-qrels/test-*
- config_name: temporal_reasoning-queries
data_files:
- split: test
path: temporal_reasoning-queries/test-*
- config_name: temporal_reasoning-top_ranked
data_files:
- split: test
path: temporal_reasoning-top_ranked/test-*
tags:
- mteb
- text
LMEB dialogue-memory retrieval task based on LoCoMo, covering single-hop, multi-hop, temporal, open-domain, and adversarial long-conversation questions.
| Task category | Retrieval (text-to-text) |
| Domains | Social, Spoken |
| Reference | LMEB: Long-horizon Memory Embedding Benchmark |
Source datasets:
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_task("LoCoMo")
model = mteb.get_model(YOUR_MODEL)
mteb.evaluate(model, task)
To learn more about how to run models on mteb task check out the GitHub repository.
Citation
If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing as a part of the MMTEB Contribution.
@misc{zhao2026lmeb,
archiveprefix = {arXiv},
author = {Zhao, Xinping and Hu, Xinshuo and Xu, Jiaxin and Tang, Danyu and Zhang, Xin and Zhou, Mengjia and Zhong, Yan and Zhou, Yao and Shan, Zifei and Zhang, Meishan and Hu, Baotian and Zhang, Min},
eprint = {2603.12572},
primaryclass = {cs.CL},
title = {LMEB: Long-horizon Memory Embedding Benchmark},
url = {https://arxiv.org/abs/2603.12572},
year = {2026},
}
@article{enevoldsen2025mmtebmassivemultilingualtext,
title={MMTEB: Massive Multilingual Text Embedding Benchmark},
author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
publisher = {arXiv},
journal={arXiv preprint arXiv:2502.13595},
year={2025},
url={https://arxiv.org/abs/2502.13595},
doi = {10.48550/arXiv.2502.13595},
}
@article{muennighoff2022mteb,
author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Loïc and Reimers, Nils},
title = {MTEB: Massive Text Embedding Benchmark},
publisher = {arXiv},
journal={arXiv preprint arXiv:2210.07316},
year = {2022}
url = {https://arxiv.org/abs/2210.07316},
doi = {10.48550/ARXIV.2210.07316},
}
Dataset Statistics
Dataset Statistics
The following code contains the descriptive statistics from the task. These can also be obtained using:
import mteb
task = mteb.get_task("LoCoMo")
desc_stats = task.metadata.descriptive_stats
{
"test": {
"num_samples": 31386,
"number_of_characters": 5956920,
"documents_text_statistics": {
"total_text_length": 5845720,
"min_text_length": 74,
"average_text_length": 198.76640598435907,
"max_text_length": 532,
"unique_texts": 5882
},
"documents_image_statistics": null,
"documents_audio_statistics": null,
"queries_text_statistics": {
"total_text_length": 111200,
"min_text_length": 12,
"average_text_length": 56.2753036437247,
"max_text_length": 148,
"unique_texts": 1964
},
"queries_image_statistics": null,
"queries_audio_statistics": null,
"relevant_docs_statistics": {
"num_relevant_docs": 2800,
"min_relevant_docs_per_query": 1,
"average_relevant_docs_per_query": 1.417004048582996,
"max_relevant_docs_per_query": 19,
"unique_relevant_docs": 2389
},
"top_ranked_statistics": {
"num_top_ranked": 1188911,
"min_top_ranked_per_query": 369,
"average_top_ranked_per_query": 601.6756072874493,
"max_top_ranked_per_query": 689
},
"hf_subset_descriptive_stats": {
"single_hop": {
"num_samples": 6722,
"number_of_characters": 1219368,
"documents_text_statistics": {
"total_text_length": 1169144,
"min_text_length": 74,
"average_text_length": 198.76640598435907,
"max_text_length": 532,
"unique_texts": 5882
},
"documents_image_statistics": null,
"documents_audio_statistics": null,
"queries_text_statistics": {
"total_text_length": 50224,
"min_text_length": 15,
"average_text_length": 59.79047619047619,
"max_text_length": 131,
"unique_texts": 829
},
"queries_image_statistics": null,
"queries_audio_statistics": null,
"relevant_docs_statistics": {
"num_relevant_docs": 893,
"min_relevant_docs_per_query": 1,
"average_relevant_docs_per_query": 1.063095238095238,
"max_relevant_docs_per_query": 4,
"unique_relevant_docs": 772
},
"top_ranked_statistics": {
"num_top_ranked": 510502,
"min_top_ranked_per_query": 369,
"average_top_ranked_per_query": 607.7404761904762,
"max_top_ranked_per_query": 689
}
},
"multi_hop": {
"num_samples": 6162,
"number_of_characters": 1182490,
"documents_text_statistics": {
"total_text_length": 1169144,
"min_text_length": 74,
"average_text_length": 198.76640598435907,
"max_text_length": 532,
"unique_texts": 5882
},
"documents_image_statistics": null,
"documents_audio_statistics": null,
"queries_text_statistics": {
"total_text_length": 13346,
"min_text_length": 21,
"average_text_length": 47.66428571428571,
"max_text_length": 101,
"unique_texts": 280
},
"queries_image_statistics": null,
"queries_audio_statistics": null,
"relevant_docs_statistics": {
"num_relevant_docs": 875,
"min_relevant_docs_per_query": 1,
"average_relevant_docs_per_query": 3.125,
"max_relevant_docs_per_query": 19,
"unique_relevant_docs": 698
},
"top_ranked_statistics": {
"num_top_ranked": 166614,
"min_top_ranked_per_query": 369,
"average_top_ranked_per_query": 595.05,
"max_top_ranked_per_query": 689
}
},
"temporal_reasoning": {
"num_samples": 6203,
"number_of_characters": 1184901,
"documents_text_statistics": {
"total_text_length": 1169144,
"min_text_length": 74,
"average_text_length": 198.76640598435907,
"max_text_length": 532,
"unique_texts": 5882
},
"documents_image_statistics": null,
"documents_audio_statistics": null,
"queries_text_statistics": {
"total_text_length": 15757,
"min_text_length": 21,
"average_text_length": 49.087227414330215,
"max_text_length": 88,
"unique_texts": 321
},
"queries_image_statistics": null,
"queries_audio_statistics": null,
"relevant_docs_statistics": {
"num_relevant_docs": 375,
"min_relevant_docs_per_query": 1,
"average_relevant_docs_per_query": 1.1682242990654206,
"max_relevant_docs_per_query": 4,
"unique_relevant_docs": 319
},
"top_ranked_statistics": {
"num_top_ranked": 189039,
"min_top_ranked_per_query": 369,
"average_top_ranked_per_query": 588.9065420560747,
"max_top_ranked_per_query": 689
}
},
"open_domain": {
"num_samples": 5971,
"number_of_characters": 1174409,
"documents_text_statistics": {
"total_text_length": 1169144,
"min_text_length": 74,
"average_text_length": 198.76640598435907,
"max_text_length": 532,
"unique_texts": 5882
},
"documents_image_statistics": null,
"documents_audio_statistics": null,
"queries_text_statistics": {
"total_text_length": 5265,
"min_text_length": 12,
"average_text_length": 59.157303370786515,
"max_text_length": 148,
"unique_texts": 89
},
"queries_image_statistics": null,
"queries_audio_statistics": null,
"relevant_docs_statistics": {
"num_relevant_docs": 197,
"min_relevant_docs_per_query": 1,
"average_relevant_docs_per_query": 2.2134831460674156,
"max_relevant_docs_per_query": 17,
"unique_relevant_docs": 185
},
"top_ranked_statistics": {
"num_top_ranked": 54774,
"min_top_ranked_per_query": 419,
"average_top_ranked_per_query": 615.438202247191,
"max_top_ranked_per_query": 689
}
},
"adversarial": {
"num_samples": 6328,
"number_of_characters": 1195752,
"documents_text_statistics": {
"total_text_length": 1169144,
"min_text_length": 74,
"average_text_length": 198.76640598435907,
"max_text_length": 532,
"unique_texts": 5882
},
"documents_image_statistics": null,
"documents_audio_statistics": null,
"queries_text_statistics": {
"total_text_length": 26608,
"min_text_length": 23,
"average_text_length": 59.65919282511211,
"max_text_length": 129,
"unique_texts": 446
},
"queries_image_statistics": null,
"queries_audio_statistics": null,
"relevant_docs_statistics": {
"num_relevant_docs": 460,
"min_relevant_docs_per_query": 1,
"average_relevant_docs_per_query": 1.031390134529148,
"max_relevant_docs_per_query": 2,
"unique_relevant_docs": 415
},
"top_ranked_statistics": {
"num_top_ranked": 267982,
"min_top_ranked_per_query": 369,
"average_top_ranked_per_query": 600.8565022421525,
"max_top_ranked_per_query": 689
}
}
}
}
}
This dataset card was automatically generated using MTEB