This task is used to evaluate the reranking performance for visual document retrieval. The candidates for reranking are the top-50 pages retrieved by the BAAI/bge-m3 model. This dataset, Energy Fr, is a corpus of reports on energy supply in europe, intended for complex-document understanding tasks. Original queries were created in french, then translated to english, german, italian, portuguese and spanish.This version add the OCR'ed markdown to allow for comparison across image-text, image-only and text-only models. You can evaluate an embedding model on this dataset using the following code: To learn more about how to run models on mteb task check out the GitHub repository. If you use this…
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cc-by-4.0
This task is used to evaluate the reranking performance for visual document retrieval. The candidates for reranking are the top-50 pages retrieved by the BAAI/bge-m3 model. This task, Finance - EN, is a corpus of reports from american banking companies, intended for long-document understanding tasks. Original queries were created in english, then translated to french, german, italian, portuguese and spanish.This version add the OCR'ed markdown to allow for comparison across image-text, image-only and text-only models. You can evaluate an embedding model on this dataset using the following code: To learn more about how to run models on mteb task check out the GitHub repository. If you use…
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cc-by-4.0
This task is used to evaluate the reranking performance for visual document retrieval. The candidates for reranking are the top-50 pages retrieved by the BAAI/bge-m3 model. This task, Finance - FR, is a corpus of reports from french companies in the luxury domain, intended for long-document understanding tasks. Original queries were created in french, then translated to english, german, italian, portuguese and spanish.This version add the OCR'ed markdown to allow for comparison across image-text, image-only and text-only models. You can evaluate an embedding model on this dataset using the following code: To learn more about how to run models on mteb task check out the GitHub repository. If…
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cc-by-4.0
This task is used to evaluate the reranking performance for visual document retrieval. The candidates for reranking are the top-50 pages retrieved by the BAAI/bge-m3 model. This dataset, HR, is a corpus of reports released by the european union, intended for complex-document understanding tasks. Original queries were created in english, then translated to french, german, italian, portuguese and spanish.This version add the OCR'ed markdown to allow for comparison across image-text, image-only and text-only models. You can evaluate an embedding model on this dataset using the following code: To learn more about how to run models on mteb task check out the GitHub repository. If you use this…
Publicly accessible
cc-by-4.0
This task is used to evaluate the reranking performance for visual document retrieval. The candidates for reranking are the top-50 pages retrieved by the BAAI/bge-m3 model. This dataset, Industrial reports, is a corpus of technical documents on military aircraft (fueling, mechanics...), intended for complex-document understanding tasks. Original queries were created in english, then translated to french, german, italian, portuguese and spanish.This version add the OCR'ed markdown to allow for comparison across image-text, image-only and text-only models. You can evaluate an embedding model on this dataset using the following code: To learn more about how to run models on mteb task check out…
Publicly accessible
cc-by-4.0
This task is used to evaluate the reranking performance for visual document retrieval. The candidates for reranking are the top-50 pages retrieved by the BAAI/bge-m3 model. This dataset, Pharmaceutical, is a corpus of slides from the FDA, intended for long-document understanding tasks. Original queries were created in english, then translated to french, german, italian, portuguese and spanish.This version add the OCR'ed markdown to allow for comparison across image-text, image-only and text-only models. You can evaluate an embedding model on this dataset using the following code: To learn more about how to run models on mteb task check out the GitHub repository. If you use this dataset…
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cc-by-4.0
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This repository is the immutable audit copy of raw Weibo API responses collected by a private archive. Original gzip snapshots are stored unchanged inside bounded TAR shards with SHA-256 manifests. Older snapshots remain individually addressable. The database records each repository, entry and byte range. The parsed and authoritative text lives in the operator's PostgreSQL database; these files exist for audit and re-processing without re-fetching from Weibo. This dataset uses Hugging Face manual gated access. Access requests are reviewed by the repository owner. Do not mirror, redistribute, bulk-download, or use the responses to identify or contact individuals. Source content may contain…
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other
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apache-2.0
两位抖音博主的视频数据集 + SAM 2.1 语义分割结果，按博主（抖音号/UID）分别打包。 视频文件名为 序号作品ID.mp4；metadata.json 中 awemeid 与作品 ID 对应，含标题/点赞/评论等元数据。 tar 均为未压缩归档（纯打包，字节无损），解压即得与原始一致的目录树。 - frameXXXseg.png：分割叠加图（原始帧 + 彩色实例掩码） - masks.npz：键 frameXXX 对应 (Nmasks, H, W) bool 掩码数组 - report.json：每帧掩码数量与耗时统计 掩码为类无关实例分割；需要类别标签可自行接 CLIP / Grounding DINO。 recon.npz 内含每帧 pred{i}pts（点云）与 view{i}img（RGB）等，可用于点云可视化/深度/位姿估计。 四个 tar 相互独立、内部路径均相对 data/，可并行下载解压。
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This dataset was generated using the inference script with the following configuration: The dataset contains the following key columns: - query: The original query - entitya: Starting entity - entityb: Target entity - relb: Target relationship - pathprediction: Generated connection paths - promptforpath: Prompts used for path generation You can load this dataset using: This dataset was generated on 2026-10-09 23:45:16 using the inference pipeline with the above configuration.
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mit
Lossless archive of 1,073 completed GPT-OSS raw NPZ files from the A1 PRM800K extension collection, outside the earlier 5,000-trace pilot archive. Original source payload: 11,414,646,710 bytes. This migration retains all existing step features, labels, checkpoints, manifests, completion receipts and reports locally. These are legacy replay signals, separate from the new 198,000-trace date-free GPT-OSS core. This is an archival repository, not a new benchmark or curated training split. Original source licenses and model terms continue to apply; no new license is asserted. This follows the tar-shard layout of the previous PRM800K archive. During migration, each shards/signals-.tar has a…
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a12cryptoresearch · klines spot de Binance (binance.vision) en parquet 1s/symbol= /date= /data.parquet — velas de 1 segundo, particion hive por simbolo y dia UTC. 1m/klines1m.parquet — velas de 1 minuto de todos los simbolos en UN fichero (columna symbol, ordenado por symbol, t; un row group por simbolo). Columnas: t = apertura de la vela en segundos epoch UTC; o,h,l,c precio; v volumen base; qv volumen quote; n trades; tbb / tbq volumen comprador
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mit
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mit
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ACID (Aerial Coastline Imagery Dataset) camera trajectories and frames, in the pixelSplat chunk release, repacked as random-access WebDataset shards. Every file in this repository was verified against the source copy (same file set, same byte sizes). WebDataset tar shards (about 3 GB each), one tar row per scene, indexed for random access with ultar.utix files (msgpack rows of entry keys, offsets and sizes, so they can be read without ultar). Every scene row holds: -.tar.utix — the ultar row index (offsets and sizes of every entry). -.tar.centres.bin — float32 camera centres per frame per scene (a small sidecar used for farthest-point view sampling); header DPFV, then a per-scene offset…
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mit
10K<n<100K
This dataset was created using LeRobot.
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apache-2.0
