19,997 machine learning datasets
19,997 dataset results
These are processed versions of the monthly lichess database release. Only games with stockfish analysis are included. The games have been converted from pgn to csv and the per move and per game information has been extracted. If you wish to see the original game files download the corresponding standard games database release from Lichess. The game_id column matches that used by lichess. The meaning of each column should be straightforward. The per move information tends to be from the perspective of the active player, although the cp is not, instead the cp_rel columns is the relative centipawn value.
A human-refined dataset of OpenAPI definitions based on the APIs.guru OpenAPI directory.
This dataset was created for the purpose of performing NER tasks. It utilizes the OpenFDA Device Recalls dataset, which has been processed and annotated for performing NER. The Device Recalls dataset has been further processed to extract the recall action element, which is utilized for annotation in this dataset.
A high quality speech prompted semantic segmentation dataset
A high quality sound prompted semantic segmentation dataset
The ULS23 training dataset contains 38,693 diverse lesions from chest-abdomen-pelvis CT examinations. For the challenge, we introduced two novel 3D annotated datasets targeting lesions in the pancreas and bones, which are traditionally challenging to segment. Additionally, we aggregate 10 publicly available datasets with a lesion segmentation component into a single, easily accessible data repository.
Useful for checking the physical reasoning capabilities in household agents. Made through human annotations of what type of object configurations we prefer for accomplishing a household task.
This Quantum Dots Stability Diagrams (QDSD) Dataset aggregates experimental stability diagrams of quantum dots from different research groups.
RoomSpace: a new benchmark designed to evaluate language models on spatial reasoning tasks demanding spatial relation knowledge and multi-hop reasoning. RoomSpace encompasses a comprehensive range of qualitative spatial relationships, including topological, directional, and distance relations. These relationships are presented from various viewpoints, with differing levels of granularity and density of relational constraints to simulate real-world complexities. This approach promotes a more accurate assessment of language models' capabilities in spatial reasoning tasks.
The DADE dataset, short for Driving Agents in Dynamic Environments, is a synthetic dataset designed for the training and evaluation of methods for the task of semantic segmentation in the context of autonomous driving agents navigating dynamic environments and weather conditions.
Large Language Models (LLMs) have the potential to enhance Agent-Based Modeling by better representing complex interdependent cybersecurity systems, improving cybersecurity threat modeling and risk management. Evaluating LLMs in this context is crucial for legal compliance and effective application development. Existing LLM evaluation frameworks often overlook the human factor and cognitive computing capabilities essential for interdependent cybersecurity. To address this gap, I propose OllaBench, a novel evaluation framework that assesses LLMs' accuracy, wastefulness, and consistency in answering scenario-based information security compliance and non-compliance questions.
AgentEval is part of the AgentGym framework, which is designed to evaluate and develop generally-capable Large Language Model-based (LLM-based) agents. AgentEval serves as a benchmark suite within AgentGym, providing a set of tasks and environments to assess the performance of these agents¹².
During the covid-19 era wearing face masks posed new challenges to face-related tasks, including facial recognition, face inpainting, expression recognition, and object removal. Mask region segmentation is a preliminary stage to tackle the occlusion issue corresponding to the face-related tasks. Existing masked face datasets are not procedure binary segmentation maps because Segmenting mask regions manually is a time-consuming operation. As a result, existing unmasking methods; synthesize training data by overlaying masks on existing face datasets. However, since these techniques rely on an artificially generated mask, their effects tend to seem unnatural. To address this issue, the masked face segmentation dataset(MFSD) provides the first public training dataset for the mask segmentation task.
Mediapi-RGB is a bilingual corpus of French Sign Language (LSF) and written French in the form of subtitled videos, accompanied by complementary data (various representations, segmentation, vocabulary, etc.). It can be used in academic research for a wide range of tasks, such as training or evaluating sign language (SL) extraction, recognition or translation models.
Confocal fluorescence microscopy is one of the most accessible and widely used imaging techniques for the study of biological processes at the cellular and subcellular levels. Scanning confocal microscopy allows the capture of high-quality images from thick three-dimensional (3D) samples, yet suffers from well-known limitations such as photobleaching and phototoxicity of specimens caused by intense light exposure, which limits its use in some applications, especially for living cells. Cellular damage can be alleviated by changing imaging parameters to reduce light exposure, often at the expense of image quality. Machine/deep learning methods for single-image super-resolution (SISR) can be applied to restore image quality by upscaling lower-resolution (LR) images to produce high-resolution images (HR). These SISR methods have been successfully applied to photo-realistic images due partly to the abundance of publicly available data. In contrast, the lack of publicly available data partl
InaGVAD is a Voice Activity Detection (VAD) and Speaker Gender Segmentation (SGS) dataset designed for representing the acoustic diversity of French TV and Radio programs. InaGVAD detailed description, together with a benchmark of 6 freely available VAD systems and 3 SGS systems, is provided in a paper presented in LREC-COLING 2024.
Dataset Description EUROPA is a dataset designed for training and evaluating multilingual keyphrase generation models in the legal domain. It consists of legal judgments from the Court of Justice of the European Union (EU) and includes instances in all 24 official EU languages.
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The ComTQA dataset is a visual table question answering benchmark. It includes images collected from FinTabNet and PubTables-1M, comprising a total of 9,070 QA pairs with 1,591 images. The dataset is designed to address tasks related to table question answering and is available in English. It falls under the size category of 1K<n<10K and is licensed under cc-by-nc-4.0¹.
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