Showing 61-104 of 104 articles
NuminaMath
NuminaMath is a family of openly licensed competition-mathematics resources developed by the non-profit Project Numina, spanning the largest public dataset of...
MathematicsOpen Source AI
One-Hot Encoding
See also: Machine learning terms One-hot encoding is a data preprocessing technique that converts a categorical variable with distinct categories into ...
Machine Learning
Open Catalyst Project
The Open Catalyst Project (OCP) is a research collaboration between Meta AI's Fundamental AI Research group (FAIR) and Carnegie Mellon University's Department...
AI for ScienceMeta AI
Open X-Embodiment
Open X-Embodiment (OXE) is a large-scale collaborative robotics research initiative, led by Google DeepMind and announced in October 2023, that produced the...
Google DeepMindRobotics
OpenOrca
OpenOrca is a large open-source instruction-tuning dataset that augments the FLAN Collection with chain-of-thought responses generated by OpenAI's GPT-3.5 and...
Large Language ModelsOpen Source AI
OpenThoughts
OpenThoughts is an open-source initiative and a series of datasets of verified reasoning traces created to train open reasoning models. Launched on January 28,...
Machine Learning
Outlier Detection
Outlier detection is the process of identifying data points, observations, or patterns that deviate so markedly from the rest of a dataset that they are likely...
Machine LearningStatistics
Oversampling
Oversampling is a data preprocessing technique in machine learning that fixes class imbalance by increasing the number of minority class examples in the...
Machine Learning
PASCAL VOC
PASCAL VOC (Pattern Analysis, Statistical Modelling and Computational Learning Visual Object Classes) is a long-running benchmark dataset and annual challenge...
AI BenchmarksComputer Vision
Participation Bias
Participation bias is a systematic error that arises when the individuals who choose to take part in a study, survey, or data collection effort differ in...
Machine LearningStatistics
Preprocessing
Preprocessing is the stage of a machine learning workflow that transforms raw data into a clean, consistent, numerical format that learning algorithms can use....
Machine Learning
Project Aria
Project Aria is an egocentric data-collection research program run by Meta's Reality Labs Research. It was announced on September 16, 2020 [1][2]. The program...
Computer VisionMeta AI
Proxy labels
A proxy label (also called a surrogate label) is an observable, easy-to-collect stand-in for the true target a model should predict, used to train that model...
Machine Learning
Quantile bucketing
See also: Discretization, Feature engineering, Quantile Quantile bucketing, also called quantile binning, equal-frequency binning, or quantile discretization,...
Machine Learning
Rater
See also: Machine learning terms A rater is a person (or, increasingly, a model) who assigns labels, scores, or judgments to data items so those items can be...
RedPajama
RedPajama is a family of large-scale, openly licensed datasets for training large language models (LLMs), created by Together AI with academic and open-source...
Machine LearningNatural Language Processing
RefinedWeb
RefinedWeb is a large-scale English pretraining dataset for large language models, built from filtered and deduplicated Common Crawl web data alone and...
Large Language ModelsOpen Source AI
Reporting Bias
Reporting bias is a type of data bias in machine learning that occurs when the frequency of events, properties, or outcomes captured in a dataset does not...
AI EthicsMachine Learning
RoboCasa
RoboCasa is a large-scale simulation framework for training generalist robots to perform everyday household tasks. Developed by researchers at The University...
Embodied AINVIDIA
Sampling Bias
Sampling bias is a systematic error in statistics and machine learning that occurs when a sample is collected so that some members of the intended population...
AI EthicsMachine Learning
Scaling
In machine learning and artificial intelligence, scaling is an umbrella term for several distinct practices: (1) feature scaling, the data-preprocessing step...
Machine Learning
Segment Anything Model and Dataset (SAM and SA-1B)
Segment Anything Model (SAM) is a promptable image segmentation foundation model released by Meta AI on April 5, 2023 that lets users "cut out" any object in...
AI ModelsAI Research
Selection Bias
Selection bias is a systematic error that occurs when the data used for analysis, training, or evaluation does not accurately represent the population or...
AI EthicsMachine Learning
Self-Instruct
Self-Instruct is a semi-automated framework for aligning a pretrained large language model with instruction-following behavior by bootstrapping its training...
Large Language ModelsTraining & Optimization
SlimPajama
SlimPajama is a 627-billion-token English-language pre-training corpus for large language models, produced by Cerebras Systems in collaboration with the...
Large Language ModelsOpen Source AI
Snorkel
Snorkel is an open-source software framework and methodology for programmatic data labeling that started at Stanford University in 2015 and is licensed under...
Machine LearningOpen Source AI
Sparse Feature
A sparse feature is a feature in machine learning whose values are predominantly zero or empty across a dataset. Google's Machine Learning Crash Course defines...
Machine Learning
Sparse Representation
Sparse representation is a data encoding strategy in which most values in a vector, matrix, or tensor are zero (or near zero), with only a small fraction of...
Machine Learning
SuperGLUE
SuperGLUE is a public benchmark for evaluating general-purpose English language understanding in machine learning systems, consisting of eight challenging...
AI BenchmarksNatural Language Processing
Surge AI
Surge AI (legal entity Surge Labs Inc., often stylized SurgeHQ) is an American data annotation and human evaluation company headquartered in San Francisco,...
AI Companies
Synthetic Feature
A synthetic feature (also called a constructed feature or derived feature) is a variable created by transforming, combining, or otherwise manipulating one or...
Data ScienceMachine Learning
Synthetic data
Synthetic data is data that is artificially generated by algorithms, simulations, or generative models rather than collected from real-world events, used as a...
Tf.Example
See also: Machine learning terms tf.train.Example (commonly written as tf.Example) is a Protocol Buffers message type that TensorFlow uses as its standard...
Developer Tools
The Pile (dataset)
The Pile is an 825.18 GiB (approximately 886 GB) English text corpus designed for training large language models, assembled from 22 diverse, high-quality...
Machine LearningNatural Language Processing
The Stack (BigCode dataset)
The Stack is a family of large, permissively-licensed source-code datasets built by the BigCode project, an open scientific collaboration jointly led by...
AI Code GenerationOpen Source AI
The Stack v2
The Stack v2 is a large open dataset of source code released by BigCode in February 2024 as the training dataset behind the StarCoder2 family of code models....
Machine Learning
Training Set
A training set is the portion of a dataset that a machine learning model learns from: the labeled examples a model processes during training to adjust its...
Machine Learning
Training-Serving Skew
Training-serving skew is a difference between a machine learning model's performance during training and its performance during serving (production inference)....
MLOpsMachine Learning
TxT360
TxT360 is an open large-scale pretraining corpus for large language models, released in October 2024 by the LLM360 project, a collaboration led by Petuum and...
Large Language ModelsOpen Source AI
UltraChat
UltraChat is a large-scale synthetic multi-turn instructional conversation dataset released in May 2023 by the OpenBMB group at Tsinghua University, comprising...
Chinese AILarge Language Models
WRAP (Web Rephrase Augmented Pre-training)
WRAP (Web Rephrase Augmented Pre-training) is a synthetic-data pre-training method introduced in the paper "Rephrasing the Web: A Recipe for Compute and...
Large Language ModelsTraining & Optimization
Weak supervision
Weak supervision is a machine learning paradigm in which models are trained from noisy, limited, imprecise, or programmatically generated labels rather than...
Machine Learning
WildChat
WildChat is a large public corpus of real conversations between human users and ChatGPT, released by researchers at the Allen Institute for AI (AI2) and...
Machine Learning
Z-Score Normalization
See also: Machine learning terms Z-score normalization, also called standardization, standard score normalization, or z-score scaling, is a data preprocessing...
Machine Learning