A researcher has published the OpenGauntlet research catalog, a public resource containing information on 168 text-to-speech systems and 106 speech-to-text systems. The directories cover open and hosted models, licensing, hardware requirements, languages, capabilities, lifecycle status, source information, and published benchmark data where available.
A monthly-refreshed compliance matrix has been published for all 4,893 Indic-language datasets on the Hugging Face Hub, revealing that 65.1% declare no license tag as of August 1, 2026.
Calibra v0.7.1 introduces a new Dataset Integrity stage that runs before quality and coverage analysis to help users verify if their robotics datasets are trustworthy.
Calibra is an open-source toolkit designed to help researchers audit robot datasets and identify quality issues before training policies. The first public release includes a Robot Dataset Health Check interactive Space for auditing LeRobot datasets and a benchmark of 30 public LeRobot datasets with health scores.
Huggy Engine has published the Huggy Database on Hugging Face, described as the largest open dataset of French horse racing available. The release provides 30 years of complete daily coverage from 1996 to 2026 for use in machine learning applications.
Hugging Face has released The Stack v3, described as the largest open code dataset to date. The release provides two distinct access methods to accommodate different user needs.
louidev has released the GlassBallAI dataset on Hugging Face, capturing live forecasting behavior from Google's Gemini models before outcomes are known. The dataset contains over 3,655 rows of data collected between February 17 and May 19, 2026, covering Gemini 2.5 Flash, 2.5 Pro, 2.5 Flash Lite, and 3.0 Flash Preview.
IBM has open-sourced CodeAlchemy, a pipeline and synthetic dataset designed to improve AI model performance by pairing code with execution traces. The release includes nearly 1 trillion tokens across 15 programming languages, totaling at least 200 times the size of Wikipedia.
A user shares their experience with the computational expense of generating training datasets from physics simulations, such as fluid flow and structural fields. They highlight that the primary challenge is not the model architecture but the difficulty of building a large and diverse dataset when each sample is costly to produce.
Researchers propose Cluster-based Sequential Feature Selection (CSFS), a novel clustering-based wrapper method for automatic and efficient feature selection in renewable energy prediction pipelines. The approach addresses the lack of systematic methods for selecting input features from the large number of available monitoring and environmental variables.
Researchers propose Cluster-based Sequential Feature Selection (CSFS), a novel, model-agnostic wrapper method designed to address the lack of systematic feature selection in wind and solar power prediction. The approach aims to provide automatic, efficient, and reliable feature selection for renewable energy pipelines.
Researchers introduce ViHoRec, a public dataset of 18,267 interactions between 6,832 users and 560 hotels for Vietnamese hotel recommendation. The resource addresses challenges in cross-platform entity resolution and privacy-preserving release using HMAC pseudonyms.
Researchers introduce FormalAnalyticGeo, a scalable framework for the fully automatic generation of multimodal analytic geometry problems that eliminates the need for human annotation. The system utilizes a formal intermediate representation called CDL to bridge problem text with precise diagram rendering through a Signed Distance Field engine.
Researchers have developed a method for biomolecular cryptography that uses DNA origami to transform secret messages into nano-Morse code. This approach aims to secure information using biological molecules rather than traditional computer-based cryptographic algorithms.
A user has created a derivative dataset based on the 'Orthogonal Model of Emotions' by removing one dimension and replacing ontological cluster labels with 10 emoji categories.
A new multi-modal dataset called the In-Car Sign Language (ICSL) corpus has been introduced to address the challenges of using sign language within shared mobility services like taxis and ride-sharing platforms. The resource focuses on Brazilian Sign Language (Libras) to improve public transport accessibility for the Deaf and Hard-of-Hearing community in confined vehicle interiors.
Researchers investigate semantic change in 23 German and 26 English noun compounds by introducing the Compositionality Trend Prediction task, evaluated against a novel dataset of per-decade diachronic ratings. Contrary to literature positing a decisive tendency for compounds to become less compositional, the study finds only a small negative trend over time.
Researchers have released JobHop v2, an improved version of the publicly available JobHop dataset designed for workforce planning and labor market analysis. Constructed via end-to-end large language model extraction from approximately 440,000 pseudonymized multilingual resumes provided by VDAB, the Flemish Public Employment Service, the dataset contains 355,315 career trajectories.
A project using the University of Oxford's Their Finest Hour Online Archive evaluated three Natural Language Processing approaches—Named Entity Recognition, Keyword Extraction, and Topic Modelling—to automate keyword extraction at scale. The study tested these methods across a range of techniques, from traditional statistical models to modern generative AI neural networks.
Researchers present a systematic empirical evaluation of learning curve convergence rates to address the lack of data-driven guidelines for determining minimum sample sizes in inertial sensor-based classification tasks.