data-science
generalization-science-dataRETECO-SemEval2027
RETECO
Training & Development Data · SemEval-2027 Task 1
Retrieval that must reason about when evidence applies
and what the conversation has already established.
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🧰 Starter kit
🎯 At a glance
What
Official training and development data for RETECO, the SemEval-2027 shared task on reasoning-oriented retrieval
Scope
2 tracks · 5 sub-tracks · 24 self-contained domains… See the full description on the dataset page: https://huggingface.co/datasets/DataScience-UIBK/RETECO-SemEval2027.sciencemysterybench-dataAI-For-Science-Retreat-DataDataScience-Instruct-500K
DeepAnalyze: Agentic Large Language Models for Autonomous Data Science
Authors: Shaolei Zhang, Ju Fan*, Meihao Fan, Guoliang Li, Xiaoyong Du
DeepAnalyze is the first agentic LLM for autonomous data science. It can autonomously complete a wide range of data-centric tasks without human intervention, supporting:
🛠 Entire data science pipeline: Automatically perform any data science tasks such as data preparation, analysis, modeling, visualization, and report generation.
🔍… See the full description on the dataset page: https://huggingface.co/datasets/RUC-DataLab/DataScience-Instruct-500K.gut-microbiome-allergy-data
Dataset Card for Gut Microbiome–Food Allergy Prediction Datasets
Dataset Summary
This repository contains multiple human gut microbiome datasets curated for predicting food allergy development.
Each dataset corresponds to a distinct cohort with longitudinal microbiome sampling, providing both metadata and derived embeddings suitable for machine learning.
The datasets are designed to support binary classification of subjects into healthy vs allergic categories, enabling… See the full description on the dataset page: https://huggingface.co/datasets/hugging-science/gut-microbiome-allergy-data.