Omkar2118/datasets huggingface dataset:
CAIS
Full name: Chinese Artificial Intelligence Speakers

We collect utterances from the Chinese Artificial Intelligence Speakers (CAIS), and annotate them with slot tags and intent labels. The training, validation and test sets are split by the distribution of intents, where detailed statistics are provided in the supplementary material. Since the utterances are collected from speaker systems in the real world, intent labels are partial to the PlayMusic option. We adopt the BIOES tagging scheme for slots instead of the BIO2 used in the ATIS, since previous studies have highlighted meaningful improvements with this scheme (Ratinov and Roth, 2009) in the sequence labeling field

Introducing paper: CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding
HumanEval-X

HumanEval-X is a benchmark for evaluating the multilingual ability of code generative models. It consists of 820 high-quality human-crafted data samples (each with test cases) in Python, C++, Java, JavaScript, and Go, and can be used for various tasks, such as code generation and translation.

Introducing paper: CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X
PASTIS-R
Full name: Panoptic Segmentation of Radar and Optical Satellite image TIme Series

Extension of the [PASTIS benchmark](https://zenodo.org/records/5012942#.YaUaQ7so-V6) with radar and optical image time series.

Introducing paper: Multi-Modal Temporal Attention Models for Crop Mapping from Satellite Time Series