Omkar2118/datasets huggingface dataset:
BioRED

BioRED is a first-of-its-kind biomedical relation extraction dataset with multiple entity types (e.g. gene/protein, disease, chemical) and relation pairs (e.g. gene–disease; chemical–chemical) at the document level, on a set of600 PubMed abstracts. Furthermore, BioRED label each relation as describing either a novel finding or previously known background knowledge, enabling automated algorithms to differentiate between novel and background information.

Introducing paper: BioRED: A Rich Biomedical Relation Extraction Dataset
Vi-Fi Multi-modal Dataset

A large-scale multi-modal dataset to facilitate research and studies that concentrate on vision-wireless systems.
The Vi-Fi dataset is a large-scale multi-modal dataset that consists of vision, wireless and smartphone motion sensor data of multiple participants and passer-by pedestrians in both indoor and outdoor scenarios. In Vi-Fi, vision modality includes RGB-D video from a mounted camera. Wireless modality comprises smartphone data from participants including WiFi FTM and IMU measurements.

The presence of Vi-Fi dataset facilitates and innovates multi-modal system research, especially, vision-wireless sensor data fusion, association and localization.

(Data collection was in accordance with IRB protocols and subject faces have been blurred for subject privacy.)
DistNLI

This dataset is named as the DistNLI dataset, which is a synthesized benchmark aiming to probe neural network models from the aspect of conjunctions on distributivity in NLI task in American English. DistNLI consists of sentence minimal pairs (premise and hypothesis) differentiated with conjunction structure within the pair and distributivity-related linguistic phenomenon. DistNLI is compiled with 328 sentences so far (164 for distributive and 164 for ambiguous predicates), annotated by 4 proficient English speakers with a background in NLP and Linguistics. Due to the specificity of the linguistic phenomenon involved and its size, this DistNLI dataset should only be used as an adversarial dataset in the investigation of distributivity of verb predication.

Introducing paper: Testing Pre-trained Language Models' Understanding of Distributivity via Causal Mediation Analysis