Omkar2118/datasets huggingface dataset:
MVSEC-SEG

Based on the [MVSEC](https://daniilidis-group.github.io/mvsec/) dataset, we select some image-event pairs to evaluate the segmentation performance, namely MVSEC-SEG, which only serves as a test set. The MVSEC-SEG consists of 500 image-event pairs each in ”indoor flying1” and ”outdoor day2” sequences, containing 54,600 masks.

Introducing paper: Segment Any Events via Weighted Adaptation of Pivotal Tokens
MVALUE
Full name: Multilingual human VALUE dataset

Multilingual human VALUE(MVALUE) is a multilingual dataset covering 7 concepts of human values: morality, deontology, utilitarianism, fairness, truthfulness, toxicity and harmfulness, each concept subset of it includes positive and negative texts that represent the two opposing directions of the concept. We performed translation on collected human value datasets from English into 15 non-English languages using Google Translate. These languages belong to various language families, including Indo-European (Catalan, French, Indonesian, Portuguese, Spanish), NigerCongo (Chichewa, Swahili), Dravidian (Tamil, Telugu), Uralic (Finnish, Hungarian), Sino-Tibetan (Chinese), Japonic (Japanese), Koreanic (Korean) and Austro-Asiatic (Vietnamese).

In detail, we collected three subsets of the ETHICS dataset (Hendrycks et al.,2021) for morality, deontology, and utilitarianism. Regarding fairness, truthfulness, toxicity, and harmfulness, we chose the StereoSet (Nadeem et al., 2021), TruthfulQA (Lin et al., 2022), REALTOXICITYPROMPTS (Gehman et al., 2020), AdvBench (Zou et al., 2023b) dataset, respectively. Some of these dataset are naturally composed of positive and negative text pairs, we reformatted the rest ones. Refer to Appendix A of [our paper](https://arxiv.org/pdf/2402.18120.pdf) for detailed definitions, data splits, and examples of each human value of MVALUE dataset.

Introducing paper: Exploring Multilingual Concepts of Human Value in Large Language Models: Is Value Alignment Consistent, Transferable and Controllable across Languages?
DDD17-SEG

Based on the  [DDD17](https://pkuml.org/resources/pku-ddd17-car.html) dataset, we select some image-event pairs to evaluate the segmentation performance, namely DDD17-SEG, which only serves as a test set. The DDD17-SEG consists of 1,000 image-event pairs in five sequences (dir0,dir1,dir3,dir4,dir7), containing 86,000 masks.

Introducing paper: Segment Any Events via Weighted Adaptation of Pivotal Tokens
DSEC-SEG

Based on the [DSEC](https://dsec.ifi.uzh.ch/) dataset, we select some image-event pairs to evaluate the segmentation performance, namely DSEC-SEG, which only serves as a test set. The DSEC-SEG consists of 1,000 image-event pairs in two sequences (zurich_city_01_a, zurich_city_04_c), containing 63,200 masks.

Introducing paper: Segment Any Events via Weighted Adaptation of Pivotal Tokens
IUPAC Standards Online

IUPAC Standards Online is a database built from IUPAC’s standards and recommendations, extracted from the journal Pure and Applied Chemistry (PAC).
Human Protein Atlas

The Human Protein Atlas contains images of histological sections from normal and cancer tissues obtained by immunohistochemistry. Antibodies are labeled with DAB (3,3'-diaminobenzidine) and the resulting brown staining indicates where an antibody has bound to its corresponding antigen.

Check https://www.nature.com/articles/s41592-019-0658-6
MMOS

Mix of Minimal Optimal Sets (MMOS) of dataset has two advantages for two aspects, higher performance and lower construction costs on math reasoning.

Introducing paper: An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning