modal
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All datasets matching “modal”multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR
PreFLMR M2KR Dataset Card
Dataset details
Dataset type:
M2KR is a benchmark dataset for multimodal knowledge retrieval. It contains a collection of tasks and datasets for training and evaluating multimodal knowledge retrieval models.
We pre-process the datasets into a uniform format and write several task-specific prompting instructions for each dataset. The details of the instruction can be found in the paper. The M2KR benchmark contains three types of tasks:… See the full description on the dataset page: https://huggingface.co/datasets/BByrneLab/multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR.Multi-modal_dataset_named_SynthSoM
SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM)
📌 Overview
SynthSoM dataset covers eight rich and diverse application scenarios, including vehicle-road coordination, low-altitude economy, smart campus, as well as typical urban, suburban, rural, and campus environments. The urban scenario further includes intersections, ultra-wide lanes, elevated interchanges, and CBD areas; the suburban scenario… See the full description on the dataset page: https://huggingface.co/datasets/pku-pcni-lab/Multi-modal_dataset_named_SynthSoM.MixBench25MixBench is a benchmark for evaluating mixed-modality retrieval. It contains queries and corpora from four datasets: MSCOCO, Google_WIT, VisualNews, and OVEN. Each subset provides: query, corpus, mixed_corpus, and qrel splits.Multi-modal-Self-instruct
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You can download the zip dataset directly, and both train and test subsets are collected in Multi-modal-Self-instruct.zip.
Dataset Description
Multi-Modal Self-Instruct dataset utilizes large language models and their code capabilities to synthesize massive abstract images and visual reasoning instructions across daily scenarios. This benchmark… See the full description on the dataset page: https://huggingface.co/datasets/zwq2018/Multi-modal-Self-instruct.NEXUS-temporal_hierarchical_multi-modal
NEXUS: Neural Evolution for eXtensible Universal Semantics Dataset
(Temporal Multimodal Slices)
This dataset is a multi-modal, hierarchical, temporal representation derived from HuggingFaceFV/finevideo. It is designed for streaming training where the primary unit is a 10 ms "slice" that aggregates upward into moments (100 ms), seconds (1 s), experiences (10 s), and minutes (60 s).
It is meant to represent an extensible stream of "experience" as there are… See the full description on the dataset page: https://huggingface.co/datasets/Ardea/NEXUS-temporal_hierarchical_multi-modal.multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR_CN
PreFLMR M2KR Dataset Card
Dataset details
Dataset type:
M2KR is a benchmark dataset for multimodal knowledge retrieval. It contains a collection of tasks and datasets for training and evaluating multimodal knowledge retrieval models.
We pre-process the datasets into a uniform format and write several task-specific prompting instructions for each dataset. The details of the instruction can be found in the paper. The M2KR benchmark contains three types of tasks:… See the full description on the dataset page: https://huggingface.co/datasets/BByrneLab/multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR_CN.