datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
LLaVA-NeXT-Interleave-Bench
LLaVA-Interleave Bench Dataset Card
Dataset details
Dataset type:
LLaVA-Interleave Bench is a comprehensive set of multi-image datasets that are collected from public datasets or generated by the GPT-4V API.
It is constructed for evaluating the interleaved multi-image reaoning capbilities of LMMs.
Dataset date:
LLaVA-Interleave Bench was collected in April 2024, and released in June 2024.
Paper or resources for more information:
Blog:… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/LLaVA-NeXT-Interleave-Bench.EMMA
Dataset Description
EMMA (Enhanced MultiModal reAsoning) is a benchmark targeting organic multimodal reasoning across mathematics, physics, chemistry, and coding.
EMMA tasks demand advanced cross-modal reasoning that cannot be solved by thinking separately in each modality, offering an enhanced test suite for MLLMs' reasoning capabilities.
EMMA is composed of 2,788 problems, of which 1,796 are newly constructed, across four domains. Within each subject, we further provide… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/EMMA.EMMA-mini
Dataset Description
EMMA (Enhanced MultiModal reAsoning) is a benchmark targeting organic multimodal reasoning across mathematics, physics, chemistry, and coding.
EMMA tasks demand advanced cross-modal reasoning that cannot be solved by thinking separately in each modality, offering an enhanced test suite for MLLMs' reasoning capabilities.
EMMA is composed of 2,788 problems, of which 1,796 are newly constructed, across four domains. Within each subject, we further provide… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/EMMA-mini.