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Jun 11, 2024 · The first benchmark specifically designed to systematically evaluate the capability of existing MLLMs to comprehend long multimodal documents.
Needle In A Multimodal Haystack (MM-NIAH) is a comprehensive benchmark designed to systematically evaluate the capability of existing MLLMs to comprehend long ...
Jun 17, 2024 · We introduce the MultiModal Needle-in-a-haystack (MMNeedle) benchmark, specifically designed to assess the long-context capabilities of MLLMs.
The paper proposes the first "needle in a haystack" dataset to evaluate the comprehension of long documents of multi-modal models. The experiments effectively ...
Jun 17, 2024 · Needle In A Multimodal Haystack (MM-NIAH) is a comprehensive benchmark designed to systematically evaluate the capability of existing MLLMs to ...
Overview. We introduce Needle In A Multimodal Haystack ( Logo mm-niah), a benchmark designed to systematically evaluate the comprehension ability for ...
In this work, we present Needle In A Multimodal. Haystack (MM-NIAH), the first benchmark specifically designed to systemati- cally evaluate the capability of ...
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This work presents Needle In A Multimodal Haystack (MM-NIAH), the first benchmark specifically designed to systematically evaluate the capability of ...
Jun 27, 2024 · This repo contains the code and data for our benchmark paper: Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal LLMs.
Jun 11, 2024 · The first benchmark specifically designed to systematically evaluate the capability of existing MLLMs to comprehend long multimodal documents.