The study introduces Blink, a novel benchmark for multimodal language models (LLMs) that uniquely focuses on core visual perception abilities not addressed in other evaluations. From basic pattern matching to intermediate reasoning and advanced visual understand...
实验设置不一致)带来的难以公平评测不同模型能力的问题,后来的研究者难以轻松地选择适合自己的模型研究,这种不一致限制了多模态情感识别的发展,于是制作了MER2023 benchmark数据集,和一套模型测试方法,并在众多已有的模型上测试,给出了多指标的测试结果,方便后期工作者了解不同模型的性能。
本文将最近的代表性 MLLM 分为四种主要类型:多模态指令调整(MIT)、多模态上下文学习 (M-ICL)、多模态思维链(M-CoT) 和 LLM 辅助视觉推理 (LAVR)。前三个构成了 MLLM 的基本原理,最后一个是一个以 LLM 作为核心的多模态系统。这三种技术相对独立,可以结合使用。 我们从 M-IT(第 3.1 节)的详细介绍开始,...
However, assessing the utility of MLLMs presents considerable challenges, primarily due to the absence of multimodal benchmarks that align with human preferences. Drawing inspiration from the concept of LLM-as-a-Judge within LLMs, this paper introduces a novel benchmark, termed MLLM-as-a-Judge...
We find that while GPT-4 consistently outperforms LLaVa, both models struggle with every visual network analysis task we propose. We publicly release the first benchmark for the evaluation of VLMs on foundational VNA tasks.Williams, Evan M....
MM-SafetyBench: A Benchmark forSafety Evaluation ofMultimodal Large Language Models The security concerns surrounding Large Language Models (LLMs) have been extensively explored, yet the safety of Multimodal Large Language Models (MLLMs) r... X Liu,Y Zhu,J Gu,... - European Conference on Com...
Multimodal-Robustness-Benchmark This repo contains the official evaluation code and dataset for the paper“Seeing Clearly, Answering Incorrectly: A Multimodal Robustness Benchmark for Evaluating MLLMs on Leading Questions”.📢 News and Updates2024.06...
Then modify the llm_model in the Model Config to the folder that contains Vicuna weights. Run InstructBLIP on our Benchmark Modify the file path and run the script BenchLMM/scripts/InstructBLIP.sh bash BenchLMM/scripts/InstructBLIP.sh Evaluate results Modify the file path and run the scrip...
LLMs, each characterized by its specific formulations. Additionally, we review the performance of MM-LLMs on mainstream benchmarks and summarize key training recipes to enhance the potency of MM-LLMs. Lastly, we explore promising directions for MM-LLMs while concurrently maintaining a real-time ...
115 billion text tokens, and 353 million images, extracted from Common Crawl dumps between February 2020 and February 2023. Models trained on these web documents demonstrate superior performance compared to vision and language models trained exclusively on image-text pairs across a range of benchmark...