EvALign-ICL
Multimodal model evaluator
Evaluating and improving large multimodal models through in-context learning
[ICLR2024] (EvALign-ICL Benchmark) Beyond Task Performance: Evaluating and Reducing the Flaws of Large Multimodal Models with In-Context Learning
21 stars
2 watching
0 forks
Language: Python
last commit: 11 months ago Related projects:
Repository | Description | Stars |
---|---|---|
pkunlp-icler/pca-eval | An open-source benchmark and evaluation tool for assessing multimodal large language models' performance in embodied decision-making tasks | 99 |
ys-zong/vl-icl | A benchmarking suite for multimodal in-context learning models | 31 |
chenllliang/mmevalpro | A benchmarking framework for evaluating Large Multimodal Models by providing rigorous metrics and an efficient evaluation pipeline. | 22 |
freedomintelligence/mllm-bench | Evaluates and compares the performance of multimodal large language models on various tasks | 56 |
x-plug/mplug-halowl | Evaluates and mitigates hallucinations in multimodal large language models | 82 |
ailab-cvc/seed-bench | A benchmark for evaluating large language models' ability to process multimodal input | 322 |
evolvinglmms-lab/lmms-eval | Tools and evaluation framework for accelerating the development of large multimodal models by providing an efficient way to assess their performance | 2,164 |
yuweihao/mm-vet | Evaluates the capabilities of large multimodal models using a set of diverse tasks and metrics | 274 |
uw-madison-lee-lab/cobsat | Provides a benchmarking framework and dataset for evaluating the performance of large language models in text-to-image tasks | 30 |
yuliang-liu/multimodalocr | An evaluation benchmark for OCR capabilities in large multmodal models. | 484 |
lancopku/iais | This project proposes a novel method for calibrating attention distributions in multimodal models to improve contextualized representations of image-text pairs. | 30 |
multimodal-art-projection/omnibench | Evaluates and benchmarks multimodal language models' ability to process visual, acoustic, and textual inputs simultaneously. | 15 |
open-compass/vlmevalkit | An evaluation toolkit for large vision-language models | 1,514 |
declare-lab/instruct-eval | An evaluation framework for large language models trained with instruction tuning methods | 535 |
esmvalgroup/esmvaltool | A community-developed tool for evaluating climate models and providing diagnostic metrics. | 230 |