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Visual Question Answering Vqa On Core Mm

Métriques

Abductive

Analogical

Deductive

Overall score

Params

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Abductive	Analogical	Deductive	Overall score	Params	Paper Title	Repository
MiniGPT-v2	13.28	5.69	11.02	10.43	8B	MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
BLIP-2-OPT2.7B	18.96	7.5	2.76	19.31	3B	BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
GPT-4V	77.88	69.86	74.86	74.44	-	GPT-4 Technical Report
SPHINX v2	49.85	20.69	42.17	39.48	16B	SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models
InstructBLIP	37.76	20.56	27.56	28.02	8B	InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Emu	36.57	18.19	28.9	28.24	14B	Emu: Generative Pretraining in Multimodality
Otter	33.64	13.33	22.49	22.69	7B	Otter: A Multi-Modal Model with In-Context Instruction Tuning
CogVLM-Chat	47.88	28.75	36.75	37.16	17B	CogVLM: Visual Expert for Pretrained Language Models
mPLUG-Owl2	20.6	7.64	23.43	20.05	7B	mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration
OpenFlamingo-v2	5.3	1.11	8.88	6.82	9B	OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models
LLaVA-1.5	47.91	24.31	30.94	32.62	13B	Improved Baselines with Visual Instruction Tuning
Qwen-VL-Chat	44.39	30.42	37.55	37.39	16B	Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
LLaMA-Adapter V2	46.12	22.08	28.7	30.46	7B	LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
InternLM-XComposer-VL	35.97	18.61	26.77	26.84	9B	InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition

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