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Models/MiniGPT-v2

MiniGPT-v2

Reported on 7 benchmarks across 3 tasks · 3 papers · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing4 results

Visual Question Answering (VQA)onInfiMM-Eval
Abductive· 2023-04-20
13.28
best: 77.88 (GPT-4V)
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592
Visual Question Answering (VQA)onInfiMM-Eval
Analogical· 2023-04-20
5.69
best: 69.86 (GPT-4V)
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592
Visual Question Answering (VQA)onInfiMM-Eval
Deductive· 2023-04-20
11.02
best: 74.86 (GPT-4V)
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592
Visual Question Answering (VQA)onInfiMM-Eval
Overall score· 2023-04-20
10.43
best: 74.44 (GPT-4V)
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592

Reasoning3 results

Natural Language Visual GroundingonScreenSpot
Accuracy (%)· 2023-10-14
5.7
best: 86.34 (UGround-V1-7B)
SOTA
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning arXiv:2310.09478
Emotion InterpretationonEIBench (complex)
Recall· 2025-04-10
35.1
best: 39.27 (ChatGPT-4o)
Why We Feel: Breaking Boundaries in Emotional Reasoning with Multimodal Large Language Models arXiv:2504.07521
Emotion InterpretationonEIBench
Recall· 2025-04-10
52.89
best: 63.24 (Claude-3-haiku)
Why We Feel: Breaking Boundaries in Emotional Reasoning with Multimodal Large Language Models arXiv:2504.07521