Papers with Vision-Language
Enhancing Advanced Visual Reasoning Ability of Large Language Models (2024.emnlp-main)
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| Challenge: | Recent advances in Vision-Language (VL) research have sparked new benchmarks for complex visual reasoning, challenging models’ advanced reasoning ability. |
| Approach: | They propose a novel multi-modal in-context learning methodology to enhance LLMs’ contextual understanding and reasoning. |
| Outcome: | The proposed model achieves SOTA performance among all visual reasoning tasks and achieves a 'higher level of accuracy' than previous models. |
MAGMA – Multimodal Augmentation of Generative Models through Adapter-based Finetuning (2022.findings-emnlp)
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| Challenge: | Large-scale pretraining is becoming the norm in Vision-Language (VL) modeling. |
| Approach: | They propose a method for augmenting generative language models with additional modalities using adapter-based finetuning. |
| Outcome: | The proposed method outperforms Frozen on open-ended generative tasks while maintaining the language model weights. |