Papers by Teruhisa Misu
ViCor: Bridging Visual Understanding and Commonsense Reasoning with Large Language Models (2024.findings-acl)
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| Challenge: | Existing methods for visual commonsense reasoning (VCR) use pre-trained large language models and pre-training visionlanguage models. |
| Approach: | They propose a collaborative approach where pre-trained LLMs serve as problem classifiers to analyze problem category and either use VLMs to answer directly or actively instruct LLM to gather relevant visual elements to support potential commonsense inferences. |
| Outcome: | The proposed approach outperforms all other methods without in-domain fine-tuning on two VCR benchmark datasets. |
GesNavi: Gesture-guided Outdoor Vision-and-Language Navigation (2024.eacl-srw)
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| Challenge: | Existing datasets for outdoor Vision-and-Language Navigation (VLN) tasks do not include verbal instructions for communicating with mobility. |
| Approach: | They propose a dataset for gesture-guided outdoor VLN instructions with demonstrative expressions that incorporates gestures and linguistic commands. |
| Outcome: | The proposed datasets are compared against existing datasets and analysed in detail. |