Papers by Daiki Shiono
Detecting Response Generation Not Requiring Factual Judgment (2024.naacl-srw)
Copied to clipboard
| Challenge: | Large language models (LLMs) have undergone considerable development and can solve various natural language processing tasks. |
| Approach: | They aimed to achieve both attractiveness and factuality in a dialogue response by crowdsourcing a dataset and performing classification tasks on several models. |
| Outcome: | The proposed model with the highest classification accuracy could yield about 88% accurate classification results. |
Evaluating Model Alignment with Human Perception: A Study on Shitsukan in LLMs and LVLMs (2025.coling-main)
Copied to clipboard
| Challenge: | This work examines the alignment of large language models and large vision-language models with human perception. |
| Approach: | They use a dataset of *shitsukan* terms elicited from individuals in response to object images to evaluate their understanding of the Japanese concept of shitukan. |
| Outcome: | The proposed models demonstrated mixed accuracy across benchmark tasks, with limited overlap between model- and human-generated terms. |