2 citations · 2 across the 11 of their papers we have counts for
4 papers · 1 filter
MiCEval: Unveiling Multimodal Chain of Thought's Quality via Image Description and Reasoning Steps
Xiongtao Zhou, Jie He, Lanyu Chen +5
Multimodal Chain of Thought (MCoT) is a popular prompting strategy for improving the performance of multimodal large language models (MLLMs) across a range of complex reasoning tas…
An Empirical Study on Parameter-Efficient Fine-Tuning for MultiModal Large Language Models
Xiongtao Zhou, Jie He, Yuhua Ke +3
Multimodal large language models (MLLMs) fine-tuned with multimodal instruction datasets have demonstrated remarkable capabilities in multimodal tasks. However, fine-tuning all par…
Evaluating and Safeguarding the Adversarial Robustness of Retrieval-Based In-Context Learning
Simon Yu, Jie He, Pasquale Minervini +1
With the emergence of large language models, such as LLaMA and OpenAI GPT-3, In-Context Learning (ICL) gained significant attention due to its effectiveness and efficiency. However…
UniArk: Improving Generalisation and Consistency for Factual Knowledge Extraction through Debiasing
Yijun Yang, Jie He, Pinzhen Chen +2
Several recent papers have investigated the potential of language models as knowledge bases as well as the existence of severe biases when extracting factual knowledge. In this wor…