1 citations · 1 across the 17 of their papers we have counts for
4 papers · 1 filter
Multimodal Hypothetical Summary for Retrieval-based Multi-image Question Answering
Peize Li, Qingyi Si, Peng Fu +2
Retrieval-based multi-image question answering (QA) task involves retrieving multiple question-related images and synthesizing these images to generate an answer. Conventional "ret…
Towards Flexible Evaluation for Generative Visual Question Answering
Huishan Ji, Qingyi Si, Zheng Lin +1
Throughout rapid development of multimodal large language models, a crucial ingredient is a fair and accurate evaluation of their multimodal comprehension abilities. Although Visua…
Light-PEFT: Lightening Parameter-Efficient Fine-Tuning via Early Pruning
Naibin Gu, Peng Fu, Xiyu Liu +3
Parameter-efficient fine-tuning (PEFT) has emerged as the predominant technique for fine-tuning in the era of large language models. However, existing PEFT methods still have inade…
Are Large Language Models Table-based Fact-Checkers?
Hanwen Zhang, Qingyi Si, Peng Fu +2
Table-based Fact Verification (TFV) aims to extract the entailment relation between statements and structured tables. Existing TFV methods based on small-scaled models suffer from…