1.5k citations · 1.6k across the 15 of their papers we have counts for
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What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction Tuning
Yifan Du, Hangyu Guo, Kun Zhou +6
Visual instruction tuning is crucial for enhancing the zero-shot generalization capability of Multi-modal Large Language Models (MLLMs). In this paper, we aim to investigate a fund…
Learning to Imagine: Visually-Augmented Natural Language Generation
Tianyi Tang, Yushuo Chen, Yifan Du +3
People often imagine relevant scenes to aid in the writing process. In this work, we aim to utilize visual information for composition in the same manner as humans. We propose a me…
Zero-shot Visual Question Answering with Language Model Feedback
Yifan Du, Junyi Li, Tianyi Tang +2
In this paper, we propose a novel language model guided captioning approach, LAMOC, for knowledge-based visual question answering (VQA). Our approach employs the generated captions…
Evaluating Object Hallucination in Large Vision-Language Models
Yifan Li, Yifan Du, Kun Zhou +3
Inspired by the superior language abilities of large language models (LLM), large vision-language models (LVLM) have been recently explored by integrating powerful LLMs for improvi…
A Survey of Large Language Models
Wayne Xin Zhao, Kun Zhou, Junyi Li +19
Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for compre…