14 citations · 14 across the 1 of their papers we have counts for
3 papers
cs.CL2024
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement
Nicholas Lee, Thanakul Wattanawong, Sehoon Kim +6
Pretrained large language models (LLMs) are currently state-of-the-art for solving the vast majority of natural language processing tasks. While many real-world applications still…
cs.CV2023★ 14 cited
Large Language Models are Visual Reasoning Coordinators
Liangyu Chen, Bo Li, Sheng Shen +5
Visual reasoning requires multimodal perception and commonsense cognition of the world. Recently, multiple vision-language models (VLMs) have been proposed with excellent commonsen…
cs.CV2023
HallE-Control: Controlling Object Hallucination in Large Multimodal Models
Bohan Zhai, Shijia Yang, Chenfeng Xu +4
Current Large Multimodal Models (LMMs) achieve remarkable progress, yet there remains significant uncertainty regarding their ability to accurately apprehend visual details, that i…