3 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
Zirui Wang, Mengzhou Xia, Luxi He +10
Chart understanding plays a pivotal role when applying Multimodal Large Language Models (MLLMs) to real-world tasks such as analyzing scientific papers or financial reports. Howeve…
Improving Language Understanding from Screenshots
Tianyu Gao, Zirui Wang, Adithya Bhaskar +1
An emerging family of language models (LMs), capable of processing both text and images within a single visual view, has the promise to unlock complex tasks such as chart understan…
Language Models as Science Tutors
Alexis Chevalier, Jiayi Geng, Alexander Wettig +19
NLP has recently made exciting progress toward training language models (LMs) with strong scientific problem-solving skills. However, model development has not focused on real-life…
Language Models Meet World Models: Embodied Experiences Enhance Language Models
Jiannan Xiang, Tianhua Tao, Yi Gu +4
While large language models (LMs) have shown remarkable capabilities across numerous tasks, they often struggle with simple reasoning and planning in physical environments, such as…