most citedVision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2024

Advancing Chart Question Answering with Robust Chart Component Recognition

Hanwen Zheng, Sijia Wang, Chris Thomas +1

Chart comprehension presents significant challenges for machine learning models due to the diverse and intricate shapes of charts. Existing multimodal methods often overlook these…

cs.CV20243 cited

AMD: Automatic Multi-step Distillation of Large-scale Vision Models

Cheng Han, Qifan Wang, Sohail A. Dianat +6

Transformer-based architectures have become the de-facto standard models for diverse vision tasks owing to their superior performance. As the size of the models continues to scale…

cs.CL2024

InternalInspector : Robust Confidence Estimation in LLMs through Internal States

Mohammad Beigi, Ying Shen, Runing Yang +7

Despite their vast capabilities, Large Language Models (LLMs) often struggle with generating reliable outputs, frequently producing high-confidence inaccuracies known as hallucinat…

cs.CL20242 cited

Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning

Zhiyang Xu, Chao Feng, Rulin Shao +6

Despite vision-language models' (VLMs) remarkable capabilities as versatile visual assistants, two substantial challenges persist within the existing VLM frameworks: (1) lacking ta…

cs.CL2023

A Survey of Document-Level Information Extraction

Hanwen Zheng, Sijia Wang, Lifu Huang

Document-level information extraction (IE) is a crucial task in natural language processing (NLP). This paper conducts a systematic review of recent document-level IE literature. I…