1 citations · 1 across the 3 of their papers we have counts for
3 papers
ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, Pengyuan Li, Dhiraj Joshi +24
Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a capability where current vision-language…
Augmenting In-Context-Learning in LLMs via Automatic Data Labeling and Refinement
Joseph Shtok, Amit Alfassy, Foad Abo Dahood +3
It has been shown that Large Language Models' (LLMs) performance can be improved for many tasks using Chain of Thought (CoT) or In-Context Learning (ICL), which involve demonstrati…
Towards Multimodal In-Context Learning for Vision & Language Models
Sivan Doveh, Shaked Perek, M. Jehanzeb Mirza +5
State-of-the-art Vision-Language Models (VLMs) ground the vision and the language modality primarily via projecting the vision tokens from the encoder to language-like tokens, whic…