A new chart dataset with simplified vector encodings and chain-of-thought answers improves fine-tuned MLLM performance on data-centric chart QA, at least for models with strong spatial perception.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.HC 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
SimVecVis: A Dataset for Enhancing MLLMs in Visualization Understanding
A new chart dataset with simplified vector encodings and chain-of-thought answers improves fine-tuned MLLM performance on data-centric chart QA, at least for models with strong spatial perception.