Papers Factual Inconsistency Detection in Chart Captioning
“Factual Inconsistency Detection in Chart Captioning” 태그가 달린 논문 4편 · 필터 해제
Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning
Recent advancements in large vision-language models (LVLMs) have led to significant progress in generating natural language descriptions for visual content and thus enhancing various applications. One issue with these po…
Factual Inconsistency Detection in Chart CaptioningImage CaptioningVisual EntailmentImproved Baselines with Visual Instruction Tuning
Large multimodal models (LMM) have recently shown encouraging progress with visual instruction tuning. In this note, we show that the fully-connected vision-language cross-modal connector in LLaVA is surprisingly powerfu…
Factual Inconsistency Detection in Chart CaptioningImage ClassificationReferring Expression ComprehensionReferring expression generation+4GPT-4 Technical Report
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-world scenarios, GPT-4 exhibits human-level…
answerability predictionArithmetic ReasoningBug fixingCode Generation+18DePlot: One-shot visual language reasoning by plot-to-table translation
Visual language such as charts and plots is ubiquitous in the human world. Comprehending plots and charts requires strong reasoning skills. Prior state-of-the-art (SOTA) models require at least tens of thousands of train…
Chart Question AnsweringFactual Inconsistency Detection in Chart CaptioningLanguage ModellingLarge Language Model+2