Papers Chart Understanding
“Chart Understanding” 태그가 달린 논문 47편 · 필터 해제
C2F-CHART: A Curriculum Learning Approach to Chart Classification
In scientific research, charts are usually the primary method for visually representing data. However, the accessibility of charts remains a significant concern. In an effort to improve chart understanding pipelines, we …
Chart UnderstandingChartMoE: Mixture of Expert Connector for Advanced Chart Understanding
Automatic chart understanding is crucial for content comprehension and document parsing. Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in chart understanding through domain-specific a…
Chart UnderstandingEvoChart: A Benchmark and a Self-Training Approach Towards Real-World Chart Understanding
Chart understanding enables automated data analysis for humans, which requires models to achieve highly accurate visual comprehension. While existing Visual Language Models (VLMs) have shown progress in chart understandi…
Chart UnderstandingChartEye: A Deep Learning Framework for Chart Information Extraction
The widespread use of charts and infographics as a means of data visualization in various domains has inspired recent research in automated chart understanding. However, information extraction from chart images is a comp…
Chart UnderstandingClassificationData VisualizationDeep Learning+3Revisiting Multi-Modal LLM Evaluation
With the advent of multi-modal large language models (MLLMs), datasets used for visual question answering (VQA) and referring expression comprehension have seen a resurgence. However, the most popular datasets used to ev…
Chart UnderstandingOptical Character RecognitionQuestion AnsweringReferring Expression+3Assessing Graphical Perception of Image Embedding Models using Channel Effectiveness
Recent advancements in vision models have greatly improved their ability to handle complex chart understanding tasks, like chart captioning and question answering. However, it remains challenging to assess how these mode…
Chart UnderstandingQuestion AnsweringOn Pre-training of Multimodal Language Models Customized for Chart Understanding
Recent studies customizing Multimodal Large Language Models (MLLMs) for domain-specific tasks have yielded promising results, especially in the field of scientific chart comprehension. These studies generally utilize vis…
Chart UnderstandingMultimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Although most current large multimodal models (LMMs) can already understand photos of natural scenes and portraits, their understanding of abstract images, e.g., charts, maps, or layouts, and visual reasoning capabilitie…
Chart UnderstandingLanguage ModelingLanguage ModellingVisual ReasoningChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild
Given the ubiquity of charts as a data analysis, visualization, and decision-making tool across industries and sciences, there has been a growing interest in developing pre-trained foundation models as well as general pu…
Chart UnderstandingDecision MakingFact CheckingQuestion AnsweringCharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
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. However, existing datasets often focus on over…
Chart UnderstandingReMI: A Dataset for Reasoning with Multiple Images
With the continuous advancement of large language models (LLMs), it is essential to create new benchmarks to effectively evaluate their expanding capabilities and identify areas for improvement. This work focuses on mult…
Chart UnderstandingMathAre Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs
Natural language is a powerful complementary modality of communication for data visualizations, such as bar and line charts. To facilitate chart-based reasoning using natural language, various downstream tasks have been …
Chart Question AnsweringChart UnderstandingData VisualizationFact Checking+1TinyChart: Efficient Chart Understanding with Visual Token Merging and Program-of-Thoughts Learning
Charts are important for presenting and explaining complex data relationships. Recently, multimodal large language models (MLLMs) have shown remarkable capabilities in various chart understanding tasks. However, the shee…
Chart UnderstandingFrom Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models
Data visualization in the form of charts plays a pivotal role in data analysis, offering critical insights and aiding in informed decision-making. Automatic chart understanding has witnessed significant advancements with…
Chart UnderstandingData VisualizationChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning
Charts provide visual representations of data and are widely used for analyzing information, addressing queries, and conveying insights to others. Various chart-related downstream tasks have emerged recently, such as que…
Chart UnderstandingInstruction FollowingQuestion AnsweringImproving Language Understanding from Screenshots
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 understanding and UI navigation. We refer to thes…
Chart UnderstandingVary: Scaling up the Vision Vocabulary for Large Vision-Language Models
Modern Large Vision-Language Models (LVLMs) enjoy the same vision vocabulary -- CLIP, which can cover most common vision tasks. However, for some special vision task that needs dense and fine-grained vision perception, e…
Chart UnderstandingDecoderOptical Character Recognition (OCR)Visual Question AnsweringChartLlama: A Multimodal LLM for Chart Understanding and Generation
Multi-modal large language models have demonstrated impressive performances on most vision-language tasks. However, the model generally lacks the understanding capabilities for specific domain data, particularly when it …
Chart UnderstandingLanguage ModellingLarge Language ModelMMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning
With the rapid development of large language models (LLMs) and their integration into large multimodal models (LMMs), there has been impressive progress in zero-shot completion of user-oriented vision-language tasks. How…
Chart UnderstandingStructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding
Charts are common in literature across various scientific fields, conveying rich information easily accessible to readers. Current chart-related tasks focus on either chart perception that extracts information from the v…
Chart Question AnsweringChart UnderstandingLanguage ModellingLarge Language Model+2