As a prominent direction of Artificial General Intelligence (AGI), Multimodal Large Language
Models (MLLMs) have garnered increased attention from both industry and academia …

Emerging multimodal large language models (MLLMs) exhibit great potential for chart
question answering (CQA). Recent efforts primarily focus on scaling up training datasets (ie …

The rapid advancement of Large Language Models (LLMs) and Large Multimodal Models
(LMMs) has heightened the demand for AI-based scientific assistants capable of …

Coding tasks have been valuable for evaluating Large Language Models (LLMs), as they
demand the comprehension of high-level instructions, complex reasoning, and the …

The ability to organically reason over and with both text and images is a pillar of human
intelligence, yet the ability of Multimodal Large Language Models (MLLMs) to perform such …

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in
chart understanding tasks. However, interpreting charts with textual descriptions often leads …

Multimodal large language models (LLMs) have demonstrated impressive capabilities in
generating high-quality images from textual instructions. However, their performance in …

Large Language Models (LLMs) have gained popularity in time series forecasting, but their
potential for anomaly detection remains largely unexplored. Our study investigates whether …

This paper introduces the human-curated PandasPlotBench dataset, designed to evaluate
language models' effectiveness as assistants in visual data exploration. Our benchmark …