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Found 4 papers, 4 papers with code
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
To bridge this gap, we present MathVista, a benchmark designed to combine challenges from diverse mathematical and visual tasks.
TheoremQA: A Theorem-driven Question Answering dataset
We evaluate a wide spectrum of 16 large language and code models with different prompting strategies like Chain-of-Thoughts and Program-of-Thoughts.
Ranked #1 on
Natural Questions
on TheoremQA
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
We further design language models to learn to generate lectures and explanations as the chain of thought (CoT) to mimic the multi-hop reasoning process when answering ScienceQA questions.
Ranked #5 on
Science Question Answering
on ScienceQA
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
Also, we develop a strong IconQA baseline Patch-TRM that applies a pyramid cross-modal Transformer with input diagram embeddings pre-trained on the icon dataset.
Ranked #1 on
Visual Question Answering (VQA)
on IconQA
